com.github.tommyettinger.random.distribution.RayleighDistribution Maven / Gradle / Ivy
Go to download
Show more of this group Show more artifacts with this name
Show all versions of juniper Show documentation
Show all versions of juniper Show documentation
Serializable pseudo-random number generators and distributions.
/*
* Copyright (c) 2023 See AUTHORS file.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*
*/
package com.github.tommyettinger.random.distribution;
import com.github.tommyettinger.random.EnhancedRandom;
import com.github.tommyettinger.random.AceRandom;
/**
* A one-parameter distribution with range from 0 exclusive to positive infinity.
* @see Wikipedia's page on this distribution.
*/
public class RayleighDistribution extends Distribution {
public String getTag() {
return "Rayleigh";
}
@Override
public RayleighDistribution copy() {
return new RayleighDistribution(generator.copy(), sigma);
}
private double sigma;
public double getSigma() {
return 1.0 / sigma;
}
@Override
public double getParameterA() {
return sigma;
}
/**
* Uses an {@link AceRandom}, sigma = 1.0 .
*/
public RayleighDistribution() {
this(new AceRandom(), 1);
}
/**
* Uses an {@link AceRandom} and the given sigma.
*/
public RayleighDistribution(double sigma) {
this(new AceRandom(), sigma);
}
/**
* Uses the given EnhancedRandom directly. Uses the given sigma.
*/
public RayleighDistribution(EnhancedRandom generator, double sigma)
{
this.generator = generator;
if(!setParameters(sigma, 0.0, 0.0))
throw new IllegalArgumentException("Given sigma is invalid.");
}
@Override
public double getMaximum() {
return Double.POSITIVE_INFINITY;
}
@Override
public double getMean() {
return sigma * Math.sqrt(0.5 * Math.PI);
}
@Override
public double getMedian() {
return sigma * Math.sqrt(Math.log(4));
}
@Override
public double getMinimum() {
return 0.0;
}
@Override
public double[] getMode() {
return new double[]{sigma};
}
@Override
public double getVariance() {
return sigma * sigma * (4.0 - Math.PI) * 0.5;
}
/**
* Sets all parameters and returns true if they are valid, otherwise leaves parameters unchanged and returns false.
* @param a sigma; should be greater than 0.0
* @param b ignored
* @param c ignored
* @return true if the parameters given are valid and will be used
*/
@Override
public boolean setParameters(double a, double b, double c) {
if(a > 0.0) {
sigma = a;
return true;
}
return false;
}
@Override
public double nextDouble() {
return sample(generator, sigma);
}
public static double sample(EnhancedRandom generator, double sigma) {
double n0 = generator.nextGaussian() * sigma;
double n1 = generator.nextGaussian() * sigma;
return Math.sqrt(n0 * n0 + n1 * n1);
}
}