BayesianFlatPrior Class Reference

#include <BayesianFlatPrior.h>

Inheritance diagram for BayesianFlatPrior:

Public Member Functions
	BayesianFlatPrior ()
virtual const std::string &	name () const
virtual bool	run (RooWorkspace *w, RooStats::ModelConfig *mc_s, RooStats::ModelConfig *mc_b, RooAbsData &data, double &limit, double &limitErr, const double *hint)
Public Member Functions inherited from LimitAlgo
virtual void	applyDefaultOptions ()
virtual void	applyOptions (const boost::program_options::variables_map &vm)
	LimitAlgo ()
	LimitAlgo (const char *desc)
const boost::program_options::options_description &	options () const
virtual void	setNToys (const int)
virtual void	setToyNumber (const int)

Static Private Attributes
static int	maxDim_ = 4

Additional Inherited Members
Protected Attributes inherited from LimitAlgo
boost::program_options::options_description	options_

Detailed Description

abstract interface for physics objects

Author

Luca Lista (INFN), from initial implementation by Giovanni Petrucciani (UCSD)

Definition at line 13 of file BayesianFlatPrior.h.

Constructor & Destructor Documentation

BayesianFlatPrior::BayesianFlatPrior

(

)

Definition at line 21 of file BayesianFlatPrior.cc.

References maxDim_, and LimitAlgo::options_.

                                     :
    LimitAlgo("BayesianSimple specific options")
{
    options_.add_options()
        ("maxDim", boost::program_options::value<int>(&maxDim_)->default_value(maxDim_), "Maximum number of dimensions to try doing the integration")
        ;
}

Member Function Documentation

virtual const std::string& BayesianFlatPrior::name ( void  ) const

inlinevirtual

Implements LimitAlgo.

Definition at line 17 of file BayesianFlatPrior.h.

Referenced by BeautifulSoup.Tag::_invert().

                                         {
    static const std::string name("BayesianSimple");
    return name;
  }

bool BayesianFlatPrior::run ( RooWorkspace *  w, RooStats::ModelConfig *  mc_s, RooStats::ModelConfig *  mc_b, RooAbsData &  data, double &  limit, double &  limitErr, const double *  hint  )

virtual

Implements LimitAlgo.

Definition at line 29 of file BayesianFlatPrior.cc.

References alignmentValidation::c1, dtNoiseDBValidation_cfg::cerr, cl, gather_cfg::cout, maxDim_, alignCSCRings::r, and withSystematics.

                                                                                                                                                                        {
  RooArgSet  poi(*mc_s->GetParametersOfInterest());

  int dim = poi.getSize();
  if (withSystematics) dim += mc_s->GetNuisanceParameters()->getSize();
  if (dim >= maxDim_) {
    std::cerr << "ERROR: Your model has more parameters than the maximum allowed in the BayesianSimple method. \n" << 
                 "             N(params) = " << dim << ", maxDim = " << maxDim_ << "\n" <<
                 "       Please use MarkovChainMC or BayesianToyMC method to compute Bayesian limits instead of BayesianSimple.\n" <<
                 "       If you really want to run BayesianSimple, change the value of the 'maxDim' option, \n" 
                 "       but note that it's really not supposed to work for N(params) above 5 or so " << std::endl;
    throw std::logic_error("Too many parameters for BayesianSimple method. Use MarkovChainMC or BayesianToyMC method to compute Bayesian limits instead.");
  }

  RooRealVar *r = dynamic_cast<RooRealVar *>(poi.first());
  double rMax = r->getMax();
  std::auto_ptr<RooStats::ModelConfig> mc_noNuis(0);
  if (!withSystematics && mc_s->GetNuisanceParameters() != 0) {
    mc_noNuis.reset(new RooStats::ModelConfig(w));
    mc_noNuis->SetPdf(*mc_s->GetPdf());
    mc_noNuis->SetObservables(*mc_s->GetObservables());
    mc_noNuis->SetParametersOfInterest(*mc_s->GetParametersOfInterest());
    mc_noNuis->SetPriorPdf(*mc_s->GetPriorPdf());
    mc_s = mc_noNuis.get();
  }
  for (;;) {
    BayesianCalculator bcalc(data, *mc_s);
    bcalc.SetLeftSideTailFraction(0);
    bcalc.SetConfidenceLevel(cl); 
    std::auto_ptr<SimpleInterval> bcInterval(bcalc.GetInterval());
    if (bcInterval.get() == 0) return false;
    limit = bcInterval->UpperLimit();
    if (limit >= 0.5*r->getMax()) { 
      std::cout << "Limit " << r->GetName() << " < " << limit << "; " << r->GetName() << " max < " << r->getMax() << std::endl;
      if (r->getMax()/rMax > 20) return false;
      r->setMax(r->getMax()*2); 
      continue;
    }
    if (verbose > -1) {
        std::cout << "\n -- BayesianSimple -- " << "\n";
        std::cout << "Limit: " << r->GetName() << " < " << limit << " @ " << cl * 100 << "% CL" << std::endl;
    }
    if (verbose > 200) {
      // FIXME!!!!!
      TCanvas c1("c1", "c1");
      std::auto_ptr<RooPlot> bcPlot(bcalc.GetPosteriorPlot(true, 0.1)); 
      bcPlot->Draw(); 
      c1.Print("plots/bc_plot.png");
    }
    break;
  }
  return true;
}

Member Data Documentation

int BayesianFlatPrior::maxDim_ = 4

staticprivate

Definition at line 22 of file BayesianFlatPrior.h.

Referenced by BayesianFlatPrior(), and run().