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From mdigg...@apache.org
Subject cvs commit: jakarta-commons-sandbox/math/src/java/org/apache/commons/math/util BeanTransformer.java NumberTransformer.java
Date Wed, 17 Sep 2003 19:19:09 GMT
mdiggory    2003/09/17 12:19:09

  Modified:    math/src/java/org/apache/commons/math/stat/distribution
                        BinomialDistribution.java DistributionFactory.java
                        DistributionFactoryImpl.java
               math/src/test/org/apache/commons/math/stat/distribution
                        BinomialDistributionTest.java
                        DistributionFactoryImplTest.java
               math/src/java/org/apache/commons/math/stat Univariate.java
               math/src/java/org/apache/commons/math/util
                        BeanTransformer.java NumberTransformer.java
  Added:       math/src/java/org/apache/commons/math/stat/distribution
                        HypergeometricDistribution.java
                        HypergeometricDistributionImpl.java
               math/src/test/org/apache/commons/math/stat/distribution
                        HypergeometricDistributionTest.java
               math/src/java/org/apache/commons/math/stat Applyable.java
  Log:
  PR: http://nagoya.apache.org/bugzilla/show_bug.cgi?id=23010
  Submitted by:	 Brent Worden 
  Reviewed by:	Mark Diggory
  
  Revision  Changes    Path
  1.2       +2 -2      jakarta-commons-sandbox/math/src/java/org/apache/commons/math/stat/distribution/BinomialDistribution.java
  
  Index: BinomialDistribution.java
  ===================================================================
  RCS file: /home/cvs/jakarta-commons-sandbox/math/src/java/org/apache/commons/math/stat/distribution/BinomialDistribution.java,v
  retrieving revision 1.1
  retrieving revision 1.2
  diff -u -r1.1 -r1.2
  --- BinomialDistribution.java	16 Aug 2003 17:06:15 -0000	1.1
  +++ BinomialDistribution.java	17 Sep 2003 19:19:08 -0000	1.2
  @@ -57,7 +57,7 @@
    * The Binomial Distribution.
    * 
    * Instances of BinomialDistribution objects should be created using
  - * {@link DistributionFactory#createBinomailDistribution(int, double)}.
  + * {@link DistributionFactory#createBinomialDistribution(int, double)}.
    * 
    * References:
    * <ul>
  
  
  
  1.11      +15 -2     jakarta-commons-sandbox/math/src/java/org/apache/commons/math/stat/distribution/DistributionFactory.java
  
  Index: DistributionFactory.java
  ===================================================================
  RCS file: /home/cvs/jakarta-commons-sandbox/math/src/java/org/apache/commons/math/stat/distribution/DistributionFactory.java,v
  retrieving revision 1.10
  retrieving revision 1.11
  diff -u -r1.10 -r1.11
  --- DistributionFactory.java	16 Aug 2003 17:06:15 -0000	1.10
  +++ DistributionFactory.java	17 Sep 2003 19:19:08 -0000	1.11
  @@ -51,6 +51,7 @@
    * information on the Apache Software Foundation, please see
    * <http://www.apache.org/>.
    */
  +
   package org.apache.commons.math.stat.distribution;
   
   /**
  @@ -99,7 +100,7 @@
        * @param probabilityOfSuccess the probability of success.
        * @return a new binomial distribution.
        */
  -    public abstract BinomialDistribution createBinomailDistribution(
  +    public abstract BinomialDistribution createBinomialDistribution(
           int numberOfTrials, double probabilityOfSuccess);
           
       /**
  @@ -142,4 +143,16 @@
        * @return a new t distribution.  
        */
       public abstract TDistribution createTDistribution(double degreesOfFreedom);
  +    
  +    /**
  +     * Create a new hypergeometric distribution with the given the population
  +     * size, the number of successes in the population, and the sample size.
  +     * @param populationSize the population size.
  +     * @param numberOfSuccesses number of successes in the population.
  +     * @param sampleSize the sample size.
  +     * @return a new hypergeometric desitribution.
  +     */
  +    public abstract HypergeometricDistribution
  +        createHypergeometricDistribution(int populationSize,
  +            int numberOfSuccesses, int sampleSize);
   }
  
  
  
  1.9       +19 -2     jakarta-commons-sandbox/math/src/java/org/apache/commons/math/stat/distribution/DistributionFactoryImpl.java
  
  Index: DistributionFactoryImpl.java
  ===================================================================
  RCS file: /home/cvs/jakarta-commons-sandbox/math/src/java/org/apache/commons/math/stat/distribution/DistributionFactoryImpl.java,v
  retrieving revision 1.8
  retrieving revision 1.9
  diff -u -r1.8 -r1.9
  --- DistributionFactoryImpl.java	16 Aug 2003 17:06:15 -0000	1.8
  +++ DistributionFactoryImpl.java	17 Sep 2003 19:19:08 -0000	1.9
  @@ -129,10 +129,27 @@
        * @param probabilityOfSuccess the probability of success.
        * @return a new binomial distribution.
        */
  -    public BinomialDistribution createBinomailDistribution(
  +    public BinomialDistribution createBinomialDistribution(
           int numberOfTrials, double probabilityOfSuccess) {
           return new BinomialDistributionImpl(numberOfTrials,
               probabilityOfSuccess);
  +    }
  +
  +    /**
  +     * Create a new hypergeometric distribution with the given the population
  +     * size, the number of successes in the population, and the sample size.
  +     * @param populationSize the population size.
  +     * @param numberOfSuccesses number of successes in the population.
  +     * @param sampleSize the sample size.
  +     * @return a new hypergeometric desitribution.
  +     */
  +    public HypergeometricDistribution createHypergeometricDistribution(
  +        int populationSize,
  +        int numberOfSuccesses,
  +        int sampleSize)
  +    {
  +        return new HypergeometricDistributionImpl(populationSize,
  +            numberOfSuccesses, sampleSize);
       }
   
   }
  
  
  
  1.1                  jakarta-commons-sandbox/math/src/java/org/apache/commons/math/stat/distribution/HypergeometricDistribution.java
  
  Index: HypergeometricDistribution.java
  ===================================================================
  /* ====================================================================
   * The Apache Software License, Version 1.1
   *
   * Copyright (c) 2003 The Apache Software Foundation.  All rights
   * reserved.
   *
   * Redistribution and use in source and binary forms, with or without
   * modification, are permitted provided that the following conditions
   * are met:
   *
   * 1. Redistributions of source code must retain the above copyright
   *    notice, this list of conditions and the following disclaimer.
   *
   * 2. Redistributions in binary form must reproduce the above copyright
   *    notice, this list of conditions and the following disclaimer in
   *    the documentation and/or other materials provided with the
   *    distribution.
   *
   * 3. The end-user documentation included with the redistribution, if
   *    any, must include the following acknowlegement:
   *       "This product includes software developed by the
   *        Apache Software Foundation (http://www.apache.org/)."
   *    Alternately, this acknowlegement may appear in the software itself,
   *    if and wherever such third-party acknowlegements normally appear.
   *
   * 4. The names "The Jakarta Project", "Commons", and "Apache Software
   *    Foundation" must not be used to endorse or promote products derived
   *    from this software without prior written permission. For written
   *    permission, please contact apache@apache.org.
   *
   * 5. Products derived from this software may not be called "Apache"
   *    nor may "Apache" appear in their names without prior written
   *    permission of the Apache Software Foundation.
   *
   * THIS SOFTWARE IS PROVIDED ``AS IS'' AND ANY EXPRESSED OR IMPLIED
   * WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES
   * OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
   * DISCLAIMED.  IN NO EVENT SHALL THE APACHE SOFTWARE FOUNDATION OR
   * ITS CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
   * SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
   * LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF
   * USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
   * ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
   * OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT
   * OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF
   * SUCH DAMAGE.
   * ====================================================================
   *
   * This software consists of voluntary contributions made by many
   * individuals on behalf of the Apache Software Foundation.  For more
   * information on the Apache Software Foundation, please see
   * <http://www.apache.org/>.
   */
  
  package org.apache.commons.math.stat.distribution;
  
  /**
   * The Hypergeometric Distribution.
   * 
   * Instances of HypergeometricDistribution objects should be created using
   * {@link DistributionFactory#createHypergeometricDistribution(int, int, int)}.
   * 
   * References:
   * <ul>
   * <li><a href="http://mathworld.wolfram.com/HypergeometricDistribution.html">
   * Hypergeometric Distribution</a></li>
   * </ul>
   * 
   * @version $Revision: 1.1 $ $Date: 2003/09/17 19:19:08 $
   */
  public interface HypergeometricDistribution extends DiscreteDistribution {
      /**
       * Access the number of successes.
       * @return the number of successes.
       */
      public abstract int getNumberOfSuccesses();
      
      /**
       * Access the population size.
       * @return the population size.
       */
      public abstract int getPopulationSize();
      
      /**
       * Access the sample size.
       * @return the sample size.
       */
      public abstract int getSampleSize();
      
      /**
       * Modify the number of successes.
       * @param num the new number of successes.
       */
      public abstract void setNumberOfSuccesses(int num);
      
      /**
       * Modify the population size.
       * @param size the new population size.
       */
      public abstract void setPopulationSize(int size);
      
      /**
       * Modify the sample size.
       * @param size the new sample size.
       */
      public abstract void setSampleSize(int size);
  }
  
  
  
  1.1                  jakarta-commons-sandbox/math/src/java/org/apache/commons/math/stat/distribution/HypergeometricDistributionImpl.java
  
  Index: HypergeometricDistributionImpl.java
  ===================================================================
  /* ====================================================================
   * The Apache Software License, Version 1.1
   *
   * Copyright (c) 2003 The Apache Software Foundation.  All rights
   * reserved.
   *
   * Redistribution and use in source and binary forms, with or without
   * modification, are permitted provided that the following conditions
   * are met:
   *
   * 1. Redistributions of source code must retain the above copyright
   *    notice, this list of conditions and the following disclaimer.
   *
   * 2. Redistributions in binary form must reproduce the above copyright
   *    notice, this list of conditions and the following disclaimer in
   *    the documentation and/or other materials provided with the
   *    distribution.
   *
   * 3. The end-user documentation included with the redistribution, if
   *    any, must include the following acknowlegement:
   *       "This product includes software developed by the
   *        Apache Software Foundation (http://www.apache.org/)."
   *    Alternately, this acknowlegement may appear in the software itself,
   *    if and wherever such third-party acknowlegements normally appear.
   *
   * 4. The names "The Jakarta Project", "Commons", and "Apache Software
   *    Foundation" must not be used to endorse or promote products derived
   *    from this software without prior written permission. For written
   *    permission, please contact apache@apache.org.
   *
   * 5. Products derived from this software may not be called "Apache"
   *    nor may "Apache" appear in their names without prior written
   *    permission of the Apache Software Foundation.
   *
   * THIS SOFTWARE IS PROVIDED ``AS IS'' AND ANY EXPRESSED OR IMPLIED
   * WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES
   * OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
   * DISCLAIMED.  IN NO EVENT SHALL THE APACHE SOFTWARE FOUNDATION OR
   * ITS CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
   * SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
   * LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF
   * USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
   * ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
   * OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT
   * OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF
   * SUCH DAMAGE.
   * ====================================================================
   *
   * This software consists of voluntary contributions made by many
   * individuals on behalf of the Apache Software Foundation.  For more
   * information on the Apache Software Foundation, please see
   * <http://www.apache.org/>.
   */
  
  package org.apache.commons.math.stat.distribution;
  
  import org.apache.commons.math.util.MathUtils;
  
  /**
   * The default implementation of {@link HypergeometricDistribution}.
   * 
   * @version $Revision: 1.1 $ $Date: 2003/09/17 19:19:08 $
   */
  public class HypergeometricDistributionImpl extends AbstractDiscreteDistribution
      implements HypergeometricDistribution
  {
  
      /** The number of successes in the population. */
      private int numberOfSuccesses;
      
      /** The population size. */
      private int populationSize;
      
      /** The sample size. */
      private int sampleSize;
      
      /**
       * Construct a new hypergeometric distribution with the given the population
       * size, the number of successes in the population, and the sample size.
       * @param populationSize the population size.
       * @param numberOfSuccesses number of successes in the population.
       * @param sampleSize the sample size.
       */
      public HypergeometricDistributionImpl(int populationSize,
          int numberOfSuccesses, int sampleSize)
      {
          super();
          setPopulationSize(populationSize);
          setSampleSize(sampleSize);
          setNumberOfSuccesses(numberOfSuccesses);
      }
  
      /**
       * For this disbution, X, this method returns P(X &le; x).
       * @param x the value at which the PDF is evaluated.
       * @return PDF for this distribution. 
       */
      public double cummulativeProbability(int x) {
          double ret;
          
          int n = getPopulationSize();
          int m = getNumberOfSuccesses();
          int k = getSampleSize();
  
          int[] domain = getDomain(n, m, k);
          if (x < domain[0]) {
              ret = 0.0;
          } else if(x >= domain[1]) {
              ret = 1.0;
          } else {
              ret = 0.0;
              for (int i = domain[0]; i <= x; ++i){
                  ret += probability(n, m, k, i);
              }
          }
          
          return ret;
      }
  
      /**
       * Return the domain for the given hypergeometric distribution parameters.
       * @param n the population size.
       * @param m number of successes in the population.
       * @param k the sample size.
       * @return a two element array containing the lower and upper bounds of the
       *         hypergeometric distribution.  
       */
      private int[] getDomain(int n, int m, int k){
          return new int[]{
              getLowerDomain(n, m, k),
              getUpperDomain(m, k)
          };
      }
      
      /**
       * Access the domain value lower bound, based on <code>p</code>, used to
       * bracket a PDF root.
       * 
       * @param p the desired probability for the critical value
       * @return domain value lower bound, i.e.
       *         P(X &lt; <i>lower bound</i>) &lt; <code>p</code>

       */
      protected int getDomainLowerBound(double p) {
          return getLowerDomain(getPopulationSize(), getNumberOfSuccesses(),
              getSampleSize());
      }
      
      /**
       * Access the domain value upper bound, based on <code>p</code>, used to
       * bracket a PDF root.
       * 
       * @param p the desired probability for the critical value
       * @return domain value upper bound, i.e.
       *         P(X &lt; <i>upper bound</i>) &gt; <code>p</code>

       */
      protected int getDomainUpperBound(double p) {
          return getUpperDomain(getSampleSize(), getNumberOfSuccesses());
      }
  
      /**
       * Return the lowest domain value for the given hypergeometric distribution
       * parameters.
       * @param n the population size.
       * @param m number of successes in the population.
       * @param k the sample size.
       * @return the lowest domain value of the hypergeometric distribution.  
       */
      private int getLowerDomain(int n, int m, int k) {
          return Math.max(0, m - (n - k));
      }
  
      /**
       * Access the number of successes.
       * @return the number of successes.
       */
      public int getNumberOfSuccesses() {
          return numberOfSuccesses;
      }
  
      /**
       * Access the population size.
       * @return the population size.
       */
      public int getPopulationSize() {
          return populationSize;
      }
  
      /**
       * Access the sample size.
       * @return the sample size.
       */
      public int getSampleSize() {
          return sampleSize;
      }
  
      /**
       * Return the highest domain value for the given hypergeometric distribution
       * parameters.
       * @param m number of successes in the population.
       * @param k the sample size.
       * @return the highest domain value of the hypergeometric distribution.  
       */
      private int getUpperDomain(int m, int k){
          return Math.min(k, m);
      }
  
      /**
       * For this disbution, X, this method returns P(X = x).
       * @param x the value at which the PMF is evaluated.
       * @return PMF for this distribution. 
       */
      public double probability(int x) {
          double ret;
          
          int n = getPopulationSize();
          int m = getNumberOfSuccesses();
          int k = getSampleSize();
  
          int[] domain = getDomain(n, m, k);
          if(x < domain[0] || x > domain[1]){
              ret = 0.0;
          } else {
              ret = probability(n, m, k, x);
          }
          
          return ret;
      }
  
      /**
       * For the disbution, X, defined by the given hypergeometric distribution
       * parameters, this method returns P(X = x).
       * @param n the population size.
       * @param m number of successes in the population.
       * @param k the sample size.
       * @param x the value at which the PMF is evaluated.
       * @return PMF for the distribution. 
       */
      private double probability(int n, int m, int k, int x) {
          return Math.exp(MathUtils.binomialCoefficientLog(m, x) +
              MathUtils.binomialCoefficientLog(n - m, k - x) -
              MathUtils.binomialCoefficientLog(n, k));
      }
      
      /**
       * Modify the number of successes.
       * @param num the new number of successes.
       */
      public void setNumberOfSuccesses(int num) {
          if(num < 0){
              throw new IllegalArgumentException(
                  "number of successes must be non-negative.");
          }
          numberOfSuccesses = num;
      }
  
      /**
       * Modify the population size.
       * @param size the new population size.
       */
      public void setPopulationSize(int size) {
          if(size <= 0){
              throw new IllegalArgumentException(
                  "population size must be positive.");
          }
          populationSize = size;
      }
  
      /**
       * Modify the sample size.
       * @param size the new sample size.
       */
      public void setSampleSize(int size) {
          if(size < 0){
              throw new IllegalArgumentException(
                  "sample size must be non-negative.");
          }
          sampleSize = size;
      }
  }
  
  
  
  1.2       +1 -1      jakarta-commons-sandbox/math/src/test/org/apache/commons/math/stat/distribution/BinomialDistributionTest.java
  
  Index: BinomialDistributionTest.java
  ===================================================================
  RCS file: /home/cvs/jakarta-commons-sandbox/math/src/test/org/apache/commons/math/stat/distribution/BinomialDistributionTest.java,v
  retrieving revision 1.1
  retrieving revision 1.2
  diff -u -r1.1 -r1.2
  --- BinomialDistributionTest.java	16 Aug 2003 17:06:15 -0000	1.1
  +++ BinomialDistributionTest.java	17 Sep 2003 19:19:09 -0000	1.2
  @@ -74,7 +74,7 @@
        */
       protected void setUp() throws Exception {
           super.setUp();
  -        b = DistributionFactory.newInstance().createBinomailDistribution(10, 0.70);
  +        b = DistributionFactory.newInstance().createBinomialDistribution(10, 0.70);
       }
   
       /*
  
  
  
  1.8       +55 -7     jakarta-commons-sandbox/math/src/test/org/apache/commons/math/stat/distribution/DistributionFactoryImplTest.java
  
  Index: DistributionFactoryImplTest.java
  ===================================================================
  RCS file: /home/cvs/jakarta-commons-sandbox/math/src/test/org/apache/commons/math/stat/distribution/DistributionFactoryImplTest.java,v
  retrieving revision 1.7
  retrieving revision 1.8
  diff -u -r1.7 -r1.8
  --- DistributionFactoryImplTest.java	16 Aug 2003 17:06:15 -0000	1.7
  +++ DistributionFactoryImplTest.java	17 Sep 2003 19:19:09 -0000	1.8
  @@ -200,7 +200,7 @@
       
       public void testBinomialDistributionNegativePositive(){
           try {
  -            factory.createBinomailDistribution(-1, 0.5);
  +            factory.createBinomialDistribution(-1, 0.5);
               fail("negative number of trials.  IllegalArgumentException expected");
           } catch (IllegalArgumentException ex ) {
           }
  @@ -208,7 +208,7 @@
       
       public void testBinomialDistributionZeroPositive(){
           try {
  -            factory.createBinomailDistribution(0, 0.5);
  +            factory.createBinomialDistribution(0, 0.5);
           } catch (IllegalArgumentException ex ) {
               fail("zero number of trials.  IllegalArgumentException is not expected");
           }
  @@ -216,7 +216,7 @@
       
       public void testBinomialDistributionPositivePositive(){
           try {
  -            factory.createBinomailDistribution(10, 0.5);
  +            factory.createBinomialDistribution(10, 0.5);
           } catch (IllegalArgumentException ex ) {
               fail("positive number of trials.  IllegalArgumentException is not expected");
           }
  @@ -224,7 +224,7 @@
       
       public void testBinomialDistributionPositiveNegative(){
           try {
  -            factory.createBinomailDistribution(10, -0.5);
  +            factory.createBinomialDistribution(10, -0.5);
               fail("negative probability of success.  IllegalArgumentException expected");
           } catch (IllegalArgumentException ex ) {
           }
  @@ -232,7 +232,7 @@
       
       public void testBinomialDistributionPositiveZero(){
           try {
  -            factory.createBinomailDistribution(10, 0.0);
  +            factory.createBinomialDistribution(10, 0.0);
           } catch (IllegalArgumentException ex ) {
               fail("zero probability of success.  IllegalArgumentException is not expected");
           }
  @@ -240,7 +240,7 @@
       
       public void testBinomialDistributionPositiveOne(){
           try {
  -            factory.createBinomailDistribution(10, 1.0);
  +            factory.createBinomialDistribution(10, 1.0);
           } catch (IllegalArgumentException ex ) {
               fail("valid probability of success.  IllegalArgumentException is not expected");
           }
  @@ -248,9 +248,57 @@
       
       public void testBinomialDistributionPositiveTwo(){
           try {
  -            factory.createBinomailDistribution(10, 2.0);
  +            factory.createBinomialDistribution(10, 2.0);
               fail("high probability of success.  IllegalArgumentException expected");
           } catch (IllegalArgumentException ex ) {
  +        }
  +    }
  +    
  +    public void testHypergeometricDistributionNegativePositivePositive(){
  +        try {
  +            factory.createHypergeometricDistribution(-1, 10, 10);
  +            fail("negative population size.  IllegalArgumentException expected");
  +        } catch(IllegalArgumentException ex) {
  +        }
  +    }
  +    
  +    public void testHypergeometricDistributionZeroPositivePositive(){
  +        try {
  +            factory.createHypergeometricDistribution(0, 10, 10);
  +            fail("zero population size.  IllegalArgumentException expected");
  +        } catch(IllegalArgumentException ex) {
  +        }
  +    }
  +    
  +    public void testHypergeometricDistributionPositiveNegativePositive(){
  +        try {
  +            factory.createHypergeometricDistribution(20, -1, 10);
  +            fail("negative number of successes.  IllegalArgumentException expected");
  +        } catch(IllegalArgumentException ex) {
  +        }
  +    }
  +    
  +    public void testHypergeometricDistributionPositiveZeroPositive(){
  +        try {
  +            factory.createHypergeometricDistribution(20, 0, 10);
  +        } catch(IllegalArgumentException ex) {
  +            fail("valid number of successes.  IllegalArgumentException is not expected");
  +        }
  +    }
  +    
  +    public void testHypergeometricDistributionPositivePositiveNegative(){
  +        try {
  +            factory.createHypergeometricDistribution(20, 10, -1);
  +            fail("negative sample size.  IllegalArgumentException expected");
  +        } catch(IllegalArgumentException ex) {
  +        }
  +    }
  +    
  +    public void testHypergeometricDistributionPositivePositiveZero(){
  +        try {
  +            factory.createHypergeometricDistribution(20, 10, 0);
  +        } catch(IllegalArgumentException ex) {
  +            fail("valid sample size.  IllegalArgumentException is not expected");
           }
       }
   }
  
  
  
  1.1                  jakarta-commons-sandbox/math/src/test/org/apache/commons/math/stat/distribution/HypergeometricDistributionTest.java
  
  Index: HypergeometricDistributionTest.java
  ===================================================================
  /* ====================================================================
   * The Apache Software License, Version 1.1
   *
   * Copyright (c) 2003 The Apache Software Foundation.  All rights
   * reserved.
   *
   * Redistribution and use in source and binary forms, with or without
   * modification, are permitted provided that the following conditions
   * are met:
   *
   * 1. Redistributions of source code must retain the above copyright
   *    notice, this list of conditions and the following disclaimer.
   *
   * 2. Redistributions in binary form must reproduce the above copyright
   *    notice, this list of conditions and the following disclaimer in
   *    the documentation and/or other materials provided with the
   *    distribution.
   *
   * 3. The end-user documentation included with the redistribution, if
   *    any, must include the following acknowlegement:
   *       "This product includes software developed by the
   *        Apache Software Foundation (http://www.apache.org/)."
   *    Alternately, this acknowlegement may appear in the software itself,
   *    if and wherever such third-party acknowlegements normally appear.
   *
   * 4. The names "The Jakarta Project", "Commons", and "Apache Software
   *    Foundation" must not be used to endorse or promote products derived
   *    from this software without prior written permission. For written
   *    permission, please contact apache@apache.org.
   *
   * 5. Products derived from this software may not be called "Apache"
   *    nor may "Apache" appear in their names without prior written
   *    permission of the Apache Software Foundation.
   *
   * THIS SOFTWARE IS PROVIDED ``AS IS'' AND ANY EXPRESSED OR IMPLIED
   * WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES
   * OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
   * DISCLAIMED.  IN NO EVENT SHALL THE APACHE SOFTWARE FOUNDATION OR
   * ITS CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
   * SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
   * LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF
   * USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
   * ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
   * OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT
   * OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF
   * SUCH DAMAGE.
   * ====================================================================
   *
   * This software consists of voluntary contributions made by many
   * individuals on behalf of the Apache Software Foundation.  For more
   * information on the Apache Software Foundation, please see
   * <http://www.apache.org/>.
   */
  
  package org.apache.commons.math.stat.distribution;
  
  import junit.framework.TestCase;
  
  /**
   * @version $Revision: 1.1 $ $Date: 2003/09/17 19:19:09 $
   */
  public class HypergeometricDistributionTest extends TestCase {
      private HypergeometricDistribution h;
      
      /**
       * Constructor for ChiSquareDistributionTest.
       * @param name
       */
      public HypergeometricDistributionTest(String name) {
          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();
      }
  
      public void testInverseCummulativeProbability001() {
          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 testInverseCummulativeProbability999() {
          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 testCummulativeProbability0() {
          testProbability(0, .00400);
      }
  
      public void testCummulativeProbability1() {
          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){
          double actual = h.cummulativeProbability(x);
          assertEquals(expected, actual, 10e-4);
      }
      
      private void testValue(int expected, double p){
          int actual = h.inverseCummulativeProbability(p);
          assertEquals(expected, actual);
          assertTrue(h.cummulativeProbability(actual) <= p);
          assertTrue(h.cummulativeProbability(actual + 1) >= p);
      }
  }
  
  
  
  1.9       +2 -2      jakarta-commons-sandbox/math/src/java/org/apache/commons/math/stat/Univariate.java
  
  Index: Univariate.java
  ===================================================================
  RCS file: /home/cvs/jakarta-commons-sandbox/math/src/java/org/apache/commons/math/stat/Univariate.java,v
  retrieving revision 1.8
  retrieving revision 1.9
  diff -u -r1.8 -r1.9
  --- Univariate.java	9 Jul 2003 21:45:23 -0000	1.8
  +++ Univariate.java	17 Sep 2003 19:19:09 -0000	1.9
  @@ -71,7 +71,7 @@
    * in all computations.
    * @version $Revision$ $Date$
   */
  -public interface Univariate {
  +public interface Univariate extends Applyable{
       /**
        * A LEPTOKURTIC set has a positive kurtosis (a high peak) 
        */
  
  
  
  1.1                  jakarta-commons-sandbox/math/src/java/org/apache/commons/math/stat/Applyable.java
  
  Index: Applyable.java
  ===================================================================
  /*
   * Created on Jul 15, 2003
   *
   */
  package org.apache.commons.math.stat;
  
  import org.apache.commons.math.stat.univariate.UnivariateStatistic;
  
  /**
   * Applyable.java
   * 
   * To change the template for this generated type comment go to
   * Window>Preferences>Java>Code Generation>Code and Comments
   * 
   */
  public interface Applyable {
      
      /**
       * Applies a UnivariateStatistic object against this object 
       * and returns the result.
       * @param stat The stat to apply.
       * @return The result value of the application.
       */
      double apply(UnivariateStatistic stat);
      
  }
  
  
  
  1.5       +6 -5      jakarta-commons-sandbox/math/src/java/org/apache/commons/math/util/BeanTransformer.java
  
  Index: BeanTransformer.java
  ===================================================================
  RCS file: /home/cvs/jakarta-commons-sandbox/math/src/java/org/apache/commons/math/util/BeanTransformer.java,v
  retrieving revision 1.4
  retrieving revision 1.5
  diff -u -r1.4 -r1.5
  --- BeanTransformer.java	9 Aug 2003 04:03:41 -0000	1.4
  +++ BeanTransformer.java	17 Sep 2003 19:19:09 -0000	1.5
  @@ -55,6 +55,7 @@
   
   import java.lang.reflect.InvocationTargetException;
   import org.apache.commons.beanutils.PropertyUtils;
  +import org.apache.commons.math.MathException;
   
   /**
    * Uses PropertyUtils to map a Bean getter to a double value.
  @@ -85,18 +86,18 @@
       /**
        * @see org.apache.commons.math.util.NumberTransformer#transform(java.lang.Object)
        */
  -    public double transform(final Object o) {
  +    public double transform(final Object o) throws MathException {
           double d = Double.NaN;
           try {
               d =
                   ((Number) PropertyUtils.getProperty(o, propertyName))
                       .doubleValue();
           } catch (IllegalAccessException e) {
  -            e.printStackTrace();
  +            throw new MathException(e.getMessage(),e);
           } catch (InvocationTargetException e) {
  -            e.printStackTrace();
  +            throw new MathException(e.getMessage(),e);
           } catch (NoSuchMethodException e) {
  -            e.printStackTrace();
  +            throw new MathException(e.getMessage(),e);
           }
           return d;
       }
  
  
  
  1.4       +4 -2      jakarta-commons-sandbox/math/src/java/org/apache/commons/math/util/NumberTransformer.java
  
  Index: NumberTransformer.java
  ===================================================================
  RCS file: /home/cvs/jakarta-commons-sandbox/math/src/java/org/apache/commons/math/util/NumberTransformer.java,v
  retrieving revision 1.3
  retrieving revision 1.4
  diff -u -r1.3 -r1.4
  --- NumberTransformer.java	9 Jul 2003 20:04:12 -0000	1.3
  +++ NumberTransformer.java	17 Sep 2003 19:19:09 -0000	1.4
  @@ -53,6 +53,8 @@
    */
   package org.apache.commons.math.util;
   
  +import org.apache.commons.math.MathException;
  +
   /**
    * Subclasses implementing this interface can transform Objects to doubles.
    * @version $Revision$ $Date$
  @@ -66,5 +68,5 @@
        * @param o the Object to be transformed.
        * @return the double value of the Object.
        */
  -    double transform(Object o);
  +    double transform(Object o) throws MathException;
   }
  
  
  

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