NeymanConstruction.h

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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.             *
 *************************************************************************/
 
#ifndef ROOSTATS_NeymanConstruction
#define ROOSTATS_NeymanConstruction
 
 
#include "Rtypes.h"
 
#include "RooStats/IntervalCalculator.h"
 
#include "RooStats/TestStatSampler.h"
#include "RooStats/ModelConfig.h"
#include "RooStats/ConfidenceBelt.h"
#include "RooStats/PointSetInterval.h"
 
#include "RooAbsData.h"
#include "RooAbsPdf.h"
#include "RooArgSet.h"
 
#include <map>
 
class RooAbsData;
 
namespace RooStats {
 
   class ConfInterval;
 
   class NeymanConstruction : public IntervalCalculator{
 
   public:
 
     ///     NeymanConstruction();
     NeymanConstruction(RooAbsData& data, ModelConfig& model);
 
     ~NeymanConstruction() override;
 
      /// Main interface to get a ConfInterval (will be a PointSetInterval)
     PointSetInterval* GetInterval() const override;
 
      /// in addition to interface we also need:
      /// Set the TestStatSampler (eg. ToyMC or FFT, includes choice of TestStatistic)
      void SetTestStatSampler(TestStatSampler& sampler) {fTestStatSampler = &sampler;}
      /// fLeftSideTailFraction*fSize defines lower edge of acceptance region.
      /// Unified limits use 0, central limits use 0.5,
      /// for upper/lower limits it is 0/1 depends on sign of test statistic w.r.t. parameter
      void SetLeftSideTailFraction(double leftSideFraction = 0.) {fLeftSideFraction = leftSideFraction;}
 
      /// User-defined set of points to test
      void SetParameterPointsToTest(RooAbsData& pointsToTest) {
   fPointsToTest = &pointsToTest;
        fConfBelt = new ConfidenceBelt("ConfBelt",pointsToTest);
      }
      /// This class can make regularly spaced scans based on range stored in RooRealVars.
      /// Choose number of steps for a rastor scan (common for each dimension)
      ///      void SetNumSteps(Int_t);
      /// This class can make regularly spaced scans based on range stored in RooRealVars.
      /// Choose number of steps for a rastor scan (specific for each dimension)
      ///      void SetNumSteps(std::map<RooAbsArg, Int_t>)
 
      /// Get the size of the test (eg. rate of Type I error)
      double Size() const override {return fSize;}
 
      /// Get the Confidence level for the test
      double ConfidenceLevel()  const override {return 1.-fSize;}
 
      /// Set ModelConfig
      void SetModel(const ModelConfig &model) override {fModel = model;}
 
      /// Set the DataSet
      void SetData(RooAbsData& data) override { fData = data; }
 
      /// Set the Pdf, add to the workspace if not already there
      virtual void SetPdf(RooAbsPdf& /*pdf*/) {
        std::cout << "DEPRECATED, use ModelConfig"<<std::endl;
      }
 
      /// specify the parameters of interest in the interval
      virtual void SetParameters(const RooArgSet& /*set*/) {
        std::cout << "DEPRECATED, use ModelConfig"<<std::endl;
      }
 
      /// specify the nuisance parameters (eg. the rest of the parameters)
      virtual void SetNuisanceParameters(const RooArgSet& /*set*/) {
        std::cout << "DEPRECATED, use ModelConfig"<<std::endl;
      }
 
      /// set the size of the test (rate of Type I error) ( Eg. 0.05 for a 95% Confidence Interval)
      void SetTestSize(double size) override {fSize = size;}
      /// set the confidence level for the interval (eg. 0.95 for a 95% Confidence Interval)
      void SetConfidenceLevel(double cl) override {fSize = 1.-cl;}
 
      /// Get confidence belt. This requires that CreateConfBelt() has been called.
      ConfidenceBelt* GetConfidenceBelt() {return fCreateBelt ? fConfBelt : nullptr;}
 
      /// adaptive sampling algorithm to speed up interval calculation
      void UseAdaptiveSampling(bool flag=true){fAdaptiveSampling=flag;}
 
      /// give user ability to ask for more toys
      void AdditionalNToysFactor(double fact){fAdditionalNToysFactor = fact;}
 
      /// save the confidence belt to a file
      void SaveBeltToFile(bool flag=true){
         fSaveBeltToFile = flag;
         if(flag) fCreateBelt = true;
      }
      /// should create confidence belt
      void CreateConfBelt(bool flag=true){fCreateBelt = flag;}
 
      /// Returns instance of TestStatSampler. Use to change properties of
      /// TestStatSampler, e.g. GetTestStatSampler.SetTestSize(double size);
      TestStatSampler* GetTestStatSampler(void) { return fTestStatSampler; }
 
 
   private:
 
      double fSize;    ///< size of the test (eg. specified rate of Type I error)
      RooAbsData& fData; ///< data set
      ModelConfig &fModel;
 
      TestStatSampler* fTestStatSampler;
      RooAbsData* fPointsToTest;
      double fLeftSideFraction;
      ConfidenceBelt* fConfBelt;
      bool fAdaptiveSampling;          ///< controls use of adaptive sampling algorithm
      double fAdditionalNToysFactor; ///< give user ability to ask for more toys
      bool fSaveBeltToFile;            ///< controls use if ConfidenceBelt should be saved to a TFile
      bool fCreateBelt;                ///< controls use if ConfidenceBelt should be saved to a TFile
 
   protected:
      ClassDefOverride(NeymanConstruction,1)   ///< Interface for tools setting limits (producing confidence intervals)
   };
}
 
 
#endif