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Reference Guide
rf501_simultaneouspdf.C
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1 /// \file
2 /// \ingroup tutorial_roofit
3 /// \notebook -js
4 /// 'ORGANIZATION AND SIMULTANEOUS FITS' RooFit tutorial macro #501
5 ///
6 /// Using simultaneous p.d.f.s to describe simultaneous fits to multiple
7 /// datasets
8 ///
9 /// \macro_image
10 /// \macro_output
11 /// \macro_code
12 /// \author 07/2008 - Wouter Verkerke
13 
14 
15 #include "RooRealVar.h"
16 #include "RooDataSet.h"
17 #include "RooGaussian.h"
18 #include "RooConstVar.h"
19 #include "RooChebychev.h"
20 #include "RooAddPdf.h"
21 #include "RooSimultaneous.h"
22 #include "RooCategory.h"
23 #include "TCanvas.h"
24 #include "TAxis.h"
25 #include "RooPlot.h"
26 using namespace RooFit ;
27 
28 
29 void rf501_simultaneouspdf()
30 {
31  // C r e a t e m o d e l f o r p h y s i c s s a m p l e
32  // -------------------------------------------------------------
33 
34  // Create observables
35  RooRealVar x("x","x",-8,8) ;
36 
37  // Construct signal pdf
38  RooRealVar mean("mean","mean",0,-8,8) ;
39  RooRealVar sigma("sigma","sigma",0.3,0.1,10) ;
40  RooGaussian gx("gx","gx",x,mean,sigma) ;
41 
42  // Construct background pdf
43  RooRealVar a0("a0","a0",-0.1,-1,1) ;
44  RooRealVar a1("a1","a1",0.004,-1,1) ;
45  RooChebychev px("px","px",x,RooArgSet(a0,a1)) ;
46 
47  // Construct composite pdf
48  RooRealVar f("f","f",0.2,0.,1.) ;
49  RooAddPdf model("model","model",RooArgList(gx,px),f) ;
50 
51 
52 
53  // C r e a t e m o d e l f o r c o n t r o l s a m p l e
54  // --------------------------------------------------------------
55 
56  // Construct signal pdf.
57  // NOTE that sigma is shared with the signal sample model
58  RooRealVar mean_ctl("mean_ctl","mean_ctl",-3,-8,8) ;
59  RooGaussian gx_ctl("gx_ctl","gx_ctl",x,mean_ctl,sigma) ;
60 
61  // Construct the background pdf
62  RooRealVar a0_ctl("a0_ctl","a0_ctl",-0.1,-1,1) ;
63  RooRealVar a1_ctl("a1_ctl","a1_ctl",0.5,-0.1,1) ;
64  RooChebychev px_ctl("px_ctl","px_ctl",x,RooArgSet(a0_ctl,a1_ctl)) ;
65 
66  // Construct the composite model
67  RooRealVar f_ctl("f_ctl","f_ctl",0.5,0.,1.) ;
68  RooAddPdf model_ctl("model_ctl","model_ctl",RooArgList(gx_ctl,px_ctl),f_ctl) ;
69 
70 
71 
72  // G e n e r a t e e v e n t s f o r b o t h s a m p l e s
73  // ---------------------------------------------------------------
74 
75  // Generate 1000 events in x and y from model
76  RooDataSet *data = model.generate(RooArgSet(x),100) ;
77  RooDataSet *data_ctl = model_ctl.generate(RooArgSet(x),2000) ;
78 
79 
80 
81  // C r e a t e i n d e x c a t e g o r y a n d j o i n s a m p l e s
82  // ---------------------------------------------------------------------------
83 
84  // Define category to distinguish physics and control samples events
85  RooCategory sample("sample","sample") ;
86  sample.defineType("physics") ;
87  sample.defineType("control") ;
88 
89  // Construct combined dataset in (x,sample)
90  RooDataSet combData("combData","combined data",x,Index(sample),Import("physics",*data),Import("control",*data_ctl)) ;
91 
92 
93 
94  // C o n s t r u c t a s i m u l t a n e o u s p d f i n ( x , s a m p l e )
95  // -----------------------------------------------------------------------------------
96 
97  // Construct a simultaneous pdf using category sample as index
98  RooSimultaneous simPdf("simPdf","simultaneous pdf",sample) ;
99 
100  // Associate model with the physics state and model_ctl with the control state
101  simPdf.addPdf(model,"physics") ;
102  simPdf.addPdf(model_ctl,"control") ;
103 
104 
105 
106  // P e r f o r m a s i m u l t a n e o u s f i t
107  // ---------------------------------------------------
108 
109  // Perform simultaneous fit of model to data and model_ctl to data_ctl
110  simPdf.fitTo(combData) ;
111 
112 
113 
114  // P l o t m o d e l s l i c e s o n d a t a s l i c e s
115  // ----------------------------------------------------------------
116 
117  // Make a frame for the physics sample
118  RooPlot* frame1 = x.frame(Bins(30),Title("Physics sample")) ;
119 
120  // Plot all data tagged as physics sample
121  combData.plotOn(frame1,Cut("sample==sample::physics")) ;
122 
123  // Plot "physics" slice of simultaneous pdf.
124  // NBL You _must_ project the sample index category with data using ProjWData
125  // as a RooSimultaneous makes no prediction on the shape in the index category
126  // and can thus not be integrated
127  simPdf.plotOn(frame1,Slice(sample,"physics"),ProjWData(sample,combData)) ;
128  simPdf.plotOn(frame1,Slice(sample,"physics"),Components("px"),ProjWData(sample,combData),LineStyle(kDashed)) ;
129 
130  // The same plot for the control sample slice
131  RooPlot* frame2 = x.frame(Bins(30),Title("Control sample")) ;
132  combData.plotOn(frame2,Cut("sample==sample::control")) ;
133  simPdf.plotOn(frame2,Slice(sample,"control"),ProjWData(sample,combData)) ;
134  simPdf.plotOn(frame2,Slice(sample,"control"),Components("px_ctl"),ProjWData(sample,combData),LineStyle(kDashed)) ;
135 
136 
137 
138  TCanvas* c = new TCanvas("rf501_simultaneouspdf","rf403_simultaneouspdf",800,400) ;
139  c->Divide(2) ;
140  c->cd(1) ; gPad->SetLeftMargin(0.15) ; frame1->GetYaxis()->SetTitleOffset(1.4) ; frame1->Draw() ;
141  c->cd(2) ; gPad->SetLeftMargin(0.15) ; frame2->GetYaxis()->SetTitleOffset(1.4) ; frame2->Draw() ;
142 
143 
144 }
virtual void SetTitleOffset(Float_t offset=1)
Set distance between the axis and the axis title Offset is a correction factor with respect to the "s...
Definition: TAttAxis.cxx:262
RooAddPdf is an efficient implementation of a sum of PDFs of the form.
Definition: RooAddPdf.h:29
TAxis * GetYaxis() const
Definition: RooPlot.cxx:1118
RooCmdArg Cut(const char *cutSpec)
TVirtualPad * cd(Int_t subpadnumber=0)
Set current canvas & pad.
Definition: TCanvas.cxx:679
RooCmdArg ProjWData(const RooAbsData &projData, Bool_t binData=kFALSE)
RooCmdArg Title(const char *name)
Double_t x[n]
Definition: legend1.C:17
RooCmdArg LineStyle(Style_t style)
Plain Gaussian p.d.f.
Definition: RooGaussian.h:25
const Double_t sigma
RooRealVar represents a fundamental (non-derived) real valued object.
Definition: RooRealVar.h:36
RooDataSet is a container class to hold unbinned data.
Definition: RooDataSet.h:29
RooCategory represents a fundamental (non-derived) discrete value object.
Definition: RooCategory.h:24
A RooPlot is a plot frame and a container for graphics objects within that frame. ...
Definition: RooPlot.h:41
RooCmdArg Import(const char *state, TH1 &histo)
The Canvas class.
Definition: TCanvas.h:31
RooCmdArg Index(RooCategory &icat)
double f(double x)
RooCmdArg Components(const RooArgSet &compSet)
virtual void Divide(Int_t nx=1, Int_t ny=1, Float_t xmargin=0.01, Float_t ymargin=0.01, Int_t color=0)
Automatic pad generation by division.
Definition: TPad.cxx:1135
RooCmdArg Bins(Int_t nbin)
#define gPad
Definition: TVirtualPad.h:284
Chebychev polynomial p.d.f.
Definition: RooChebychev.h:25
RooCmdArg Slice(const RooArgSet &sliceSet)
RooSimultaneous facilitates simultaneous fitting of multiple PDFs to subsets of a given dataset...
virtual void Draw(Option_t *options=0)
Draw this plot and all of the elements it contains.
Definition: RooPlot.cxx:559