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Reference Guide
rf204_extrangefit.cxx
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1 //////////////////////////////////////////////////////////////////////////
2 //
3 // 'ADDITION AND CONVOLUTION' RooFit tutorial macro #204
4 //
5 // Extended maximum likelihood fit with alternate range definition
6 // for observed number of events.
7 //
8 //
9 //
10 // 07/2008 - Wouter Verkerke
11 //
12 /////////////////////////////////////////////////////////////////////////
13 
14 #ifndef __CINT__
15 #include "RooGlobalFunc.h"
16 #endif
17 #include "RooRealVar.h"
18 #include "RooDataSet.h"
19 #include "RooGaussian.h"
20 #include "RooChebychev.h"
21 #include "RooAddPdf.h"
22 #include "RooExtendPdf.h"
23 #include "RooFitResult.h"
24 #include "TCanvas.h"
25 #include "RooPlot.h"
26 using namespace RooFit ;
27 
28 
29 class TestBasic204 : public RooFitTestUnit
30 {
31 public:
32  TestBasic204(TFile* refFile, Bool_t writeRef, Int_t verbose) : RooFitTestUnit("Extended ML fit in sub range",refFile,writeRef,verbose) {} ;
33  Bool_t testCode() {
34 
35  // S e t u p c o m p o n e n t p d f s
36  // ---------------------------------------
37 
38  // Declare observable x
39  RooRealVar x("x","x",0,10) ;
40 
41  // Create two Gaussian PDFs g1(x,mean1,sigma) anf g2(x,mean2,sigma) and their parameters
42  RooRealVar mean("mean","mean of gaussians",5) ;
43  RooRealVar sigma1("sigma1","width of gaussians",0.5) ;
44  RooRealVar sigma2("sigma2","width of gaussians",1) ;
45 
46  RooGaussian sig1("sig1","Signal component 1",x,mean,sigma1) ;
47  RooGaussian sig2("sig2","Signal component 2",x,mean,sigma2) ;
48 
49  // Build Chebychev polynomial p.d.f.
50  RooRealVar a0("a0","a0",0.5,0.,1.) ;
51  RooRealVar a1("a1","a1",-0.2,0.,1.) ;
52  RooChebychev bkg("bkg","Background",x,RooArgSet(a0,a1)) ;
53 
54  // Sum the signal components into a composite signal p.d.f.
55  RooRealVar sig1frac("sig1frac","fraction of component 1 in signal",0.8,0.,1.) ;
56  RooAddPdf sig("sig","Signal",RooArgList(sig1,sig2),sig1frac) ;
57 
58 
59  // C o n s t r u c t e x t e n d e d c o m p s wi t h r a n g e s p e c
60  // ------------------------------------------------------------------------------
61 
62  // Define signal range in which events counts are to be defined
63  x.setRange("signalRange",4,6) ;
64 
65  // Associated nsig/nbkg as expected number of events with sig/bkg _in_the_range_ "signalRange"
66  RooRealVar nsig("nsig","number of signal events in signalRange",500,0.,10000) ;
67  RooRealVar nbkg("nbkg","number of background events in signalRange",500,0,10000) ;
68  RooExtendPdf esig("esig","extended signal p.d.f",sig,nsig,"signalRange") ;
69  RooExtendPdf ebkg("ebkg","extended background p.d.f",bkg,nbkg,"signalRange") ;
70 
71 
72  // S u m e x t e n d e d c o m p o n e n t s
73  // ---------------------------------------------
74 
75  // Construct sum of two extended p.d.f. (no coefficients required)
76  RooAddPdf model("model","(g1+g2)+a",RooArgList(ebkg,esig)) ;
77 
78 
79  // S a m p l e d a t a , f i t m o d e l
80  // -------------------------------------------
81 
82  // Generate 1000 events from model so that nsig,nbkg come out to numbers <<500 in fit
83  RooDataSet *data = model.generate(x,1000) ;
84 
85 
86  // Perform unbinned extended ML fit to data
87  RooFitResult* r = model.fitTo(*data,Extended(kTRUE),Save()) ;
88 
89 
90  regResult(r,"rf204_result") ;
91 
92  delete data ;
93  return kTRUE ;
94  }
95 } ;
RooAddPdf is an efficient implementation of a sum of PDFs of the form.
Definition: RooAddPdf.h:29
int Int_t
Definition: RtypesCore.h:41
bool Bool_t
Definition: RtypesCore.h:59
RooCmdArg Extended(Bool_t flag=kTRUE)
Double_t x[n]
Definition: legend1.C:17
Plain Gaussian p.d.f.
Definition: RooGaussian.h:25
RooRealVar represents a fundamental (non-derived) real valued object.
Definition: RooRealVar.h:36
TRandom2 r(17)
bool verbose
RooDataSet is a container class to hold unbinned data.
Definition: RooDataSet.h:29
RooCmdArg Save(Bool_t flag=kTRUE)
Chebychev polynomial p.d.f.
Definition: RooChebychev.h:25
const Bool_t kTRUE
Definition: RtypesCore.h:91