1 /* 2 * Licensed to the Apache Software Foundation (ASF) under one or more 3 * contributor license agreements. See the NOTICE file distributed with 4 * this work for additional information regarding copyright ownership. 5 * The ASF licenses this file to You under the Apache License, Version 2.0 6 * (the "License"); you may not use this file except in compliance with 7 * the License. You may obtain a copy of the License at 8 * 9 * http://www.apache.org/licenses/LICENSE-2.0 10 * 11 * Unless required by applicable law or agreed to in writing, software 12 * distributed under the License is distributed on an "AS IS" BASIS, 13 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 14 * See the License for the specific language governing permissions and 15 * limitations under the License. 16 */ 17 package org.apache.commons.rng.sampling.distribution; 18 19 import org.apache.commons.rng.UniformRandomProvider; 20 21 /** 22 * Distribution sampler that uses the 23 * <a href="https://en.wikipedia.org/wiki/Inverse_transform_sampling"> 24 * inversion method</a>. 25 * 26 * It can be used to sample any distribution that provides access to its 27 * <em>inverse cumulative probabilty function</em>. 28 * 29 * <p>Example:</p> 30 * <pre><code> 31 * import org.apache.commons.math3.distribution.RealDistribution; 32 * import org.apache.commons.math3.distribution.ChiSquaredDistribution; 33 * 34 * import org.apache.commons.rng.simple.RandomSource; 35 * import org.apache.commons.rng.sampling.distribution.ContinuousSampler; 36 * import org.apache.commons.rng.sampling.distribution.InverseTransformContinuousSampler; 37 * import org.apache.commons.rng.sampling.distribution.ContinuousInverseCumulativeProbabilityFunction; 38 * 39 * // Distribution to sample. 40 * final RealDistribution dist = new ChiSquaredDistribution(9); 41 * // Create the sampler. 42 * final ContinuousSampler chiSquareSampler = 43 * new InverseTransformContinuousSampler(RandomSource.create(RandomSource.MT), 44 * new ContinuousInverseCumulativeProbabilityFunction() { 45 * public double inverseCumulativeProbability(double p) { 46 * return dist.inverseCumulativeProbability(p); 47 * } 48 * }); 49 * 50 * // Generate random deviate. 51 * double random = chiSquareSampler.sample(); 52 * </code></pre> 53 * 54 * @since 1.0 55 */ 56 public class InverseTransformContinuousSampler 57 extends SamplerBase 58 implements ContinuousSampler { 59 /** Inverse cumulative probability function. */ 60 private final ContinuousInverseCumulativeProbabilityFunction function; 61 /** Underlying source of randomness. */ 62 private final UniformRandomProvider rng; 63 64 /** 65 * @param rng Generator of uniformly distributed random numbers. 66 * @param function Inverse cumulative probability function. 67 */ 68 public InverseTransformContinuousSampler(UniformRandomProvider rng, 69 ContinuousInverseCumulativeProbabilityFunction function) { 70 super(null); 71 this.rng = rng; 72 this.function = function; 73 } 74 75 /** {@inheritDoc} */ 76 @Override 77 public double sample() { 78 return function.inverseCumulativeProbability(rng.nextDouble()); 79 } 80 81 /** {@inheritDoc} */ 82 @Override 83 public String toString() { 84 return function.toString() + " (inverse method) [" + rng.toString() + "]"; 85 } 86 }