RooStatsUtils.h

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// @(#)root/roostats:$Id$
// Author: Kyle Cranmer   28/07/2008
 
/*************************************************************************
 * 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_RooStatsUtils
#define ROOSTATS_RooStatsUtils
 
#include "TMath.h"
 
#include "TTree.h"
 
#include "Math/DistFuncMathCore.h"
 
#include "RooArgSet.h"
#include "RooRealVar.h"
#include "RooAbsCollection.h"
#include "RooStats/ModelConfig.h"
#include "RooProdPdf.h"
#include "RooDataSet.h"
#include "RooAbsCategoryLValue.h"
 
 
/** \namespace RooStats
    \ingroup Roostats
 
Namespace for the RooStats classes
 
All the classes of the %RooStats package are in the RooStats namespace.
In addition the namespace contain a set of utility functions.
 
*/
 
namespace RooStats {
   struct RooStatsConfig {
      bool useLikelihoodOffset{false}; /// Offset the likelihood by passing RooFit::Offset to fitTo().
      bool useEvalErrorWall{true};     /// Use the error wall RooFit::EvalErrorWall to drive the fitter away from disallowed parameter values.
   };
 
   /// Retrieve the config object which can be used to set flags for things like offsetting the likelihood
   /// or using the error wall for the minimiser.
   RooStatsConfig& GetGlobalRooStatsConfig();
 
   /// returns one-sided significance corresponding to a p-value
   inline Double_t PValueToSignificance(Double_t pvalue){
      return ::ROOT::Math::normal_quantile_c(pvalue,1);
   }
 
   /// returns p-value corresponding to a 1-sided significance
   inline Double_t SignificanceToPValue(Double_t Z){
      return ::ROOT::Math::normal_cdf_c(Z);
   }
 
   /// Compute the Asimov Median significance for a Poisson process
   /// with s = expected number of signal events, b = expected numner of background events
   /// and optionally sigma_b = expected uncertainty of backgorund events   
   Double_t AsimovSignificance(Double_t s, Double_t b, Double_t sigma_b = 0.0 ); 
 
   inline void SetParameters(const RooArgSet* desiredVals, RooArgSet* paramsToChange){
      paramsToChange->assign(*desiredVals) ;
   }
 
   inline void RemoveConstantParameters(RooArgSet* set){
      RooArgSet constSet;
      RooLinkedListIter it = set->iterator();
      RooRealVar *myarg;
      while ((myarg = (RooRealVar *)it.Next())) {
         if(myarg->isConstant()) constSet.add(*myarg);
      }
      set->remove(constSet);
   }
 
   inline void RemoveConstantParameters(RooArgList& set){
      RooArgSet constSet;
      RooLinkedListIter it = set.iterator();
      RooRealVar *myarg;
      while ((myarg = (RooRealVar *)it.Next())) {
         if(myarg->isConstant()) constSet.add(*myarg);
      }
      set.remove(constSet);
   }
 
   inline bool SetAllConstant(const RooAbsCollection &coll, bool constant = true) {
      // utility function to set all variable constant in a collection
      // (from G. Petrucciani)
      bool changed = false;
      RooLinkedListIter iter = coll.iterator();
      for (RooAbsArg *a = (RooAbsArg *) iter.Next(); a != 0; a = (RooAbsArg *) iter.Next()) {
         RooRealVar *v = dynamic_cast<RooRealVar *>(a);
         if (v && (v->isConstant() != constant)) {
            changed = true;
            v->setConstant(constant);
         }
      }
      return changed;
   }
 
 
   // assuming all values in set are RooRealVars, randomize their values
   inline void RandomizeCollection(RooAbsCollection& set,
                                   Bool_t randomizeConstants = kTRUE)
   {
      RooLinkedListIter it = set.iterator();
      RooRealVar* var;
 
      // repeat loop to avoid calling isConstant for nothing
      if (randomizeConstants) {
         while ((var = (RooRealVar*)it.Next()) != NULL)
            var->randomize();
      }
      else {
         // exclude constants variables
         while ((var = (RooRealVar*)it.Next()) != NULL)
            if (!var->isConstant() )
               var->randomize();
      }
 
 
   }
 
   void FactorizePdf(const RooArgSet &observables, RooAbsPdf &pdf, RooArgList &obsTerms, RooArgList &constraints);
 
   void FactorizePdf(RooStats::ModelConfig &model, RooAbsPdf &pdf, RooArgList &obsTerms, RooArgList &constraints);
 
   // extract constraint terms from pdf
   RooAbsPdf * MakeNuisancePdf(RooAbsPdf &pdf, const RooArgSet &observables, const char *name);
   RooAbsPdf * MakeNuisancePdf(const RooStats::ModelConfig &model, const char *name);
   // remove constraints from pdf and return the unconstrained pdf
   RooAbsPdf * MakeUnconstrainedPdf(RooAbsPdf &pdf, const RooArgSet &observables, const char *name = NULL);
   RooAbsPdf * MakeUnconstrainedPdf(const RooStats::ModelConfig &model, const char *name = NULL);
 
   // Create a TTree with the given name and description. All RooRealVars in the RooDataSet are represented as branches that contain values of type Double_t.
   TTree* GetAsTTree(TString name, TString desc, const RooDataSet& data);
 
   // useful function to print in one line the content of a set with their values
   void PrintListContent(const RooArgList & l, std::ostream & os = std::cout);
 
   // function to set a global flag in RooStats to use NLL offset when performing nll computations
   // Note that not all ROoStats tools implement this capabilities
   void UseNLLOffset(bool on);
 
   // function returning if the flag to check if the flag to use  NLLOffset is set
   bool IsNLLOffset();
 
   // function that clones a workspace, copying all needed components and discarding all others
   RooWorkspace* MakeCleanWorkspace(RooWorkspace *oldWS, const char *newName, bool copySnapshots,
                                    const char *mcname, const char *newmcname);
 
}
 
 
#endif