#include <ToyMCSamplerOpt.h>

Public Member Functions
virtual RooAbsData *	GenerateToyData (RooArgSet &, double &weight) const
void	setGlobalObsPdf (RooAbsPdf *pdf)
virtual void	SetPdf (RooAbsPdf &pdf)
	ToyMCSamplerOpt (const RooStats::ToyMCSampler &base)
	ToyMCSamplerOpt (RooStats::TestStatistic &ts, Int_t ntoys, RooAbsPdf *globalObsPdf=0, bool generateNuisances=false)
	ToyMCSamplerOpt (const ToyMCSamplerOpt &other)
	~ToyMCSamplerOpt ()
Private Member Functions
RooAbsData *	Generate (RooAbsPdf &pdf, RooArgSet &observables, const RooDataSet *protoData=NULL, int forceEvents=0) const
Private Attributes
std::map< RooAbsPdf , toymcoptutils::SimPdfGenInfo >	genCache_
int	globalObsIndex_
RooAbsPdf *	globalObsPdf_
RooDataSet *	globalObsValues_
int	nuisIndex_
RooDataSet *	nuisValues_
RooRealVar *	weightVar_

Detailed Description

Definition at line 53 of file ToyMCSamplerOpt.h.

Constructor & Destructor Documentation

ToyMCSamplerOpt::ToyMCSamplerOpt	(	RooStats::TestStatistic &	ts,
		Int_t	ntoys,
		RooAbsPdf *	globalObsPdf = `0`,
		bool	generateNuisances = `false`
	)

Definition at line 17 of file ToyMCSamplerOpt.cc.

                                                                                                                        :
    ToyMCSampler(ts, ntoys),
    globalObsPdf_(globalObsPdf),
    globalObsValues_(0), globalObsIndex_(-1),
    nuisValues_(0), nuisIndex_(-1),
    weightVar_(0)
{
    if (!generateNuisances) fPriorNuisance = 0; // set things straight from the beginning
}

ToyMCSamplerOpt::ToyMCSamplerOpt ( const RooStats::ToyMCSampler & base )

Definition at line 28 of file ToyMCSamplerOpt.cc.

                                                                 :
    ToyMCSampler(base),
    globalObsPdf_(0),
    globalObsValues_(0), globalObsIndex_(-1),
    weightVar_(0)
{
}

ToyMCSamplerOpt::ToyMCSamplerOpt ( const ToyMCSamplerOpt & other )

Definition at line 36 of file ToyMCSamplerOpt.cc.

                                                             :
    ToyMCSampler(other),
    globalObsPdf_(0),
    globalObsValues_(0), globalObsIndex_(-1),
    weightVar_(0)
{
}

ToyMCSamplerOpt::~ToyMCSamplerOpt ( )

Definition at line 44 of file ToyMCSamplerOpt.cc.

References genCache_, globalObsValues_, and weightVar_.

{
    delete weightVar_;
    for (std::map<RooAbsPdf *, toymcoptutils::SimPdfGenInfo *>::iterator it = genCache_.begin(), ed = genCache_.end(); it != ed; ++it) {
        delete it->second;
    }
    genCache_.clear();
    delete _allVars; _allVars = 0;
    delete globalObsValues_;
}

Member Function Documentation

RooAbsData * ToyMCSamplerOpt::Generate	(	RooAbsPdf &	pdf,
		RooArgSet &	observables,
		const RooDataSet *	protoData = `NULL`,
		int	forceEvents = `0`
	)		const `[private]`

Definition at line 501 of file ToyMCSamplerOpt.cc.

References patZpeak::events, toymcoptutils::SimPdfGenInfo::generate(), info, run_regression::ret, toymcoptutils::SimPdfGenInfo::setCacheTemplates(), and toymcoptutils::SimPdfGenInfo::setCopyData().

{
   if(fProtoData) {
      protoData = fProtoData;
      forceEvents = protoData->numEntries();
   }
   int events = forceEvents;
   if (events == 0) events = fNEvents;
   if (events != 0) {
      assert(events == 1);
      assert(protoData == 0);
      RooAbsData *ret = pdf.generate(observables, events);
      return ret;
   }
   toymcoptutils::SimPdfGenInfo *& info = genCache_[&pdf];
   if (info == 0) { 
       info = new toymcoptutils::SimPdfGenInfo(pdf, observables, fGenerateBinned, protoData, forceEvents);
       info->setCopyData(false);
       if (!fPriorNuisance) info->setCacheTemplates(true);
   }
   return info->generate(weightVar_, protoData, forceEvents);
}

RooAbsData * ToyMCSamplerOpt::GenerateToyData	(	RooArgSet &	,
		double &	weight
	)		const `[virtual]`

Definition at line 419 of file ToyMCSamplerOpt.cc.

References AlCaHLTBitMon_QueryRunRegistry::data, relval_generation_module::generate(), NULL, and makeHLTPrescaleTable::values.

                                                                               {
   weight = 1;
   // This method generates a toy data set for the given parameter point taking
   // global observables into account.

   if (fObservables == NULL) { 
      ooccoutE((TObject*)NULL,InputArguments) << "Observables not set." << endl; 
      return 0; 
   }

   // generate nuisances
   RooArgSet saveNuis;
   if(fPriorNuisance && fNuisancePars && fNuisancePars->getSize() > 0) {
        if (nuisValues_ == 0 || nuisIndex_ == nuisValues_->numEntries()) {
            delete nuisValues_;
            nuisValues_ = fPriorNuisance->generate(*fNuisancePars, fNToys);
            nuisIndex_  = 0;
        }
        fNuisancePars->snapshot(saveNuis);
        const RooArgSet *values = nuisValues_->get(nuisIndex_++);
        RooArgSet pars(*fNuisancePars); pars = *values;
   }

   RooArgSet observables(*fObservables);
   if(fGlobalObservables  &&  fGlobalObservables->getSize()) {
      observables.remove(*fGlobalObservables);

      // generate one set of global observables and assign it
      assert(globalObsPdf_);
      if (globalObsValues_ == 0 || globalObsIndex_ == globalObsValues_->numEntries()) {
          delete globalObsValues_;
          globalObsValues_ = (globalObsPdf_ ? globalObsPdf_ : fPdf)->generate(*fGlobalObservables, fNToys);
          globalObsIndex_  = 0;
      }
      const RooArgSet *values = globalObsValues_->get(globalObsIndex_++);
      if (!_allVars) _allVars = fPdf->getObservables(*fGlobalObservables);
      *_allVars = *values;
   }

   RooAbsData* data = NULL;

   if(!fImportanceDensity) {
      // no Importance Sampling
      data = Generate(*fPdf, observables);
   }else{
      throw std::runtime_error("No importance sampling yet");
      // Importance Sampling
      RooArgSet* allVars = fPdf->getVariables();
      RooArgSet* allVars2 = fImportanceDensity->getVariables();
      allVars->add(*allVars2);
      const RooArgSet* saveVars = (const RooArgSet*)allVars->snapshot();

      // the number of events generated is either the given fNEvents or
      // in case this is not given, the expected number of events of
      // the pdf with a Poisson fluctuation
      int forceEvents = 0;
      if(fNEvents == 0) {
         forceEvents = (int)fPdf->expectedEvents(observables);
         forceEvents = RooRandom::randomGenerator()->Poisson(forceEvents);
      }

      // need to be careful here not to overwrite the current state of the
      // nuisance parameters, ie they must not be part of the snapshot
      if(fImportanceSnapshot) *allVars = *fImportanceSnapshot;

      // generate with the parameters configured in this class
      //   NULL => no protoData
      //   overwriteEvents => replaces fNEvents it would usually take
      data = Generate(*fImportanceDensity, observables, NULL, forceEvents);

      *allVars = *saveVars;
      delete allVars;
      delete allVars2;
      delete saveVars;
   }

   if (saveNuis.getSize()) { RooArgSet pars(*fNuisancePars); pars = saveNuis; }
   return data;
}

void ToyMCSamplerOpt::setGlobalObsPdf ( RooAbsPdf * pdf ) [inline]

Definition at line 60 of file ToyMCSamplerOpt.h.

References globalObsPdf_.

{ globalObsPdf_ = pdf; }

void ToyMCSamplerOpt::SetPdf ( RooAbsPdf & pdf ) [virtual]

Definition at line 411 of file ToyMCSamplerOpt.cc.

{
    ToyMCSampler::SetPdf(pdf);
    delete _allVars; _allVars = 0; 
    delete globalObsValues_; globalObsValues_ = 0; globalObsIndex_ = -1;
    delete nuisValues_; nuisValues_ = 0; nuisIndex_ = -1;
}