doc/master/rf204a__extendedLikelihood_8C.html

#include "RooRealVar.h"

#include "RooDataSet.h"

#include "RooGaussian.h"

#include "RooChebychev.h"

#include "RooAddPdf.h"

#include "RooExtendPdf.h"

#include "RooFitResult.h"

#include "TCanvas.h"

#include "TAxis.h"

#include "RooPlot.h"

using namespace RooFit ;


void rf204a_extendedLikelihood()

{


   // S e t u p   c o m p o n e n t   p d f s

   // ---------------------------------------


   // Declare observable x

   RooRealVar x("x","x",0,11) ;


   // Create two Gaussian PDFs g1(x,mean1,sigma) anf g2(x,mean2,sigma) and their parameters

   RooRealVar mean("mean","mean of gaussians",5) ;

   RooRealVar sigma1("sigma1","width of gaussians",0.5) ;

   RooRealVar sigma2("sigma2","width of gaussians",1) ;


   RooGaussian sig1("sig1","Signal component 1",x,mean,sigma1) ;

   RooGaussian sig2("sig2","Signal component 2",x,mean,sigma2) ;


   // Build Chebychev polynomial pdf

   RooRealVar a0("a0","a0",0.5,0.,1.) ;

   RooRealVar a1("a1","a1",0.2,0.,1.) ;

   RooChebychev bkg("bkg","Background",x,RooArgSet(a0,a1)) ;


   // Sum the signal components into a composite signal pdf

   RooRealVar sig1frac("sig1frac","fraction of component 1 in signal",0.8,0.,1.) ;

   RooAddPdf sig("sig","Signal",RooArgList(sig1,sig2),sig1frac) ;


   // E x t e n d   t h e   p d f s

   // -----------------------------


   // Define signal range in which events counts are to be defined

   x.setRange("signalRange",4,6) ;


   // Associated nsig/nbkg as expected number of events with sig/bkg _in_the_range_ "signalRange"

   RooRealVar nsig("nsig","number of signal events in signalRange",500,0.,10000) ;

   RooRealVar nbkg("nbkg","number of background events in signalRange",500,0,10000) ;


   // Use AddPdf to extend the model. Giving as many coefficients as pdfs switches

   // on extension.

   RooAddPdf  model("model","(g1+g2)+a", RooArgList(bkg,sig), RooArgList(nbkg,nsig)) ;


   // S a m p l e   d a t a ,   f i t   m o d e l

   // -------------------------------------------


   // Generate 1000 events from model so that nsig,nbkg come out to numbers <<500 in fit

   std::unique_ptr<RooDataSet> data{model.generate(x,1000)};


   auto canv = new TCanvas("Canvas", "Canvas", 1500, 600);

   canv->Divide(3,1);


   // Fit full range

   // -------------------------------------------


   canv->cd(1);


   // Perform unbinned ML fit to data, full range


   // IMPORTANT:

   // The model needs to be copied when fitting with different ranges because

   // the interpretation of the coefficients is tied to the fit range

   // that's used in the first fit

   RooAddPdf model1(model);

   std::unique_ptr<RooFitResult> r{model1.fitTo(*data,Save(), PrintLevel(-1))};

   r->Print() ;


   RooPlot * frame = x.frame(Title("Full range fitted"));

   data->plotOn(frame);

   model1.plotOn(frame, VisualizeError(*r));

   model1.plotOn(frame);

   model1.paramOn(frame);

   frame->Draw();


   // Fit in two regions

   // -------------------------------------------


   canv->cd(2);

   x.setRange("left",  0., 4.);

   x.setRange("right", 6., 10.);


   RooAddPdf model2(model);

   std::unique_ptr<RooFitResult> r2{model2.fitTo(*data, Range("left,right"), Save(), PrintLevel(-1))};

   r2->Print();


   RooPlot * frame2 = x.frame(Title("Fit in left/right sideband"));

   data->plotOn(frame2);

   model2.plotOn(frame2, VisualizeError(*r2));

   model2.plotOn(frame2);

   model2.paramOn(frame2);

   frame2->Draw();


   // Fit in one region

   // -------------------------------------------

   // Note how restricting the region to only the left tail increases

   // the fit uncertainty


   canv->cd(3);

   x.setRange("leftToMiddle",  0., 5.);


   RooAddPdf model3(model);

   std::unique_ptr<RooFitResult> r3{model3.fitTo(*data, Range("leftToMiddle"), Save(), PrintLevel(-1))};

   r3->Print();


   RooPlot * frame3 = x.frame(Title("Fit from left to middle"));

   data->plotOn(frame3);

   model3.plotOn(frame3, VisualizeError(*r3));

   model3.plotOn(frame3);

   model3.paramOn(frame3);

   frame3->Draw();


   canv->Draw();

}

RooAddPdf.h

RooChebychev.h

RooDataSet.h

RooExtendPdf.h

RooFitResult.h

RooGaussian.h

RooPlot.h

RooRealVar.h

TAxis.h

TCanvas.h

data
Option_t Option_t TPoint TPoint const char GetTextMagnitude GetFillStyle GetLineColor GetLineWidth GetMarkerStyle GetTextAlign GetTextColor GetTextSize void data
Definition TGWin32VirtualXProxy.cxx:104

r
Option_t Option_t TPoint TPoint const char GetTextMagnitude GetFillStyle GetLineColor GetLineWidth GetMarkerStyle GetTextAlign GetTextColor GetTextSize void char Point_t Rectangle_t WindowAttributes_t Float_t r
Definition TGWin32VirtualXProxy.cxx:168

RooAddPdf
Efficient implementation of a sum of PDFs of the form.
Definition RooAddPdf.h:33

RooArgList
RooArgList is a container object that can hold multiple RooAbsArg objects.
Definition RooArgList.h:22

RooArgSet
RooArgSet is a container object that can hold multiple RooAbsArg objects.
Definition RooArgSet.h:55

RooChebychev
Chebychev polynomial p.d.f.
Definition RooChebychev.h:25

RooGaussian
Plain Gaussian p.d.f.
Definition RooGaussian.h:24

RooPlot
Plot frame and a container for graphics objects within that frame.
Definition RooPlot.h:43

RooPlot::frame
static RooPlot * frame(const RooAbsRealLValue &var, double xmin, double xmax, Int_t nBins)
Create a new frame for a given variable in x.
Definition RooPlot.cxx:237

RooPlot::Draw
void Draw(Option_t *options=nullptr) override
Draw this plot and all of the elements it contains.
Definition RooPlot.cxx:649

RooRealVar
Variable that can be changed from the outside.
Definition RooRealVar.h:37

TCanvas
The Canvas class.
Definition TCanvas.h:23

RooFit::Save
RooCmdArg Save(bool flag=true)
Definition RooGlobalFunc.cxx:566

RooFit::PrintLevel
RooCmdArg PrintLevel(Int_t code)
Definition RooGlobalFunc.cxx:574

RooFit::VisualizeError
RooCmdArg VisualizeError(const RooDataSet &paramData, double Z=1)
Definition RooGlobalFunc.cxx:225

x
Double_t x[n]
Definition legend1.C:17

RooFit
The namespace RooFit contains mostly switches that change the behaviour of functions of PDFs (or othe...
Definition JSONIO.h:26

rf204a_extendedLikelihood
Definition rf204a_extendedLikelihood.py:1

xmlio::Title
const char * Title
Definition TXMLSetup.cxx:68

Range
Ta Range(0, 0, 1, 1)