RooLandau.cxx

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/*****************************************************************************
 * Project: RooFit                                                           *
 * Package: RooFitModels                                                     *
 * @(#)root/roofit:$Id$
 * Authors:                                                                  *
 *   WV, Wouter Verkerke, UC Santa Barbara, verkerke@slac.stanford.edu       *
 *   DK, David Kirkby,    UC Irvine,         dkirkby@uci.edu                 *
 *                                                                           *
 * Copyright (c) 2000-2005, Regents of the University of California          *
 *                          and Stanford University. All rights reserved.    *
 *                                                                           *
 * Redistribution and use in source and binary forms,                        *
 * with or without modification, are permitted according to the terms        *
 * listed in LICENSE (http://roofit.sourceforge.net/license.txt)             *
 *****************************************************************************/
 
/** \class RooLandau
    \ingroup Roofit
 
Landau distribution p.d.f
\image html RF_Landau.png "PDF of the Landau distribution."
**/
 
#include "RooLandau.h"
#include "RooHelpers.h"
#include "RooRandom.h"
#include "RooBatchCompute.h"
 
#include "TMath.h"
#include "Math/ProbFunc.h"
 
ClassImp(RooLandau);
 
////////////////////////////////////////////////////////////////////////////////
 
RooLandau::RooLandau(const char *name, const char *title, RooAbsReal& _x, RooAbsReal& _mean, RooAbsReal& _sigma) :
  RooAbsPdf(name,title),
  x("x","Dependent",this,_x),
  mean("mean","Mean",this,_mean),
  sigma("sigma","Width",this,_sigma)
{
  RooHelpers::checkRangeOfParameters(this, {&_sigma}, 0.0);
}
 
////////////////////////////////////////////////////////////////////////////////
 
RooLandau::RooLandau(const RooLandau& other, const char* name) :
  RooAbsPdf(other,name),
  x("x",this,other.x),
  mean("mean",this,other.mean),
  sigma("sigma",this,other.sigma)
{
}
 
////////////////////////////////////////////////////////////////////////////////
 
double RooLandau::evaluate() const
{
  return TMath::Landau(x, mean, sigma);
}
 
////////////////////////////////////////////////////////////////////////////////
/// Compute multiple values of Landau distribution.
void RooLandau::computeBatch(cudaStream_t* stream, double* output, size_t nEvents, RooFit::Detail::DataMap const& dataMap) const
{
  auto dispatch = stream ? RooBatchCompute::dispatchCUDA : RooBatchCompute::dispatchCPU;
  dispatch->compute(stream, RooBatchCompute::Landau, output, nEvents,
          {dataMap.at(x), dataMap.at(mean), dataMap.at(sigma)});
}
 
////////////////////////////////////////////////////////////////////////////////
 
Int_t RooLandau::getGenerator(const RooArgSet& directVars, RooArgSet &generateVars, bool /*staticInitOK*/) const
{
  if (matchArgs(directVars,generateVars,x)) return 1 ;
  return 0;
}
 
Int_t RooLandau::getAnalyticalIntegral(RooArgSet &allVars, RooArgSet &analVars, const char * /*rangeName*/) const
{
   if (matchArgs(allVars, analVars, x))
      return 1;
   return 0;
}
 
Double_t RooLandau::analyticalIntegral(Int_t /*code*/, const char *rangeName) const
{
   // Don't do anything with "code". It can only be "1" anyway (see
   // implementation of getAnalyticalIntegral).
 
   const double max = x.max(rangeName);
   const double min = x.min(rangeName);
 
   const double meanVal = mean;
   const double sigmaVal = sigma;
 
   using ROOT::Math::landau_cdf;
   return sigmaVal * (landau_cdf(max, sigmaVal, meanVal) - landau_cdf(min, sigmaVal, meanVal));
}
 
////////////////////////////////////////////////////////////////////////////////
 
void RooLandau::generateEvent(Int_t code)
{
  assert(1 == code); (void)code;
  double xgen ;
  while(1) {
    xgen = RooRandom::randomGenerator()->Landau(mean,sigma);
    if (xgen<x.max() && xgen>x.min()) {
      x = xgen ;
      break;
    }
  }
  return;
}