RooPoisson.cxx

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 /*****************************************************************************
  * Project: RooFit                                                           *
  *                                                                           *
  * Simple Poisson PDF
  * author: Kyle Cranmer <cranmer@cern.ch>
  *                                                                           *
  *****************************************************************************/
 
/** \class RooPoisson
    \ingroup Roofit
 
Poisson pdf
**/
 
#include "RooPoisson.h"
#include "RooRandom.h"
#include "RooMath.h"
#include "RooNaNPacker.h"
#include "RooBatchCompute.h"
 
#include <RooFit/Detail/MathFuncs.h>
 
#include <array>
 
 
////////////////////////////////////////////////////////////////////////////////
/// Constructor
 
RooPoisson::RooPoisson(const char *name, const char *title,
             RooAbsReal::Ref _x,
             RooAbsReal::Ref _mean,
             bool noRounding) :
  RooAbsPdf(name,title),
  x("x","x",this,_x),
  mean("mean","mean",this,_mean),
  _noRounding(noRounding)
{
}
 
////////////////////////////////////////////////////////////////////////////////
/// Copy constructor
 
 RooPoisson::RooPoisson(const RooPoisson& other, const char* name) :
   RooAbsPdf(other,name),
   x("x",this,other.x),
   mean("mean",this,other.mean),
   _noRounding(other._noRounding),
   _protectNegative(other._protectNegative)
{
}
 
////////////////////////////////////////////////////////////////////////////////
/// Implementation in terms of the TMath::Poisson() function.
 
double RooPoisson::evaluate() const
{
  double k = _noRounding ? x : floor(x);
  if(_protectNegative && mean<0) {
    RooNaNPacker np;
    np.setPayload(-mean);
    return np._payload;
  }
  return RooFit::Detail::MathFuncs::poisson(k, mean);
}
 
////////////////////////////////////////////////////////////////////////////////
/// Compute multiple values of the Poisson distribution.
void RooPoisson::doEval(RooFit::EvalContext &ctx) const
{
   std::array<double, 2> extraArgs{static_cast<double>(_protectNegative), static_cast<double>(_noRounding)};
   RooBatchCompute::compute(ctx.config(this), RooBatchCompute::Poisson, ctx.output(), {ctx.at(x), ctx.at(mean)},
                            extraArgs);
}
 
////////////////////////////////////////////////////////////////////////////////
 
Int_t RooPoisson::getAnalyticalIntegral(RooArgSet& allVars, RooArgSet& analVars, const char* /*rangeName*/) const
{
  if (matchArgs(allVars,analVars,x)) return 1 ;
  if (matchArgs(allVars, analVars, mean)) return 2;
  return 0 ;
}
 
////////////////////////////////////////////////////////////////////////////////
 
double RooPoisson::analyticalIntegral(Int_t code, const char* rangeName) const
{
  R__ASSERT(code == 1 || code == 2) ;
 
  RooRealProxy const &integrand = code == 1 ? x : mean;
  return RooFit::Detail::MathFuncs::poissonIntegral(
     code, mean, _noRounding ? x : std::floor(x), integrand.min(rangeName), integrand.max(rangeName), _protectNegative);
}
 
////////////////////////////////////////////////////////////////////////////////
/// Advertise internal generator in x
 
Int_t RooPoisson::getGenerator(const RooArgSet& directVars, RooArgSet &generateVars, bool /*staticInitOK*/) const
{
  if (matchArgs(directVars,generateVars,x)) return 1 ;
  return 0 ;
}
 
////////////////////////////////////////////////////////////////////////////////
/// Implement internal generator using TRandom::Poisson
 
void RooPoisson::generateEvent(Int_t code)
{
  R__ASSERT(code==1) ;
  double xgen ;
  while(true) {
    xgen = RooRandom::randomGenerator()->Poisson(mean);
    if (xgen<=x.max() && xgen>=x.min()) {
      x = xgen ;
      break;
    }
  }
  return;
}