//////////////////////////////////////////////////////////////////////////
//
// 'LIKELIHOOD AND MINIMIZATION' RooFit tutorial macro #605
//
// Working with the profile likelihood estimator
//
//
//
// 07/2008 - Wouter Verkerke
//
/////////////////////////////////////////////////////////////////////////
#ifndef __CINT__
#include "RooGlobalFunc.h"
#endif
#include "RooRealVar.h"
#include "RooDataSet.h"
#include "RooGaussian.h"
#include "RooConstVar.h"
#include "RooAddPdf.h"
#include "RooMinuit.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
RooMinuit(*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 ;
}