rf605_profilell.C

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/// \file
/// \ingroup tutorial_roofit
/// \notebook -js
///  'LIKELIHOOD AND MINIMIZATION' RooFit tutorial macro #605
///
///  Working with the profile likelihood estimator
///
/// \macro_image
/// \macro_output
/// \macro_code
/// \author 07/2008 - Wouter Verkerke 


#include "RooRealVar.h"
#include "RooDataSet.h"
#include "RooGaussian.h"
#include "RooConstVar.h"
#include "RooAddPdf.h"
#include "RooMinimizer.h"
#include "TCanvas.h"
#include "TAxis.h"
#include "RooPlot.h"
using namespace RooFit ;


void rf605_profilell()
{
   // C r e a t e   m o d e l   a n d   d a t a s e t 
   // -----------------------------------------------

   // Observable
   RooRealVar x("x","x",-20,20) ;

   // Model (intentional strong correlations)
   RooRealVar mean("mean","mean of g1 and g2",0,-10,10) ;
   RooRealVar sigma_g1("sigma_g1","width of g1",3) ;
   RooGaussian g1("g1","g1",x,mean,sigma_g1) ;

   RooRealVar sigma_g2("sigma_g2","width of g2",4,3.0,6.0) ;
   RooGaussian g2("g2","g2",x,mean,sigma_g2) ;

   RooRealVar frac("frac","frac",0.5,0.0,1.0) ;
   RooAddPdf model("model","model",RooArgList(g1,g2),frac) ;

   // Generate 1000 events
   RooDataSet* data = model.generate(x,1000) ;
   


   // C o n s t r u c t   p l a i n   l i k e l i h o o d
   // ---------------------------------------------------

   // Construct unbinned likelihood
   RooAbsReal* nll = model.createNLL(*data,NumCPU(2)) ;

   // Minimize likelihood w.r.t all parameters before making plots
   RooMinimizer(*nll).migrad() ;

   // Plot likelihood scan frac 
   RooPlot* frame1 = frac.frame(Bins(10),Range(0.01,0.95),Title("LL and profileLL in frac")) ;
   nll->plotOn(frame1,ShiftToZero()) ;

   // Plot likelihood scan in sigma_g2
   RooPlot* frame2 = sigma_g2.frame(Bins(10),Range(3.3,5.0),Title("LL and profileLL in sigma_g2")) ;
   nll->plotOn(frame2,ShiftToZero()) ;



   // C o n s t r u c t   p r o f i l e   l i k e l i h o o d   i n   f r a c
   // -----------------------------------------------------------------------

   // The profile likelihood estimator on nll for frac will minimize nll w.r.t
   // all floating parameters except frac for each evaluation

   RooAbsReal* pll_frac = nll->createProfile(frac) ;

   // Plot the profile likelihood in frac
   pll_frac->plotOn(frame1,LineColor(kRed)) ;

   // Adjust frame maximum for visual clarity
   frame1->SetMinimum(0) ;
   frame1->SetMaximum(3) ;



   // C o n s t r u c t   p r o f i l e   l i k e l i h o o d   i n   s i g m a _ g 2 
   // -------------------------------------------------------------------------------

   // The profile likelihood estimator on nll for sigma_g2 will minimize nll
   // w.r.t all floating parameters except sigma_g2 for each evaluation
   RooAbsReal* pll_sigmag2 = nll->createProfile(sigma_g2) ;

   // Plot the profile likelihood in sigma_g2
   pll_sigmag2->plotOn(frame2,LineColor(kRed)) ;

   // Adjust frame maximum for visual clarity
   frame2->SetMinimum(0) ;
   frame2->SetMaximum(3) ;



   // Make canvas and draw RooPlots
   TCanvas *c = new TCanvas("rf605_profilell","rf605_profilell",800, 400);
   c->Divide(2);
   c->cd(1) ; gPad->SetLeftMargin(0.15) ; frame1->GetYaxis()->SetTitleOffset(1.4) ; frame1->Draw() ;
   c->cd(2) ; gPad->SetLeftMargin(0.15) ; frame2->GetYaxis()->SetTitleOffset(1.4) ; frame2->Draw() ;

   delete pll_frac ;
   delete pll_sigmag2 ;
   delete nll ;
}