rf701_efficiencyfit.C

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/// \file
/// \ingroup tutorial_roofit
/// \notebook -js
///  'SPECIAL PDFS' RooFit tutorial macro #701
///
///  Unbinned maximum likelihood fit of an efficiency eff(x) function to
///  a dataset D(x,cut), where cut is a category encoding a selection, of which
///  the efficiency as function of x should be described by eff(x)
///
/// \macro_image
/// \macro_output
/// \macro_code
/// \author 07/2008 - Wouter Verkerke 
 
 
#include "RooRealVar.h"
#include "RooDataSet.h"
#include "RooGaussian.h"
#include "RooConstVar.h"
#include "RooFormulaVar.h"
#include "RooProdPdf.h"
#include "RooEfficiency.h"
#include "RooPolynomial.h"
#include "RooCategory.h"
#include "TCanvas.h"
#include "TAxis.h"
#include "RooPlot.h"
using namespace RooFit ;
 
 
void rf701_efficiencyfit()
{
   // C o n s t r u c t   e f f i c i e n c y   f u n c t i o n   e ( x ) 
   // -------------------------------------------------------------------
 
   // Declare variables x,mean,sigma with associated name, title, initial value and allowed range
   RooRealVar x("x","x",-10,10) ;
 
   // Efficiency function eff(x;a,b) 
   RooRealVar a("a","a",0.4,0,1) ;
   RooRealVar b("b","b",5) ;
   RooRealVar c("c","c",-1,-10,10) ;
   RooFormulaVar effFunc("effFunc","(1-a)+a*cos((x-c)/b)",RooArgList(a,b,c,x)) ;
 
 
 
   // C o n s t r u c t   c o n d i t i o n a l    e f f i c i e n c y   p d f   E ( c u t | x ) 
   // ------------------------------------------------------------------------------------------
 
   // Acceptance state cut (1 or 0)
   RooCategory cut("cut","cutr") ;
   cut.defineType("accept",1) ;
   cut.defineType("reject",0) ;
 
   // Construct efficiency p.d.f eff(cut|x)
   RooEfficiency effPdf("effPdf","effPdf",effFunc,cut,"accept") ;
 
 
 
   // G e n e r a t e   d a t a   ( x ,   c u t )   f r o m   a   t o y   m o d e l 
   // -----------------------------------------------------------------------------
 
   // Construct global shape p.d.f shape(x) and product model(x,cut) = eff(cut|x)*shape(x) 
   // (These are _only_ needed to generate some toy MC here to be used later)
   RooPolynomial shapePdf("shapePdf","shapePdf",x,RooConst(-0.095)) ;
   RooProdPdf model("model","model",shapePdf,Conditional(effPdf,cut)) ;
 
   // Generate some toy data from model
   RooDataSet* data = model.generate(RooArgSet(x,cut),10000) ;
 
 
 
   // F i t   c o n d i t i o n a l   e f f i c i e n c y   p d f   t o   d a t a 
   // --------------------------------------------------------------------------
 
   // Fit conditional efficiency p.d.f to data
   effPdf.fitTo(*data,ConditionalObservables(x)) ;
 
 
 
   // P l o t   f i t t e d ,   d a t a   e f f i c i e n c y  
   // --------------------------------------------------------
 
   // Plot distribution of all events and accepted fraction of events on frame
   RooPlot* frame1 = x.frame(Bins(20),Title("Data (all, accepted)")) ;
   data->plotOn(frame1) ;
   data->plotOn(frame1,Cut("cut==cut::accept"),MarkerColor(kRed),LineColor(kRed)) ;
 
   // Plot accept/reject efficiency on data overlay fitted efficiency curve
   RooPlot* frame2 = x.frame(Bins(20),Title("Fitted efficiency")) ;
   data->plotOn(frame2,Efficiency(cut)) ; // needs ROOT version >= 5.21
   effFunc.plotOn(frame2,LineColor(kRed)) ;
 
 
 
   // Draw all frames on a canvas
   TCanvas* ca = new TCanvas("rf701_efficiency","rf701_efficiency",800,400) ;
   ca->Divide(2) ;
   ca->cd(1) ; gPad->SetLeftMargin(0.15) ; frame1->GetYaxis()->SetTitleOffset(1.6) ; frame1->Draw() ;
   ca->cd(2) ; gPad->SetLeftMargin(0.15) ; frame2->GetYaxis()->SetTitleOffset(1.4) ; frame2->Draw() ;
   
 
}