doc/v632/rf202__extendedmlfit_8C.html

#include "RooRealVar.h"

#include "RooDataSet.h"

#include "RooGaussian.h"

#include "RooChebychev.h"

#include "RooAddPdf.h"

#include "RooExtendPdf.h"

#include "TCanvas.h"

#include "TAxis.h"

#include "RooPlot.h"

using namespace RooFit;


void rf202_extendedmlfit()

{


   // 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, 10);


   // 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);


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

   // M E T H O D   1

   //================


   // C o n s t r u c t   e x t e n d e d   c o m p o s i t e   m o d e l

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


   // Sum the composite signal and background into an extended pdf nsig*sig+nbkg*bkg

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

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

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


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

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


   // Generate a data sample of expected number events in x from model

   // = model.expectedEvents() = nsig+nbkg

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


   // Fit model to data, extended ML term automatically included

   model.fitTo(*data, PrintLevel(-1));


   // Plot data and PDF overlaid, use expected number of events for pdf projection normalization

   // rather than observed number of events (==data->numEntries())

   RooPlot *xframe = x.frame(Title("extended ML fit example"));

   data->plotOn(xframe);

   model.plotOn(xframe, Normalization(1.0, RooAbsReal::RelativeExpected));


   // Overlay the background component of model with a dashed line

   model.plotOn(xframe, Components(bkg), LineStyle(kDashed), Normalization(1.0, RooAbsReal::RelativeExpected));


   // Overlay the background+sig2 components of model with a dotted line

   model.plotOn(xframe, Components(RooArgSet(bkg, sig2)), LineStyle(kDotted),

                Normalization(1.0, RooAbsReal::RelativeExpected));


   // Print structure of composite pdf

   model.Print("t");


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

   // M E T H O D   2

   //================


   // C o n s t r u c t   e x t e n d e d   c o m p o n e n t s   f i r s t

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


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

   RooExtendPdf esig("esig", "extended signal pdf", sig, nsig);

   RooExtendPdf ebkg("ebkg", "extended background pdf", bkg, nbkg);


   // S u m   e x t e n d e d   c o m p o n e n t s   w i t h o u t   c o e f s

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


   // Construct sum of two extended pdf (no coefficients required)

   RooAddPdf model2("model2", "(g1+g2)+a", RooArgList(ebkg, esig));


   // Draw the frame on the canvas

   new TCanvas("rf202_composite", "rf202_composite", 600, 600);

   gPad->SetLeftMargin(0.15);

   xframe->GetYaxis()->SetTitleOffset(1.4);

   xframe->Draw();

}

RooAddPdf.h

RooChebychev.h

RooDataSet.h

RooExtendPdf.h

RooGaussian.h

RooPlot.h

RooRealVar.h

kDashed
@ kDashed
Definition TAttLine.h:48

kDotted
@ kDotted
Definition TAttLine.h:48

TAxis.h

TCanvas.h

TRangeDynCast
ROOT::Detail::TRangeCast< T, true > TRangeDynCast
TRangeDynCast is an adapter class that allows the typed iteration through a TCollection.
Definition TCollection.h:358

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

gPad
#define gPad
Definition TVirtualPad.h:305

ROOT::Detail::TRangeCast
Definition TCollection.h:311

RooAbsReal::RelativeExpected
@ RelativeExpected
Definition RooAbsReal.h:276

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

RooExtendPdf
RooExtendPdf is a wrapper around an existing PDF that adds a parameteric extended likelihood term to ...
Definition RooExtendPdf.h:22

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:45

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

TCanvas
The Canvas class.
Definition TCanvas.h:23

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

rf202_extendedmlfit
Definition rf202_extendedmlfit.py:1