001/* 002 * Licensed to the Apache Software Foundation (ASF) under one or more 003 * contributor license agreements. See the NOTICE file distributed with 004 * this work for additional information regarding copyright ownership. 005 * The ASF licenses this file to You under the Apache License, Version 2.0 006 * (the "License"); you may not use this file except in compliance with 007 * the License. You may obtain a copy of the License at 008 * 009 * http://www.apache.org/licenses/LICENSE-2.0 010 * 011 * Unless required by applicable law or agreed to in writing, software 012 * distributed under the License is distributed on an "AS IS" BASIS, 013 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 014 * See the License for the specific language governing permissions and 015 * limitations under the License. 016 */ 017package org.apache.commons.rng.sampling.distribution; 018 019import org.apache.commons.rng.UniformRandomProvider; 020 021/** 022 * Distribution sampler that uses the 023 * <a href="https://en.wikipedia.org/wiki/Inverse_transform_sampling"> 024 * inversion method</a>. 025 * 026 * It can be used to sample any distribution that provides access to its 027 * <em>inverse cumulative probabilty function</em>. 028 * 029 * <p>Example:</p> 030 * <pre><code> 031 * import org.apache.commons.math3.distribution.RealDistribution; 032 * import org.apache.commons.math3.distribution.ChiSquaredDistribution; 033 * 034 * import org.apache.commons.rng.simple.RandomSource; 035 * import org.apache.commons.rng.sampling.distribution.ContinuousSampler; 036 * import org.apache.commons.rng.sampling.distribution.InverseTransformContinuousSampler; 037 * import org.apache.commons.rng.sampling.distribution.ContinuousInverseCumulativeProbabilityFunction; 038 * 039 * // Distribution to sample. 040 * final RealDistribution dist = new ChiSquaredDistribution(9); 041 * // Create the sampler. 042 * final ContinuousSampler chiSquareSampler = 043 * new InverseTransformContinuousSampler(RandomSource.create(RandomSource.MT), 044 * new ContinuousInverseCumulativeProbabilityFunction() { 045 * public double inverseCumulativeProbability(double p) { 046 * return dist.inverseCumulativeProbability(p); 047 * } 048 * }); 049 * 050 * // Generate random deviate. 051 * double random = chiSquareSampler.sample(); 052 * </code></pre> 053 * 054 * @since 1.0 055 */ 056public class InverseTransformContinuousSampler 057 extends SamplerBase 058 implements ContinuousSampler { 059 /** Inverse cumulative probability function. */ 060 private final ContinuousInverseCumulativeProbabilityFunction function; 061 /** Underlying source of randomness. */ 062 private final UniformRandomProvider rng; 063 064 /** 065 * @param rng Generator of uniformly distributed random numbers. 066 * @param function Inverse cumulative probability function. 067 */ 068 public InverseTransformContinuousSampler(UniformRandomProvider rng, 069 ContinuousInverseCumulativeProbabilityFunction function) { 070 super(null); 071 this.rng = rng; 072 this.function = function; 073 } 074 075 /** {@inheritDoc} */ 076 @Override 077 public double sample() { 078 return function.inverseCumulativeProbability(rng.nextDouble()); 079 } 080 081 /** {@inheritDoc} */ 082 @Override 083 public String toString() { 084 return function.toString() + " (inverse method) [" + rng.toString() + "]"; 085 } 086}