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

Classes in this File	Line Coverage	Branch Coverage	Complexity
DistributionFactoryImpl	92%	N/A	1.0;1

1		/*
2		* Copyright 2003-2004 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		package org.apache.commons.math.distribution;
17
18		/**
19		* A concrete distribution factory. This is the default factory used by
20		* Commons-Math.
21		*
22		* @version $Revision$ $Date: 2005-06-26 15:20:57 -0700 (Sun, 26 Jun 2005) $
23		*/
24		public class DistributionFactoryImpl extends DistributionFactory {
25
26		/**
27		* Default constructor. Package scope to prevent unwanted instantiation.
28		*/
29		public DistributionFactoryImpl() {
30	464	super();
31	464	}
32
33		/**
34		* Create a new chi-square distribution with the given degrees of freedom.
35		*
36		* @param degreesOfFreedom degrees of freedom
37		* @return a new chi-square distribution
38		*/
39		public ChiSquaredDistribution createChiSquareDistribution(
40		final double degreesOfFreedom) {
41
42	98	return new ChiSquaredDistributionImpl(degreesOfFreedom);
43		}
44
45		/**
46		* Create a new gamma distribution the given shape and scale parameters.
47		*
48		* @param alpha the shape parameter
49		* @param beta the scale parameter
50		* @return a new gamma distribution
51		*/
52		public GammaDistribution createGammaDistribution(
53		double alpha, double beta) {
54
55	142	return new GammaDistributionImpl(alpha, beta);
56		}
57
58		/**
59		* Create a new t distribution with the given degrees of freedom.
60		*
61		* @param degreesOfFreedom degrees of freedom
62		* @return a new t distribution.
63		*/
64		public TDistribution createTDistribution(double degreesOfFreedom) {
65	176	return new TDistributionImpl(degreesOfFreedom);
66		}
67
68		/**
69		* Create a new F-distribution with the given degrees of freedom.
70		*
71		* @param numeratorDegreesOfFreedom numerator degrees of freedom
72		* @param denominatorDegreesOfFreedom denominator degrees of freedom
73		* @return a new F-distribution
74		*/
75		public FDistribution createFDistribution(
76		double numeratorDegreesOfFreedom,
77		double denominatorDegreesOfFreedom) {
78	26	return new FDistributionImpl(numeratorDegreesOfFreedom,
79		denominatorDegreesOfFreedom);
80		}
81
82		/**
83		* Create a new exponential distribution with the given degrees of freedom.
84		*
85		* @param mean mean
86		* @return a new exponential distribution
87		*/
88		public ExponentialDistribution createExponentialDistribution(double mean) {
89	22	return new ExponentialDistributionImpl(mean);
90		}
91
92		/**
93		* Create a binomial distribution with the given number of trials and
94		* probability of success.
95		*
96		* @param numberOfTrials the number of trials
97		* @param probabilityOfSuccess the probability of success
98		* @return a new binomial distribution
99		*/
100		public BinomialDistribution createBinomialDistribution(
101		int numberOfTrials, double probabilityOfSuccess) {
102	30	return new BinomialDistributionImpl(numberOfTrials,
103		probabilityOfSuccess);
104		}
105
106		/**
107		* Create a new hypergeometric distribution with the given the population
108		* size, the number of successes in the population, and the sample size.
109		*
110		* @param populationSize the population size
111		* @param numberOfSuccesses number of successes in the population
112		* @param sampleSize the sample size
113		* @return a new hypergeometric desitribution
114		*/
115		public HypergeometricDistribution createHypergeometricDistribution(
116		int populationSize, int numberOfSuccesses, int sampleSize) {
117	42	return new HypergeometricDistributionImpl(populationSize,
118		numberOfSuccesses, sampleSize);
119		}
120
121		/**
122		* Create a new normal distribution with the given mean and standard
123		* deviation.
124		*
125		* @param mean the mean of the distribution
126		* @param sd standard deviation
127		* @return a new normal distribution
128		*/
129		public NormalDistribution createNormalDistribution(double mean, double sd) {
130	32	return new NormalDistributionImpl(mean, sd);
131		}
132
133		/**
134		* Create a new normal distribution with the mean zero and standard
135		* deviation one.
136		*
137		* @return a new normal distribution
138		*/
139		public NormalDistribution createNormalDistribution() {
140	0	return new NormalDistributionImpl();
141		}
142
143		/**
144		* Create a new Poisson distribution with poisson parameter lambda.
145		* <p>
146		* lambda must be postive; otherwise an
147		* <code>IllegalArgumentException</code> is thrown.
148		*
149		* @param lambda poisson parameter
150		* @return a new Poisson distribution
151		* @throws IllegalArgumentException if lambda &le; 0
152		*/
153		public PoissonDistribution createPoissonDistribution(double lambda) {
154	28	return new PoissonDistributionImpl(lambda);
155		}
156
157		}