 ROOT   Reference Guide rf702_efficiencyfit_2D.C
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1 /// \file
2 /// \ingroup tutorial_roofit
3 /// \notebook
4 /// Special pdf's: unbinned maximum likelihood fit of an efficiency eff(x) function
5 /// to a dataset D(x,cut), cut is a category encoding a selection whose efficiency as function
6 /// of x should be described by eff(x)
7 ///
8 /// \macro_image
9 /// \macro_output
10 /// \macro_code
11 ///
12 /// \date February 2018
13 /// \authors Clemens Lange, Wouter Verkerke (C++ version)
14
15 #include "RooRealVar.h"
16 #include "RooDataSet.h"
17 #include "RooGaussian.h"
18 #include "RooConstVar.h"
19 #include "RooCategory.h"
20 #include "RooEfficiency.h"
21 #include "RooPolynomial.h"
22 #include "RooProdPdf.h"
23 #include "RooFormulaVar.h"
24 #include "TCanvas.h"
25 #include "TAxis.h"
26 #include "TH1.h"
27 #include "RooPlot.h"
28 using namespace RooFit;
29
31 {
32  // C o n s t r u c t e f f i c i e n c y f u n c t i o n e ( x , y )
33  // -----------------------------------------------------------------------
34
35  // Declare variables x,mean,sigma with associated name, title, initial value and allowed range
36  RooRealVar x("x", "x", -10, 10);
37  RooRealVar y("y", "y", -10, 10);
38
39  // Efficiency function eff(x;a,b)
40  RooRealVar ax("ax", "ay", 0.6, 0, 1);
41  RooRealVar bx("bx", "by", 5);
42  RooRealVar cx("cx", "cy", -1, -10, 10);
43
44  RooRealVar ay("ay", "ay", 0.2, 0, 1);
45  RooRealVar by("by", "by", 5);
46  RooRealVar cy("cy", "cy", -1, -10, 10);
47
48  RooFormulaVar effFunc("effFunc", "((1-ax)+ax*cos((x-cx)/bx))*((1-ay)+ay*cos((y-cy)/by))",
49  RooArgList(ax, bx, cx, x, ay, by, cy, y));
50
51  // Acceptance state cut (1 or 0)
52  RooCategory cut("cut", "cutr", { {"accept", 1}, {"reject", 0} });
53
54  // C o n s t r u c t c o n d i t i o n a l e f f i c i e n c y p d f E ( c u t | x , y )
55  // ---------------------------------------------------------------------------------------------
56
57  // Construct efficiency pdf eff(cut|x)
58  RooEfficiency effPdf("effPdf", "effPdf", effFunc, cut, "accept");
59
60  // G e n e r a t e d a t a ( x , y , c u t ) f r o m a t o y m o d e l
61  // -------------------------------------------------------------------------------
62
63  // Construct global shape pdf shape(x) and product model(x,cut) = eff(cut|x)*shape(x)
64  // (These are _only_ needed to generate some toy MC here to be used later)
65  RooPolynomial shapePdfX("shapePdfX", "shapePdfX", x, RooConst(flat ? 0 : -0.095));
66  RooPolynomial shapePdfY("shapePdfY", "shapePdfY", y, RooConst(flat ? 0 : +0.095));
67  RooProdPdf shapePdf("shapePdf", "shapePdf", RooArgSet(shapePdfX, shapePdfY));
68  RooProdPdf model("model", "model", shapePdf, Conditional(effPdf, cut));
69
70  // Generate some toy data from model
71  RooDataSet *data = model.generate(RooArgSet(x, y, cut), 10000);
72
73  // F i t c o n d i t i o n a l e f f i c i e n c y p d f t o d a t a
74  // --------------------------------------------------------------------------
75
76  // Fit conditional efficiency pdf to data
77  effPdf.fitTo(*data, ConditionalObservables(RooArgSet(x, y)));
78
79  // P l o t f i t t e d , d a t a e f f i c i e n c y
80  // --------------------------------------------------------
81
82  // Make 2D histograms of all data, selected data and efficiency function
83  TH1 *hh_data_all = data->createHistogram("hh_data_all", x, Binning(8), YVar(y, Binning(8)));
84  TH1 *hh_data_sel = data->createHistogram("hh_data_sel", x, Binning(8), YVar(y, Binning(8)), Cut("cut==cut::accept"));
85  TH1 *hh_eff = effFunc.createHistogram("hh_eff", x, Binning(50), YVar(y, Binning(50)));
86
87  // Some adjustment for good visualization
88  hh_data_all->SetMinimum(0);
89  hh_data_sel->SetMinimum(0);
90  hh_eff->SetMinimum(0);
91  hh_eff->SetLineColor(kBlue);
92
93  // Draw all frames on a canvas
94  TCanvas *ca = new TCanvas("rf702_efficiency_2D", "rf702_efficiency_2D", 1200, 400);
95  ca->Divide(3);
96  ca->cd(1);
98  hh_data_all->GetZaxis()->SetTitleOffset(1.8);
99  hh_data_all->Draw("lego");
100  ca->cd(2);
102  hh_data_sel->GetZaxis()->SetTitleOffset(1.8);
103  hh_data_sel->Draw("lego");
104  ca->cd(3);
106  hh_eff->GetZaxis()->SetTitleOffset(1.8);
107  hh_eff->Draw("surf");
108
109  return;
110 }
RooFormulaVar.h
RooDataSet::createHistogram
TH2F * createHistogram(const RooAbsRealLValue &var1, const RooAbsRealLValue &var2, const char *cuts="", const char *name="hist") const
Create a TH2F histogram of the distribution of the specified variable using this dataset.
Definition: RooDataSet.cxx:1437
TH1::SetMinimum
virtual void SetMinimum(Double_t minimum=-1111)
Definition: TH1.h:399
RooArgList
RooArgList is a container object that can hold multiple RooAbsArg objects.
Definition: RooArgList.h:21
RooGaussian.h
x
Double_t x[n]
Definition: legend1.C:17
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)
TAttLine::SetLineColor
virtual void SetLineColor(Color_t lcolor)
Set the line color.
Definition: TAttLine.h:40
TCanvas.h
RooFit::YVar
RooCmdArg YVar(const RooAbsRealLValue &var, const RooCmdArg &arg=RooCmdArg::none())
Definition: RooGlobalFunc.cxx:246
RooFit::Binning
RooCmdArg Binning(const RooAbsBinning &binning)
Definition: RooGlobalFunc.cxx:83
TH1::GetZaxis
TAxis * GetZaxis()
Definition: TH1.h:322
RooDataSet.h
bool
RooPolynomial.h
RooFit::Cut
RooCmdArg Cut(const char *cutSpec)
Definition: RooGlobalFunc.cxx:81
RooFormulaVar
A RooFormulaVar is a generic implementation of a real-valued object, which takes a RooArgList of serv...
Definition: RooFormulaVar.h:30
RooProdPdf.h
RooFit
The namespace RooFit contains mostly switches that change the behaviour of functions of PDFs (or othe...
Definition: RooCFunction1Binding.h:29
TCanvas::cd
Definition: TCanvas.cxx:708
RooPolynomial
RooPolynomial implements a polynomial p.d.f of the form.
Definition: RooPolynomial.h:28
kFALSE
const Bool_t kFALSE
Definition: RtypesCore.h:92
RooPlot.h
RooEfficiency.h
RooCategory.h
y
Double_t y[n]
Definition: legend1.C:17
RooRealVar.h
RooFit::ConditionalObservables
RooCmdArg ConditionalObservables(const RooArgSet &set)
Definition: RooGlobalFunc.cxx:199
RooConstVar.h
RooFit::Conditional
RooCmdArg Conditional(const RooArgSet &pdfSet, const RooArgSet &depSet, Bool_t depsAreCond=kFALSE)
Definition: RooGlobalFunc.cxx:231
TCanvas
The Canvas class.
Definition: TCanvas.h:23
RooCategory
RooCategory is an object to represent discrete states.
Definition: RooCategory.h:27
TAxis.h
TH1
TH1 is the base class of all histogramm classes in ROOT.
Definition: TH1.h:58
RooEfficiency
RooEfficiency is a PDF helper class to fit efficiencies parameterized by a supplied function F.
Definition: RooEfficiency.h:27
kBlue
@ kBlue
Definition: Rtypes.h:66
RooDataSet
RooDataSet is a container class to hold unbinned data.
Definition: RooDataSet.h:33
make_cnn_model.model
model
Definition: make_cnn_model.py:6
TAttAxis::SetTitleOffset
virtual void SetTitleOffset(Float_t offset=1)
Set distance between the axis and the axis title.
Definition: TAttAxis.cxx:293
RooRealVar
RooRealVar represents a variable that can be changed from the outside.
Definition: RooRealVar.h:37
RooProdPdf
RooProdPdf is an efficient implementation of a product of PDFs of the form.
Definition: RooProdPdf.h:37
TH1.h
RooArgSet
RooArgSet is a container object that can hold multiple RooAbsArg objects.
Definition: RooArgSet.h:29
TH1::Draw
virtual void Draw(Option_t *option="")
Draw this histogram with options.
Definition: TH1.cxx:3050
RooFit::RooConst
RooConstVar & RooConst(Double_t val)
Definition: RooGlobalFunc.cxx:347