HybridCalculator.cxx

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// @(#)root/roostats:$Id$
// Author: Kyle Cranmer, Sven Kreiss   23/05/10
/*************************************************************************
 * 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.             *
 *************************************************************************/
 
/** \class RooStats::HybridCalculator
    \ingroup Roostats
 
Same purpose as HybridCalculatorOriginal, but different implementation.
 
This class implements the Hypothesis test calculation using an hybrid
(frequentist/bayesian) procedure.A frequentist sampling of the test statistic
distribution is obtained but with marginalization of the nuisance parameters.
The toys are generated by sampling the nuisance parameters according to their
prior distribution.
 
The use of the of ToyMCSampler as the TestStatSampler is assumed.
 
*/
 
#include "RooStats/HybridCalculator.h"
#include "RooStats/ToyMCSampler.h"
 
 
 
using namespace RooStats;
using std::endl;
 
////////////////////////////////////////////////////////////////////////////////
 
int HybridCalculator::CheckHook(void) const {
 
   if( fPriorNuisanceNull && (!fNullModel->GetNuisanceParameters() || fNullModel->GetNuisanceParameters()->empty()) ) {
      oocoutE(nullptr,InputArguments)  << "HybridCalculator - Nuisance PDF has been specified, but is unaware of which parameters are the nuisance parameters. Must set nuisance parameters in the Null ModelConfig." << std::endl;
      return -1; // error
   }
   if( fPriorNuisanceAlt && (!fAltModel->GetNuisanceParameters() || fAltModel->GetNuisanceParameters()->empty()) ) {
      oocoutE(nullptr,InputArguments)  << "HybridCalculator - Nuisance PDF has been specified, but is unaware of which parameters are the nuisance parameters. Must set nuisance parameters in the Alt ModelConfig" << std::endl;
      return -1; // error
   }
 
   return 0; // ok
}
 
////////////////////////////////////////////////////////////////////////////////
 
int HybridCalculator::PreNullHook(RooArgSet* /*parameterPoint*/, double obsTestStat) const {
 
 
   // ****** any TestStatSampler ********
 
   if(fPriorNuisanceNull) {
      // Setup Priors for ad hoc Hybrid
      fTestStatSampler->SetPriorNuisance(fPriorNuisanceNull);
   } else if(
      fNullModel->GetNuisanceParameters() == nullptr ||
      fNullModel->GetNuisanceParameters()->empty()
   ) {
      oocoutI(nullptr,InputArguments)
       << "HybridCalculator - No nuisance parameters specified for Null model and no prior forced. "
       << "Case is reduced to simple hypothesis testing with no uncertainty." << std::endl;
   } else {
      oocoutI(nullptr,InputArguments) << "HybridCalculator - Using uniform prior on nuisance parameters (Null model)." << std::endl;
   }
 
 
   // ***** ToyMCSampler specific *******
 
   // check whether TestStatSampler is a ToyMCSampler
   ToyMCSampler *toymcs = dynamic_cast<ToyMCSampler*>(GetTestStatSampler());
   if(toymcs) {
      oocoutI(nullptr,InputArguments) << "Using a ToyMCSampler. Now configuring for Null." << std::endl;
 
      // variable number of toys
      if(fNToysNull >= 0) toymcs->SetNToys(fNToysNull);
 
      // adaptive sampling
      if(fNToysNullTail) {
         oocoutI(nullptr,InputArguments) << "Adaptive Sampling" << std::endl;
         if(GetTestStatSampler()->GetTestStatistic()->PValueIsRightTail()) {
            toymcs->SetToysRightTail(fNToysNullTail, obsTestStat);
         }else{
            toymcs->SetToysLeftTail(fNToysNullTail, obsTestStat);
         }
      }else{
         toymcs->SetToysBothTails(0, 0, obsTestStat); // disable adaptive sampling
      }
 
      GetNullModel()->LoadSnapshot();
   }
 
   return 0;
}
 
////////////////////////////////////////////////////////////////////////////////
 
int HybridCalculator::PreAltHook(RooArgSet* /*parameterPoint*/, double obsTestStat) const {
 
   // ****** any TestStatSampler ********
 
   if(fPriorNuisanceAlt){
     // Setup Priors for ad hoc Hybrid
     fTestStatSampler->SetPriorNuisance(fPriorNuisanceAlt);
   } else if (
      fAltModel->GetNuisanceParameters()==nullptr ||
      fAltModel->GetNuisanceParameters()->empty()
   ) {
      oocoutI(nullptr,InputArguments)
       << "HybridCalculator - No nuisance parameters specified for Alt model and no prior forced. "
       << "Case is reduced to simple hypothesis testing with no uncertainty." << std::endl;
   } else {
      oocoutI(nullptr,InputArguments) << "HybridCalculator - Using uniform prior on nuisance parameters (Alt model)." << std::endl;
   }
 
 
   // ***** ToyMCSampler specific *******
 
   // check whether TestStatSampler is a ToyMCSampler
   ToyMCSampler *toymcs = dynamic_cast<ToyMCSampler*>(GetTestStatSampler());
   if(toymcs) {
      oocoutI(nullptr,InputArguments) << "Using a ToyMCSampler. Now configuring for Alt." << std::endl;
 
      // variable number of toys
      if(fNToysAlt >= 0) toymcs->SetNToys(fNToysAlt);
 
      // adaptive sampling
      if(fNToysAltTail) {
         oocoutI(nullptr,InputArguments) << "Adaptive Sampling" << std::endl;
         if(GetTestStatSampler()->GetTestStatistic()->PValueIsRightTail()) {
            toymcs->SetToysLeftTail(fNToysAltTail, obsTestStat);
         }else{
            toymcs->SetToysRightTail(fNToysAltTail, obsTestStat);
         }
      }else{
         toymcs->SetToysBothTails(0, 0, obsTestStat); // disable adaptive sampling
      }
   }
 
   return 0;
}