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// @(#)root/mathmore:$Id$
// Authors: L. Moneta 8/2015
/**********************************************************************
* *
* Copyright (c) 2015 , ROOT MathLib Team *
* *
* *
**********************************************************************/
// Header file for random class
//
//
// Created by: Lorenzo Moneta : Tue 4 Aug 2015
//
//
#ifndef ROOT_Math_GSLRandomFunctions
#define ROOT_Math_GSLRandomFunctions
//#include <type_traits>
#include "Math/RandomFunctions.h"
#include "Math/GSLRndmEngines.h"
namespace ROOT {
namespace Math {
//___________________________________________________________________________________
/**
Specialized implementation of the Random functions based on the GSL library.
These will work onlmy with a GSLRandomEngine type
@ingroup Random
*/
template <class EngineType >
class RandomFunctions<EngineType, ROOT::Math::GSLRandomEngine> : public RandomFunctions<EngineType, DefaultEngineType> {
//class RandomFunctions<Engine, ROOT::Math::GSLRandomEngine> {
//typdef TRandomEngine DefaulEngineType;
public:
RandomFunctions() {}
RandomFunctions(EngineType & rng) : RandomFunctions<EngineType, DefaultEngineType>(rng) {}
inline EngineType & Engine() { return RandomFunctions<EngineType,DefaultEngineType>::Rng(); }
double GausZig(double mean, double sigma) {
return Engine().GaussianZig(sigma) + mean;
}
// double GausRatio(double mean, double sigma) {
// auto & r = RandomFunctions<Engine,DefaultEngineType>::Rng();
// return r.GaussianRatio(sigma) + mean;
// }
/**
Gaussian distribution. Default method (use Ziggurat)
*/
double Gaus(double mean = 0, double sigma = 1) {
return mean + Engine().GaussianZig(sigma);
}
/**
Gaussian distribution (Box-Muller method)
*/
double GausBM(double mean = 0, double sigma = 1) {
return mean + Engine().Gaussian(sigma);
}
/**
Gaussian distribution (Ratio Method)
*/
double GausR(double mean = 0, double sigma = 1) {
return mean + Engine().GaussianRatio(sigma);
}
/**
Gaussian Tail distribution
*/
double GaussianTail(double a, double sigma = 1) {
return Engine().GaussianTail(a,sigma);
}
/**
Bivariate Gaussian distribution with correlation
*/
void Gaussian2D(double sigmaX, double sigmaY, double rho, double &x, double &y) {
Engine().Gaussian2D(sigmaX, sigmaY, rho, x, y);
}
/**
Exponential distribution
*/
double Exp(double tau) {
return Engine().Exponential(tau);
}
/**
Breit Wigner distribution
*/
double BreitWigner(double mean = 0., double gamma = 1) {
return mean + Engine().Cauchy( gamma/2.0 );
}
/**
Landau distribution
*/
double Landau(double mean = 0, double sigma = 1) {
return mean + sigma*Engine().Landau();
}
/**
Gamma distribution
*/
double Gamma(double a, double b) {
return Engine().Gamma(a,b);
}
/**
Beta distribution
*/
double Beta(double a, double b) {
return Engine().Beta(a,b);
}
/**
Log Normal distribution
*/
double LogNormal(double zeta, double sigma) {
return Engine().LogNormal(zeta,sigma);
}
/**
Chi square distribution
*/
double ChiSquare(double nu) {
return Engine().ChiSquare(nu);
}
/**
F distrbution
*/
double FDist(double nu1, double nu2) {
return Engine().FDist(nu1,nu2);
}
/**
t student distribution
*/
double tDist(double nu) {
return Engine().tDist(nu);
}
/**
Rayleigh distribution
*/
double Rayleigh(double sigma) {
return Engine().Rayleigh(sigma);
}
/**
Logistic distribution
*/
double Logistic(double a) {
return Engine().Logistic(a);
}
/**
Pareto distribution
*/
double Pareto(double a, double b) {
return Engine().Pareto(a,b);
}
/**
generate random numbers in a 2D circle of radious 1
*/
void Circle(double &x, double &y, double r = 1) {
Engine().Dir2D(x,y);
x *= r;
y *= r;
}
/**
generate random numbers in a 3D sphere of radious 1
*/
void Sphere(double &x, double &y, double &z,double r = 1) {
Engine().Dir3D(x,y,z);
x *= r;
y *= r;
z *= r;
}
/**
Poisson distribution
*/
unsigned int Poisson(double mu) {
return Engine().Poisson(mu);
}
/**
Binomial distribution
*/
unsigned int Binomial(unsigned int ntot, double prob) {
return Engine().Binomial(prob,ntot);
}
/**
Negative Binomial distribution
First parameter is n, second is probability
To be consistent with Random::Binomial
*/
unsigned int NegativeBinomial(double n, double prob) {
return Engine().NegativeBinomial(prob,n);
}
/**
Multinomial distribution
*/
std::vector<unsigned int> Multinomial( unsigned int ntot, const std::vector<double> & p ) {
return Engine().Multinomial(ntot,p);
}
};
} // namespace Math
} // namespace ROOT
#endif /* ROOT_Math_GSLRandomFunctions */
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