removed factories
git-svn-id: https://svn.apache.org/repos/asf/commons/proper/math/branches/MATH_2_0@651251 13f79535-47bb-0310-9956-ffa450edef68
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Luc Maisonobe
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/*
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* Licensed to the Apache Software Foundation (ASF) under one or more
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* contributor license agreements. See the NOTICE file distributed with
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* this work for additional information regarding copyright ownership.
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* The ASF licenses this file to You under the Apache License, Version 2.0
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* (the "License"); you may not use this file except in compliance with
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* the License. You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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package org.apache.commons.math.distribution;
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/**
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* This factory provids the means to create common statistical distributions.
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* The following distributions are supported:
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* <ul>
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* <li>Binomial</li>
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* <li>Cauchy</li>
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* <li>Chi-Squared</li>
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* <li>Exponential</li>
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* <li>F</li>
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* <li>Gamma</li>
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* <li>HyperGeometric</li>
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* <li>Poisson</li>
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* <li>Normal</li>
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* <li>Student's t</li>
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* <li>Weibull</li>
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* <li>Pascal</li>
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* </ul>
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*
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* Common usage:<pre>
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* DistributionFactory factory = DistributionFactory.newInstance();
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*
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* // create a Chi-Square distribution with 5 degrees of freedom.
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* ChiSquaredDistribution chi = factory.createChiSquareDistribution(5.0);
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* </pre>
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*
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* @version $Revision$ $Date$
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* @deprecated pluggability of distribution instances is now provided through
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* constructors and setters.
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*/
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public abstract class DistributionFactory {
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/**
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* Default constructor.
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*/
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protected DistributionFactory() {
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super();
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}
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/**
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* Create an instance of a <code>DistributionFactory</code>
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* @return a new factory.
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*/
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public static DistributionFactory newInstance() {
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return new DistributionFactoryImpl();
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}
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/**
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* Create a binomial distribution with the given number of trials and
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* probability of success.
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*
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* @param numberOfTrials the number of trials.
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* @param probabilityOfSuccess the probability of success
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* @return a new binomial distribution
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*/
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public abstract BinomialDistribution createBinomialDistribution(
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int numberOfTrials, double probabilityOfSuccess);
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/**
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* Create a Pascal distribution with the given number of successes and
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* probability of success.
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*
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* @param numberOfSuccesses the number of successes.
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* @param probabilityOfSuccess the probability of success
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* @return a new Pascal distribution
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* @since 1.2
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*/
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public PascalDistribution createPascalDistribution(
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int numberOfSuccesses, double probabilityOfSuccess) {
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return new PascalDistributionImpl(numberOfSuccesses, probabilityOfSuccess);
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}
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/**
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* Create a new cauchy distribution with the given median and scale.
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* @param median the median of the distribution
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* @param scale the scale
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* @return a new cauchy distribution
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* @since 1.1
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*/
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public CauchyDistribution createCauchyDistribution(
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double median, double scale)
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{
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return new CauchyDistributionImpl(median, scale);
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}
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/**
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* Create a new chi-square distribution with the given degrees of freedom.
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*
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* @param degreesOfFreedom degrees of freedom
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* @return a new chi-square distribution
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*/
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public abstract ChiSquaredDistribution createChiSquareDistribution(
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double degreesOfFreedom);
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/**
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* Create a new exponential distribution with the given degrees of freedom.
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*
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* @param mean mean
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* @return a new exponential distribution
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*/
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public abstract ExponentialDistribution createExponentialDistribution(
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double mean);
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/**
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* Create a new F-distribution with the given degrees of freedom.
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*
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* @param numeratorDegreesOfFreedom numerator degrees of freedom
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* @param denominatorDegreesOfFreedom denominator degrees of freedom
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* @return a new F-distribution
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*/
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public abstract FDistribution createFDistribution(
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double numeratorDegreesOfFreedom, double denominatorDegreesOfFreedom);
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/**
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* Create a new gamma distribution with the given shape and scale
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* parameters.
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*
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* @param alpha the shape parameter
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* @param beta the scale parameter
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*
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* @return a new gamma distribution
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*/
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public abstract GammaDistribution createGammaDistribution(
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double alpha, double beta);
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/**
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* Create a new t distribution with the given degrees of freedom.
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*
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* @param degreesOfFreedom degrees of freedom
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* @return a new t distribution
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*/
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public abstract TDistribution createTDistribution(double degreesOfFreedom);
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/**
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* Create a new hypergeometric distribution with the given the population
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* size, the number of successes in the population, and the sample size.
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*
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* @param populationSize the population size
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* @param numberOfSuccesses number of successes in the population
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* @param sampleSize the sample size
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* @return a new hypergeometric desitribution
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*/
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public abstract HypergeometricDistribution
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createHypergeometricDistribution(int populationSize,
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int numberOfSuccesses, int sampleSize);
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/**
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* Create a new normal distribution with the given mean and standard
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* deviation.
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*
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* @param mean the mean of the distribution
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* @param sd standard deviation
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* @return a new normal distribution
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*/
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public abstract NormalDistribution
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createNormalDistribution(double mean, double sd);
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/**
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* Create a new normal distribution with mean zero and standard
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* deviation one.
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*
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* @return a new normal distribution.
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*/
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public abstract NormalDistribution createNormalDistribution();
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/**
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* Create a new Poisson distribution with poisson parameter lambda.
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*
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* @param lambda poisson parameter
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* @return a new poisson distribution.
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*/
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public abstract PoissonDistribution
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createPoissonDistribution(double lambda);
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/**
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* Create a new Weibull distribution with the given shape and scale
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* parameters.
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*
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* @param alpha the shape parameter.
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* @param beta the scale parameter.
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* @return a new Weibull distribution.
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* @since 1.1
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*/
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public WeibullDistribution createWeibullDistribution(
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double alpha, double beta)
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{
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return new WeibullDistributionImpl(alpha, beta);
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}
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}
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@ -1,159 +0,0 @@
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/*
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* Licensed to the Apache Software Foundation (ASF) under one or more
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* contributor license agreements. See the NOTICE file distributed with
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* this work for additional information regarding copyright ownership.
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* The ASF licenses this file to You under the Apache License, Version 2.0
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* (the "License"); you may not use this file except in compliance with
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* the License. You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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package org.apache.commons.math.distribution;
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/**
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* A concrete distribution factory. This is the default factory used by
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* Commons-Math.
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*
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* @version $Revision$ $Date$
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* @deprecated pluggability of distribution instances is now provided through
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* constructors and setters.
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*/
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public class DistributionFactoryImpl extends DistributionFactory {
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/**
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* Default constructor. Package scope to prevent unwanted instantiation.
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*/
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public DistributionFactoryImpl() {
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super();
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}
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/**
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* Create a new chi-square distribution with the given degrees of freedom.
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*
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* @param degreesOfFreedom degrees of freedom
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* @return a new chi-square distribution
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*/
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public ChiSquaredDistribution createChiSquareDistribution(
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final double degreesOfFreedom) {
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return new ChiSquaredDistributionImpl(degreesOfFreedom);
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}
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/**
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* Create a new gamma distribution the given shape and scale parameters.
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*
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* @param alpha the shape parameter
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* @param beta the scale parameter
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* @return a new gamma distribution
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*/
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public GammaDistribution createGammaDistribution(
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double alpha, double beta) {
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return new GammaDistributionImpl(alpha, beta);
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}
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/**
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* Create a new t distribution with the given degrees of freedom.
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*
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* @param degreesOfFreedom degrees of freedom
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* @return a new t distribution.
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*/
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public TDistribution createTDistribution(double degreesOfFreedom) {
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return new TDistributionImpl(degreesOfFreedom);
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}
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/**
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* Create a new F-distribution with the given degrees of freedom.
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*
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* @param numeratorDegreesOfFreedom numerator degrees of freedom
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* @param denominatorDegreesOfFreedom denominator degrees of freedom
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* @return a new F-distribution
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*/
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public FDistribution createFDistribution(
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double numeratorDegreesOfFreedom,
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double denominatorDegreesOfFreedom) {
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return new FDistributionImpl(numeratorDegreesOfFreedom,
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denominatorDegreesOfFreedom);
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}
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/**
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* Create a new exponential distribution with the given degrees of freedom.
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*
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* @param mean mean
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* @return a new exponential distribution
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*/
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public ExponentialDistribution createExponentialDistribution(double mean) {
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return new ExponentialDistributionImpl(mean);
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}
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/**
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* Create a binomial distribution with the given number of trials and
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* probability of success.
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*
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* @param numberOfTrials the number of trials
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* @param probabilityOfSuccess the probability of success
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* @return a new binomial distribution
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*/
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public BinomialDistribution createBinomialDistribution(
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int numberOfTrials, double probabilityOfSuccess) {
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return new BinomialDistributionImpl(numberOfTrials,
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probabilityOfSuccess);
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}
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/**
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* Create a new hypergeometric distribution with the given the population
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* size, the number of successes in the population, and the sample size.
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*
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* @param populationSize the population size
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* @param numberOfSuccesses number of successes in the population
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* @param sampleSize the sample size
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* @return a new hypergeometric desitribution
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*/
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public HypergeometricDistribution createHypergeometricDistribution(
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int populationSize, int numberOfSuccesses, int sampleSize) {
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return new HypergeometricDistributionImpl(populationSize,
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numberOfSuccesses, sampleSize);
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}
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/**
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* Create a new normal distribution with the given mean and standard
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* deviation.
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*
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* @param mean the mean of the distribution
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* @param sd standard deviation
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* @return a new normal distribution
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*/
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public NormalDistribution createNormalDistribution(double mean, double sd) {
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return new NormalDistributionImpl(mean, sd);
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}
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/**
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* Create a new normal distribution with the mean zero and standard
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* deviation one.
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*
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* @return a new normal distribution
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*/
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public NormalDistribution createNormalDistribution() {
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return new NormalDistributionImpl();
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}
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/**
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* Create a new Poisson distribution with poisson parameter lambda.
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* <p>
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* lambda must be postive; otherwise an
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* <code>IllegalArgumentException</code> is thrown.
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*
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* @param lambda poisson parameter
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* @return a new Poisson distribution
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* @throws IllegalArgumentException if lambda ≤ 0
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*/
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public PoissonDistribution createPoissonDistribution(double lambda) {
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return new PoissonDistributionImpl(lambda);
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}
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}
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