ConfidenceBelt.cxx

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// @(#)root/roostats:$Id$
// Author: Kyle Cranmer, Lorenzo Moneta, Gregory Schott, Wouter Verkerke
/*************************************************************************
 * Copyright (C) 1995-2008, Rene Brun and Fons Rademakers.               *
 * All rights reserved.                                                  *
 *                                                                       *
 * For the licensing terms see $ROOTSYS/LICENSE.                         *
 * For the list of contributors see $ROOTSYS/README/CREDITS.             *
 *************************************************************************/
 
/*****************************************************************************
 * Project: RooStats
 * Package: RooFit/RooStats
 * @(#)root/roofit/roostats:$Id$
 * Original Author: Kyle Cranmer
 *   Kyle Cranmer, Lorenzo Moneta, Gregory Schott, Wouter Verkerke
 *
 *****************************************************************************/
 
/** \class RooStats::ConfidenceBelt
   \ingroup Roostats
 
ConfidenceBelt is a concrete implementation of the ConfInterval interface.
It implements simple general purpose interval of arbitrary dimensions and shape.
It does not assume the interval is connected.
It uses either a RooDataSet (eg. a list of parameter points in the interval) or
a RooDataHist (eg. a Histogram-like object for small regions of the parameter space) to
store the interval.
 
*/
 
#include "RooStats/ConfidenceBelt.h"
 
#include "RooDataSet.h"
#include "RooDataHist.h"
 
#include "RooStats/RooStatsUtils.h"
 
ClassImp(RooStats::ConfidenceBelt); ;
 
using namespace RooStats;
using namespace std;
 
////////////////////////////////////////////////////////////////////////////////
/// Default constructor
 
ConfidenceBelt::ConfidenceBelt() :
   TNamed(), fParameterPoints(0)
{
}
 
////////////////////////////////////////////////////////////////////////////////
/// Alternate constructor
 
ConfidenceBelt::ConfidenceBelt(const char* name) :
  TNamed(name,name), fParameterPoints(0)
{
}
 
////////////////////////////////////////////////////////////////////////////////
/// Alternate constructor
 
ConfidenceBelt::ConfidenceBelt(const char* name, const char* title) :
   TNamed(name,title), fParameterPoints(0)
{
}
 
////////////////////////////////////////////////////////////////////////////////
/// Alternate constructor
 
ConfidenceBelt::ConfidenceBelt(const char* name, RooAbsData& data) :
  TNamed(name,name), fParameterPoints((RooAbsData*)data.Clone("PointsToTestForBelt"))
{
}
 
////////////////////////////////////////////////////////////////////////////////
/// Alternate constructor
 
ConfidenceBelt::ConfidenceBelt(const char* name, const char* title, RooAbsData& data) :
   TNamed(name,title), fParameterPoints((RooAbsData*)data.Clone("PointsToTestForBelt"))
{
}
 
////////////////////////////////////////////////////////////////////////////////
/// Destructor
 
ConfidenceBelt::~ConfidenceBelt()
{
}
 
////////////////////////////////////////////////////////////////////////////////
 
Double_t ConfidenceBelt::GetAcceptanceRegionMin(RooArgSet& parameterPoint, Double_t cl, Double_t leftside) {
  if(cl>0 || leftside > 0) cout <<"using default cl, leftside for now" <<endl;
  AcceptanceRegion * region = GetAcceptanceRegion(parameterPoint, cl,leftside);
  return (region) ? region->GetLowerLimit() : TMath::QuietNaN();
}
 
////////////////////////////////////////////////////////////////////////////////
 
Double_t ConfidenceBelt::GetAcceptanceRegionMax(RooArgSet& parameterPoint, Double_t cl, Double_t leftside) {
  if(cl>0 || leftside > 0) cout <<"using default cl, leftside for now" <<endl;
  AcceptanceRegion * region = GetAcceptanceRegion(parameterPoint, cl,leftside);
  return (region) ? region->GetUpperLimit() : TMath::QuietNaN();
}
 
////////////////////////////////////////////////////////////////////////////////
 
vector<Double_t> ConfidenceBelt::ConfidenceLevels() const {
  vector<Double_t> levels;
  return levels;
}
 
////////////////////////////////////////////////////////////////////////////////
 
void ConfidenceBelt::AddAcceptanceRegion(RooArgSet& parameterPoint, Int_t dsIndex,
                Double_t lower, Double_t upper,
                Double_t cl, Double_t leftside){
  if(cl>0 || leftside > 0) cout <<"using default cl, leftside for now" <<endl;
 
  RooDataSet*  tree = dynamic_cast<RooDataSet*>(  fParameterPoints );
  RooDataHist* hist = dynamic_cast<RooDataHist*>( fParameterPoints );
 
  //  cout << "add: " << tree << " " << hist << endl;
 
  if( !this->CheckParameters(parameterPoint) )
    std::cout << "problem with parameters" << std::endl;
 
  Int_t luIndex = fSamplingSummaryLookup.GetLookupIndex(cl, leftside);
  //  cout << "lookup index = " << luIndex << endl;
  if(luIndex <0 ) {
    fSamplingSummaryLookup.Add(cl,leftside);
    luIndex = fSamplingSummaryLookup.GetLookupIndex(cl, leftside);
    cout << "lookup index = " << luIndex << endl;
  }
  AcceptanceRegion* thisRegion = new AcceptanceRegion(luIndex, lower, upper);
 
  if( hist ) {
    // need a way to get index for given point
    // Can do this by setting hist's internal parameters to desired values
    // need a better way
    //    RooStats::SetParameters(&parameterPoint, const_cast<RooArgSet*>(hist->get()));
    //    int index = hist->calcTreeIndex(); // get index
    int index = hist->getIndex(parameterPoint); // get index
    //    cout << "hist index = " << index << endl;
 
    // allocate memory if necessary.  numEntries is overkill?
    if((Int_t)fSamplingSummaries.size() <= index) {
      fSamplingSummaries.reserve( hist->numEntries() );
      fSamplingSummaries.resize( hist->numEntries() );
    }
 
    // set the region for this point (check for duplicate?)
    fSamplingSummaries.at(index) = *thisRegion;
  }
  else if( tree ){
    //    int index = tree->getIndex(parameterPoint);
    int index = dsIndex;
    //    cout << "tree index = " << index << endl;
 
    // allocate memory if necessary.  numEntries is overkill?
    if((Int_t)fSamplingSummaries.size() <= index){
      fSamplingSummaries.reserve( tree->numEntries()  );
      fSamplingSummaries.resize( tree->numEntries() );
    }
 
    // set the region for this point (check for duplicate?)
    fSamplingSummaries.at( index ) = *thisRegion;
  }
}
 
////////////////////////////////////////////////////////////////////////////////
 
void ConfidenceBelt::AddAcceptanceRegion(RooArgSet& parameterPoint, AcceptanceRegion region,
                Double_t cl, Double_t leftside){
  if(cl>0 || leftside > 0) cout <<"using default cl, leftside for now" <<endl;
 
  RooDataSet*  tree = dynamic_cast<RooDataSet*>(  fParameterPoints );
  RooDataHist* hist = dynamic_cast<RooDataHist*>( fParameterPoints );
 
  if( !this->CheckParameters(parameterPoint) )
    std::cout << "problem with parameters" << std::endl;
 
 
  if( hist ) {
    // need a way to get index for given point
    // Can do this by setting hist's internal parameters to desired values
    // need a better way
    //    RooStats::SetParameters(&parameterPoint, const_cast<RooArgSet*>(hist->get()));
    //    int index = hist->calcTreeIndex(); // get index
    int index = hist->getIndex(parameterPoint); // get index
 
    // allocate memory if necessary.  numEntries is overkill?
    if((Int_t)fSamplingSummaries.size() < index) fSamplingSummaries.reserve( hist->numEntries() );
 
    // set the region for this point (check for duplicate?)
    fSamplingSummaries.at(index) = region;
  }
  else if( tree ){
    tree->add( parameterPoint ); // assume it's unique for now
    int index = tree->numEntries() - 1; //check that last point added has index nEntries -1
    // allocate memory if necessary.  numEntries is overkill?
    if((Int_t)fSamplingSummaries.size() < index) fSamplingSummaries.reserve( tree->numEntries()  );
 
    // set the region for this point (check for duplicate?)
    fSamplingSummaries.at( index ) = region;
  }
}
 
////////////////////////////////////////////////////////////////////////////////
/// Method to determine if a parameter point is in the interval
 
AcceptanceRegion* ConfidenceBelt::GetAcceptanceRegion(RooArgSet &parameterPoint, Double_t cl, Double_t leftside)
{
  if(cl>0 || leftside > 0) cout <<"using default cl, leftside for now" <<endl;
 
  RooDataSet*  tree = dynamic_cast<RooDataSet*>(  fParameterPoints );
  RooDataHist* hist = dynamic_cast<RooDataHist*>( fParameterPoints );
 
  if( !this->CheckParameters(parameterPoint) ){
    std::cout << "problem with parameters" << std::endl;
    return 0;
  }
 
  if( hist ) {
    // need a way to get index for given point
    // Can do this by setting hist's internal parameters to desired values
    // need a better way
    //    RooStats::SetParameters(&parameterPoint, const_cast<RooArgSet*>(hist->get()));
    //    Int_t index = hist->calcTreeIndex(); // get index
    int index = hist->getIndex(parameterPoint); // get index
    if (index >= (int)fSamplingSummaries.size())
      throw std::runtime_error("ConfidenceBelt::GetAcceptanceRegion: Sampling summaries are not filled yet. Switch on NeymanConstruction::CreateConfBelt() or FeldmanCousins::CreateConfBelt().");
 
    return &(fSamplingSummaries[index].GetAcceptanceRegion());
  }
  else if( tree ){
    // need a way to get index for given point
    //    RooStats::SetParameters(&parameterPoint, tree->get()); // set tree's parameters to desired values
    Int_t index = 0; //need something like tree->calcTreeIndex();
    const RooArgSet* thisPoint = 0;
    for(index=0; index<tree->numEntries(); ++index){
      thisPoint = tree->get(index);
      bool samePoint = true;
      TIter it = parameterPoint.createIterator();
      RooRealVar *myarg;
      while ( samePoint && (myarg = (RooRealVar *)it.Next())) {
   if(myarg->getVal() != thisPoint->getRealValue(myarg->GetName()))
     samePoint = false;
      }
      if(samePoint)
   break;
    }
 
    if (index >= (int)fSamplingSummaries.size())
      throw std::runtime_error("ConfidenceBelt::GetAcceptanceRegion: Sampling summaries are not filled yet. Switch on NeymanConstruction::CreateConfBelt() or FeldmanCousins::CreateConfBelt().");
 
    return &(fSamplingSummaries[index].GetAcceptanceRegion());
  }
  else {
      std::cout << "dataset is not initialized properly" << std::endl;
  }
 
  return 0;
 
}
 
////////////////////////////////////////////////////////////////////////////////
/// returns list of parameters
 
RooArgSet* ConfidenceBelt::GetParameters() const
{
   return new RooArgSet(*(fParameterPoints->get()));
}
 
////////////////////////////////////////////////////////////////////////////////
 
Bool_t ConfidenceBelt::CheckParameters(RooArgSet &parameterPoint) const
{
   if (parameterPoint.getSize() != fParameterPoints->get()->getSize() ) {
      std::cout << "size is wrong, parameters don't match" << std::endl;
      return false;
   }
   if ( ! parameterPoint.equals( *(fParameterPoints->get() ) ) ) {
      std::cout << "size is ok, but parameters don't match" << std::endl;
      return false;
   }
   return true;
}