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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 two-parameter distribution with range from 0 (exclusive) to positive infinity.
* This is mostly here because the shape of its graph is so strange; this could allow it to be useful for modeling
* especially unusual probabilities. Or for games, to really mess with attempts to figure out the program internals.
* @see Wikipedia's page on this distribution.
*/
public class LogCauchyDistribution extends Distribution {
public String getTag() {
return "LogCauchy";
}
@Override
public LogCauchyDistribution copy() {
return new LogCauchyDistribution(generator.copy(), mu, sigma);
}
private double mu;
private double sigma;
public double getMu() {
return mu;
}
public double getSigma() {
return sigma;
}
@Override
public double getParameterA() {
return mu;
}
@Override
public double getParameterB() {
return sigma;
}
/**
* Uses an {@link AceRandom}, alpha = 0.0, sigma = 1.0 .
*/
public LogCauchyDistribution() {
this(new AceRandom(), 0.0, 1.0);
}
/**
* Uses an {@link AceRandom} and the given mu and sigma.
*/
public LogCauchyDistribution(double mu, double sigma) {
this(new AceRandom(), mu, sigma);
}
/**
* Uses the given EnhancedRandom directly. Uses the given mu and sigma.
*/
public LogCauchyDistribution(EnhancedRandom generator, double mu, double sigma)
{
this.generator = generator;
if(!setParameters(mu, sigma, 0.0))
throw new IllegalArgumentException("Given mu and/or sigma are invalid.");
}
@Override
public double getMaximum() {
return Double.POSITIVE_INFINITY;
}
@Override
public double getMean() {
return Double.POSITIVE_INFINITY;
}
@Override
public double getMedian() {
return Math.exp(mu);
}
@Override
public double getMinimum() {
return 0.0;
}
@Override
public double[] getMode() {
throw new UnsupportedOperationException("Mode is undefined.");
}
@Override
public double getVariance() {
return Double.POSITIVE_INFINITY;
}
/**
* Sets all parameters and returns true if they are valid, otherwise leaves parameters unchanged and returns false.
* @param a mu; must not be NaN
* @param b sigma; should be greater than 0.0
* @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(!Double.isNaN(a) && b > 0.0){
mu = a;
sigma = b;
return true;
}
return false;
}
@Override
public double nextDouble() {
return sample(generator, mu, sigma);
}
public static double sample(EnhancedRandom generator, double mu, double sigma) {
return Math.exp(CauchyDistribution.sample(generator, mu, sigma));
}
}