Coverage Report - org.apache.commons.math.distribution.DistributionFactory

Classes in this File Line Coverage Branch Coverage Complexity
DistributionFactory
83% 
100% 
1.143

 1  
 /*
 2  
  * Copyright 2003-2005 The Apache Software Foundation.
 3  
  *
 4  
  * Licensed under the Apache License, Version 2.0 (the "License");
 5  
  * you may not use this file except in compliance with the License.
 6  
  * You may obtain a copy of the License at
 7  
  *
 8  
  *      http://www.apache.org/licenses/LICENSE-2.0
 9  
  *
 10  
  * Unless required by applicable law or agreed to in writing, software
 11  
  * distributed under the License is distributed on an "AS IS" BASIS,
 12  
  * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 13  
  * See the License for the specific language governing permissions and
 14  
  * limitations under the License.
 15  
  */
 16  
 
 17  
 package org.apache.commons.math.distribution;
 18  
 
 19  
 import org.apache.commons.discovery.tools.DiscoverClass;
 20  
 
 21  
 /**
 22  
  * This factory provids the means to create common statistical distributions.
 23  
  * The following distributions are supported:
 24  
  * <ul>
 25  
  * <li>Binomial</li>
 26  
  * <li>Cauchy</li>
 27  
  * <li>Chi-Squared</li>
 28  
  * <li>Exponential</li>
 29  
  * <li>F</li>
 30  
  * <li>Gamma</li>
 31  
  * <li>HyperGeometric</li>
 32  
  * <li>Poisson</li>
 33  
  * <li>Normal</li>
 34  
  * <li>Student's t</li>
 35  
  * <li>Weibull</li>
 36  
  * </ul>
 37  
  *
 38  
  * Common usage:<pre>
 39  
  * DistributionFactory factory = DistributionFactory.newInstance();
 40  
  *
 41  
  * // create a Chi-Square distribution with 5 degrees of freedom.
 42  
  * ChiSquaredDistribution chi = factory.createChiSquareDistribution(5.0);
 43  
  * </pre>
 44  
  *
 45  
  * @version $Revision$ $Date: 2005-06-26 15:20:57 -0700 (Sun, 26 Jun 2005) $
 46  
  */
 47  
 public abstract class DistributionFactory {
 48  
     /**
 49  
      * Default constructor.
 50  
      */
 51  
     protected DistributionFactory() {
 52  464
         super();
 53  464
     }
 54  
     
 55  
     /**
 56  
      * Create an instance of a <code>DistributionFactory</code>
 57  
      * @return a new factory. 
 58  
      */
 59  
     public static DistributionFactory newInstance() {
 60  386
         DistributionFactory factory = null;
 61  
         try {
 62  386
             DiscoverClass dc = new DiscoverClass();
 63  386
             factory = (DistributionFactory) dc.newInstance(
 64  36
                 DistributionFactory.class,
 65  
                 "org.apache.commons.math.distribution.DistributionFactoryImpl");
 66  0
         } catch(Throwable t) {
 67  0
             return new DistributionFactoryImpl();
 68  386
         }
 69  386
         return factory;
 70  
     }
 71  
 
 72  
     /**
 73  
      * Create a binomial distribution with the given number of trials and
 74  
      * probability of success.
 75  
      * 
 76  
      * @param numberOfTrials the number of trials.
 77  
      * @param probabilityOfSuccess the probability of success
 78  
      * @return a new binomial distribution
 79  
      */
 80  
     public abstract BinomialDistribution createBinomialDistribution(
 81  
         int numberOfTrials, double probabilityOfSuccess);
 82  
     
 83  
     /**
 84  
      * Create a new cauchy distribution with the given median and scale.
 85  
      * @param median the median of the distribution
 86  
      * @param scale the scale
 87  
      * @return a new cauchy distribution  
 88  
      * @since 1.1
 89  
      */           
 90  
     public CauchyDistribution createCauchyDistribution(
 91  
         double median, double scale)
 92  
     {
 93  20
         return new CauchyDistributionImpl(median, scale);
 94  
     }
 95  
         
 96  
     /**
 97  
      * Create a new chi-square distribution with the given degrees of freedom.
 98  
      * 
 99  
      * @param degreesOfFreedom degrees of freedom
 100  
      * @return a new chi-square distribution  
 101  
      */
 102  
     public abstract ChiSquaredDistribution createChiSquareDistribution(
 103  
         double degreesOfFreedom);
 104  
     
 105  
     /**
 106  
      * Create a new exponential distribution with the given degrees of freedom.
 107  
      * 
 108  
      * @param mean mean
 109  
      * @return a new exponential distribution  
 110  
      */
 111  
     public abstract ExponentialDistribution createExponentialDistribution(
 112  
         double mean);
 113  
     
 114  
     /**
 115  
      * Create a new F-distribution with the given degrees of freedom.
 116  
      * 
 117  
      * @param numeratorDegreesOfFreedom numerator degrees of freedom
 118  
      * @param denominatorDegreesOfFreedom denominator degrees of freedom
 119  
      * @return a new F-distribution 
 120  
      */
 121  
     public abstract FDistribution createFDistribution(
 122  
         double numeratorDegreesOfFreedom, double denominatorDegreesOfFreedom);
 123  
     
 124  
     /**
 125  
      * Create a new gamma distribution with the given shape and scale
 126  
      * parameters.
 127  
      * 
 128  
      * @param alpha the shape parameter
 129  
      * @param beta the scale parameter
 130  
      * 
 131  
      * @return a new gamma distribution  
 132  
      */
 133  
     public abstract GammaDistribution createGammaDistribution(
 134  
         double alpha, double beta);
 135  
 
 136  
     /**
 137  
      * Create a new t distribution with the given degrees of freedom.
 138  
      * 
 139  
      * @param degreesOfFreedom degrees of freedom
 140  
      * @return a new t distribution  
 141  
      */
 142  
     public abstract TDistribution createTDistribution(double degreesOfFreedom);
 143  
     
 144  
     /**
 145  
      * Create a new hypergeometric distribution with the given the population
 146  
      * size, the number of successes in the population, and the sample size.
 147  
      * 
 148  
      * @param populationSize the population size
 149  
      * @param numberOfSuccesses number of successes in the population
 150  
      * @param sampleSize the sample size
 151  
      * @return a new hypergeometric desitribution
 152  
      */
 153  
     public abstract HypergeometricDistribution
 154  
         createHypergeometricDistribution(int populationSize,
 155  
             int numberOfSuccesses, int sampleSize);
 156  
  
 157  
     /**
 158  
      * Create a new normal distribution with the given mean and standard
 159  
      * deviation.
 160  
      * 
 161  
      * @param mean the mean of the distribution
 162  
      * @param sd standard deviation
 163  
      * @return a new normal distribution  
 164  
      */           
 165  
     public abstract NormalDistribution 
 166  
         createNormalDistribution(double mean, double sd);
 167  
         
 168  
     /**
 169  
      * Create a new normal distribution with mean zero and standard
 170  
      * deviation one.
 171  
      * 
 172  
      * @return a new normal distribution.  
 173  
      */               
 174  
     public abstract NormalDistribution createNormalDistribution();
 175  
     
 176  
     /**
 177  
      * Create a new Poisson distribution with poisson parameter lambda.
 178  
      * 
 179  
      * @param lambda poisson parameter
 180  
      * @return a new poisson distribution.  
 181  
      */               
 182  
     public abstract PoissonDistribution 
 183  
         createPoissonDistribution(double lambda);
 184  
     
 185  
     /**
 186  
      * Create a new Weibull distribution with the given shape and scale
 187  
      * parameters.
 188  
      * 
 189  
      * @param alpha the shape parameter.
 190  
      * @param beta the scale parameter.
 191  
      * @return a new Weibull distribution.  
 192  
      * @since 1.1
 193  
      */               
 194  
     public WeibullDistribution createWeibullDistribution(
 195  
         double alpha, double beta)
 196  
     {
 197  26
         return new WeibullDistributionImpl(alpha, beta);
 198  
     }
 199  
 }