All Downloads are FREE. Search and download functionalities are using the official Maven repository.

cern.jet.random.tdouble.BreitWigner Maven / Gradle / Ivy

Go to download

Parallel Colt is a multithreaded version of Colt - a library for high performance scientific computing in Java. It contains efficient algorithms for data analysis, linear algebra, multi-dimensional arrays, Fourier transforms, statistics and histogramming.

The newest version!
/*
Copyright (C) 1999 CERN - European Organization for Nuclear Research.
Permission to use, copy, modify, distribute and sell this software and its documentation for any purpose 
is hereby granted without fee, provided that the above copyright notice appear in all copies and 
that both that copyright notice and this permission notice appear in supporting documentation. 
CERN makes no representations about the suitability of this software for any purpose. 
It is provided "as is" without expressed or implied warranty.
 */
package cern.jet.random.tdouble;

import cern.jet.random.tdouble.engine.DoubleRandomEngine;

/**
 * BreitWigner (aka Lorentz) distribution; See the  math definition. A more general form of the Cauchy distribution.
 * 

* Instance methods operate on a user supplied uniform random number generator; * they are unsynchronized. *

Static methods operate on a default uniform random number generator; they * are synchronized. *

* Implementation: This is a port of RandBreitWigner used in CLHEP 1.4.0 (C++). * * @author [email protected] * @version 1.0, 09/24/99 */ public class BreitWigner extends AbstractContinousDoubleDistribution { /** * */ private static final long serialVersionUID = 1L; protected double mean; protected double gamma; protected double cut; // The uniform random number generated shared by all static methods. protected static BreitWigner shared = new BreitWigner(1.0, 0.2, 1.0, makeDefaultGenerator()); /** * Constructs a BreitWigner distribution. * * @param cut * cut==Double.NEGATIVE_INFINITY indicates "don't cut". */ public BreitWigner(double mean, double gamma, double cut, DoubleRandomEngine randomGenerator) { setRandomGenerator(randomGenerator); setState(mean, gamma, cut); } /** * Returns a random number from the distribution. */ public double nextDouble() { return nextDouble(mean, gamma, cut); } /** * Returns a random number from the distribution; bypasses the internal * state. * * @param cut * cut==Double.NEGATIVE_INFINITY indicates "don't cut". */ public double nextDouble(double mean, double gamma, double cut) { double val, rval, displ; if (gamma == 0.0) return mean; if (cut == Double.NEGATIVE_INFINITY) { // don't cut rval = 2.0 * randomGenerator.raw() - 1.0; displ = 0.5 * gamma * Math.tan(rval * (Math.PI / 2.0)); return mean + displ; } else { val = Math.atan(2.0 * cut / gamma); rval = 2.0 * randomGenerator.raw() - 1.0; displ = 0.5 * gamma * Math.tan(rval * val); return mean + displ; } } /** * Sets the mean, gamma and cut parameters. * * @param cut * cut==Double.NEGATIVE_INFINITY indicates "don't cut". */ public void setState(double mean, double gamma, double cut) { this.mean = mean; this.gamma = gamma; this.cut = cut; } /** * Returns a random number from the distribution. * * @param cut * cut==Double.NEGATIVE_INFINITY indicates "don't cut". */ public static double staticNextDouble(double mean, double gamma, double cut) { synchronized (shared) { return shared.nextDouble(mean, gamma, cut); } } /** * Returns a String representation of the receiver. */ public String toString() { return this.getClass().getName() + "(" + mean + "," + gamma + "," + cut + ")"; } /** * Sets the uniform random number generated shared by all static * methods. * * @param randomGenerator * the new uniform random number generator to be shared. */ private static void xstaticSetRandomGenerator(DoubleRandomEngine randomGenerator) { synchronized (shared) { shared.setRandomGenerator(randomGenerator); } } }





© 2015 - 2025 Weber Informatics LLC | Privacy Policy