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rf707_kernelestimation.C
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1 /// \file
2 /// \ingroup tutorial_roofit
3 /// \notebook
4 ///
5 /// Special p.d.f.'s: using non-parametric (multi-dimensional) kernel estimation p.d.f.s
6 ///
7 /// \macro_image
8 /// \macro_output
9 /// \macro_code
10 ///
11 /// \date 07/2008
12 /// \author Wouter Verkerke
13 
14 #include "RooRealVar.h"
15 #include "RooDataSet.h"
16 #include "RooGaussian.h"
17 #include "RooConstVar.h"
18 #include "RooPolynomial.h"
19 #include "RooKeysPdf.h"
20 #include "RooNDKeysPdf.h"
21 #include "RooProdPdf.h"
22 #include "TCanvas.h"
23 #include "TAxis.h"
24 #include "TH1.h"
25 #include "RooPlot.h"
26 using namespace RooFit;
27 
29 {
30  // C r e a t e l o w s t a t s 1 - D d a t a s e t
31  // -------------------------------------------------------
32 
33  // Create a toy pdf for sampling
34  RooRealVar x("x", "x", 0, 20);
35  RooPolynomial p("p", "p", x, RooArgList(RooConst(0.01), RooConst(-0.01), RooConst(0.0004)));
36 
37  // Sample 500 events from p
38  RooDataSet *data1 = p.generate(x, 200);
39 
40  // C r e a t e 1 - D k e r n e l e s t i m a t i o n p d f
41  // ---------------------------------------------------------------
42 
43  // Create adaptive kernel estimation pdf. In this configuration the input data
44  // is mirrored over the boundaries to minimize edge effects in distribution
45  // that do not fall to zero towards the edges
46  RooKeysPdf kest1("kest1", "kest1", x, *data1, RooKeysPdf::MirrorBoth);
47 
48  // An adaptive kernel estimation pdf on the same data without mirroring option
49  // for comparison
50  RooKeysPdf kest2("kest2", "kest2", x, *data1, RooKeysPdf::NoMirror);
51 
52  // Adaptive kernel estimation pdf with increased bandwidth scale factor
53  // (promotes smoothness over detail preservation)
54  RooKeysPdf kest3("kest1", "kest1", x, *data1, RooKeysPdf::MirrorBoth, 2);
55 
56  // Plot kernel estimation pdfs with and without mirroring over data
57  RooPlot *frame = x.frame(Title("Adaptive kernel estimation pdf with and w/o mirroring"), Bins(20));
58  data1->plotOn(frame);
59  kest1.plotOn(frame);
60  kest2.plotOn(frame, LineStyle(kDashed), LineColor(kRed));
61 
62  // Plot kernel estimation pdfs with regular and increased bandwidth
63  RooPlot *frame2 = x.frame(Title("Adaptive kernel estimation pdf with regular, increased bandwidth"));
64  kest1.plotOn(frame2);
65  kest3.plotOn(frame2, LineColor(kMagenta));
66 
67  // C r e a t e l o w s t a t s 2 - D d a t a s e t
68  // -------------------------------------------------------
69 
70  // Construct a 2D toy pdf for sampling
71  RooRealVar y("y", "y", 0, 20);
72  RooPolynomial py("py", "py", y, RooArgList(RooConst(0.01), RooConst(0.01), RooConst(-0.0004)));
73  RooProdPdf pxy("pxy", "pxy", RooArgSet(p, py));
74  RooDataSet *data2 = pxy.generate(RooArgSet(x, y), 1000);
75 
76  // C r e a t e 2 - D k e r n e l e s t i m a t i o n p d f
77  // ---------------------------------------------------------------
78 
79  // Create 2D adaptive kernel estimation pdf with mirroring
80  RooNDKeysPdf kest4("kest4", "kest4", RooArgSet(x, y), *data2, "am");
81 
82  // Create 2D adaptive kernel estimation pdf with mirroring and double bandwidth
83  RooNDKeysPdf kest5("kest5", "kest5", RooArgSet(x, y), *data2, "am", 2);
84 
85  // Create a histogram of the data
86  TH1 *hh_data = data2->createHistogram("hh_data", x, Binning(10), YVar(y, Binning(10)));
87 
88  // Create histogram of the 2d kernel estimation pdfs
89  TH1 *hh_pdf = kest4.createHistogram("hh_pdf", x, Binning(25), YVar(y, Binning(25)));
90  TH1 *hh_pdf2 = kest5.createHistogram("hh_pdf2", x, Binning(25), YVar(y, Binning(25)));
91  hh_pdf->SetLineColor(kBlue);
92  hh_pdf2->SetLineColor(kMagenta);
93 
94  TCanvas *c = new TCanvas("rf707_kernelestimation", "rf707_kernelestimation", 800, 800);
95  c->Divide(2, 2);
96  c->cd(1);
97  gPad->SetLeftMargin(0.15);
98  frame->GetYaxis()->SetTitleOffset(1.4);
99  frame->Draw();
100  c->cd(2);
101  gPad->SetLeftMargin(0.15);
102  frame2->GetYaxis()->SetTitleOffset(1.8);
103  frame2->Draw();
104  c->cd(3);
105  gPad->SetLeftMargin(0.15);
106  hh_data->GetZaxis()->SetTitleOffset(1.4);
107  hh_data->Draw("lego");
108  c->cd(4);
109  gPad->SetLeftMargin(0.20);
110  hh_pdf->GetZaxis()->SetTitleOffset(2.4);
111  hh_pdf->Draw("surf");
112  hh_pdf2->Draw("surfsame");
113 }
c
#define c(i)
Definition: RSha256.hxx:119
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:1419
RooPlot::Draw
virtual void Draw(Option_t *options=0)
Draw this plot and all of the elements it contains.
Definition: RooPlot.cxx:691
RooFit::Bins
RooCmdArg Bins(Int_t nbin)
Definition: RooGlobalFunc.cxx:174
RooArgList
Definition: RooArgList.h:21
RooGaussian.h
x
Double_t x[n]
Definition: legend1.C:17
TCanvas.h
RooFit::YVar
RooCmdArg YVar(const RooAbsRealLValue &var, const RooCmdArg &arg=RooCmdArg::none())
Definition: RooGlobalFunc.cxx:240
RooFit::Binning
RooCmdArg Binning(const RooAbsBinning &binning)
Definition: RooGlobalFunc.cxx:82
TH1::GetZaxis
TAxis * GetZaxis()
Definition: TH1.h:319
rf707_kernelestimation
Definition: rf707_kernelestimation.py:1
RooDataSet.h
RooPolynomial.h
kMagenta
@ kMagenta
Definition: Rtypes.h:66
RooProdPdf.h
RooFit
Definition: RooCFunction1Binding.h:29
RooPolynomial
Definition: RooPolynomial.h:28
RooAbsData::plotOn
virtual RooPlot * plotOn(RooPlot *frame, const RooCmdArg &arg1=RooCmdArg::none(), const RooCmdArg &arg2=RooCmdArg::none(), const RooCmdArg &arg3=RooCmdArg::none(), const RooCmdArg &arg4=RooCmdArg::none(), const RooCmdArg &arg5=RooCmdArg::none(), const RooCmdArg &arg6=RooCmdArg::none(), const RooCmdArg &arg7=RooCmdArg::none(), const RooCmdArg &arg8=RooCmdArg::none()) const
Definition: RooAbsData.cxx:547
RooPlot.h
RooPlot::GetYaxis
TAxis * GetYaxis() const
Definition: RooPlot.cxx:1256
RooPlot
Definition: RooPlot.h:44
y
Double_t y[n]
Definition: legend1.C:17
RooRealVar.h
kRed
@ kRed
Definition: Rtypes.h:66
RooConstVar.h
RooFit::LineColor
RooCmdArg LineColor(Color_t color)
Definition: RooGlobalFunc.cxx:56
TCanvas
Definition: TCanvas.h:23
TAxis.h
TH1
Definition: TH1.h:57
RooKeysPdf.h
RooNDKeysPdf.h
kBlue
@ kBlue
Definition: Rtypes.h:66
kDashed
@ kDashed
Definition: TAttLine.h:48
gPad
#define gPad
Definition: TVirtualPad.h:287
RooDataSet
Definition: RooDataSet.h:33
RooNDKeysPdf
Definition: RooNDKeysPdf.h:48
RooFit::LineStyle
RooCmdArg LineStyle(Style_t style)
Definition: RooGlobalFunc.cxx:57
TAttAxis::SetTitleOffset
virtual void SetTitleOffset(Float_t offset=1)
Set distance between the axis and the axis title.
Definition: TAttAxis.cxx:293
RooRealVar
Definition: RooRealVar.h:35
RooProdPdf
Definition: RooProdPdf.h:33
TH1.h
RooKeysPdf::NoMirror
@ NoMirror
Definition: RooKeysPdf.h:27
RooFit::Title
RooCmdArg Title(const char *name)
Definition: RooGlobalFunc.cxx:173
RooKeysPdf
Definition: RooKeysPdf.h:25
RooKeysPdf::MirrorBoth
@ MirrorBoth
Definition: RooKeysPdf.h:27
RooArgSet
Definition: RooArgSet.h:28
TH1::Draw
virtual void Draw(Option_t *option="")
Draw this histogram with options.
Definition: TH1.cxx:2997
RooFit::RooConst
RooConstVar & RooConst(Double_t val)
Definition: RooGlobalFunc.cxx:341