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rf309_ndimplot.C
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1/// \file
2/// \ingroup tutorial_roofit
3/// \notebook
4/// Multidimensional models: making 2/3 dimensional plots of pdfs and datasets
5///
6/// \macro_image
7/// \macro_output
8/// \macro_code
9///
10/// \date July 2008
11/// \author Wouter Verkerke
12
13#include "RooRealVar.h"
14#include "RooDataSet.h"
15#include "RooConstVar.h"
16#include "RooGaussian.h"
17#include "RooProdPdf.h"
18#include "TCanvas.h"
19#include "TAxis.h"
20#include "TH1.h"
21#include "RooPlot.h"
22using namespace RooFit;
23
24void rf309_ndimplot()
25{
26
27 // C r e a t e 2 D m o d e l a n d d a t a s e t
28 // -----------------------------------------------------
29
30 // Create observables
31 RooRealVar x("x", "x", -5, 5);
32 RooRealVar y("y", "y", -5, 5);
33
34 // Create parameters
35 RooRealVar a0("a0", "a0", -3.5, -5, 5);
36 RooRealVar a1("a1", "a1", -1.5, -1, 1);
37 RooRealVar sigma("sigma", "width of gaussian", 1.5);
38
39 // Create interpreted function f(y) = a0 - a1*sqrt(10*abs(y))
40 RooFormulaVar fy("fy", "a0-a1*sqrt(10*abs(y))", RooArgSet(y, a0, a1));
41
42 // Create gauss(x,f(y),s)
43 RooGaussian model("model", "Gaussian with shifting mean", x, fy, sigma);
44
45 // Sample dataset from gauss(x,y)
46 RooDataSet *data = model.generate(RooArgSet(x, y), 10000);
47
48 // M a k e 2 D p l o t s o f d a t a a n d m o d e l
49 // -------------------------------------------------------------
50
51 // Create and fill ROOT 2D histogram (20x20 bins) with contents of dataset
52 // TH2D* hh_data = data->createHistogram("hh_data",x,Binning(20),YVar(y,Binning(20))) ;
53 TH1 *hh_data = data->createHistogram("x,y", 20, 20);
54
55 // Create and fill ROOT 2D histogram (50x50 bins) with sampling of pdf
56 // TH2D* hh_pdf = model.createHistogram("hh_model",x,Binning(50),YVar(y,Binning(50))) ;
57 TH1 *hh_pdf = model.createHistogram("x,y", 50, 50);
58 hh_pdf->SetLineColor(kBlue);
59
60 // C r e a t e 3 D m o d e l a n d d a t a s e t
61 // -----------------------------------------------------
62
63 // Create observables
64 RooRealVar z("z", "z", -5, 5);
65
66 RooGaussian gz("gz", "gz", z, RooConst(0), RooConst(2));
67 RooProdPdf model3("model3", "model3", RooArgSet(model, gz));
68
69 RooDataSet *data3 = model3.generate(RooArgSet(x, y, z), 10000);
70
71 // M a k e 3 D p l o t s o f d a t a a n d m o d e l
72 // -------------------------------------------------------------
73
74 // Create and fill ROOT 2D histogram (8x8x8 bins) with contents of dataset
75 TH1 *hh_data3 = data3->createHistogram("hh_data3", x, Binning(8), YVar(y, Binning(8)), ZVar(z, Binning(8)));
76
77 // Create and fill ROOT 2D histogram (20x20x20 bins) with sampling of pdf
78 TH1 *hh_pdf3 = model3.createHistogram("hh_model3", x, Binning(20), YVar(y, Binning(20)), ZVar(z, Binning(20)));
79 hh_pdf3->SetFillColor(kBlue);
80
81 TCanvas *c1 = new TCanvas("rf309_2dimplot", "rf309_2dimplot", 800, 800);
82 c1->Divide(2, 2);
83 c1->cd(1);
84 gPad->SetLeftMargin(0.15);
85 hh_data->GetZaxis()->SetTitleOffset(1.4);
86 hh_data->Draw("lego");
87 c1->cd(2);
88 gPad->SetLeftMargin(0.20);
89 hh_pdf->GetZaxis()->SetTitleOffset(2.5);
90 hh_pdf->Draw("surf");
91 c1->cd(3);
92 gPad->SetLeftMargin(0.15);
93 hh_data->GetZaxis()->SetTitleOffset(1.4);
94 hh_data->Draw("box");
95 c1->cd(4);
96 gPad->SetLeftMargin(0.15);
97 hh_pdf->GetZaxis()->SetTitleOffset(2.5);
98 hh_pdf->Draw("cont3");
99
100 TCanvas *c2 = new TCanvas("rf309_3dimplot", "rf309_3dimplot", 800, 400);
101 c2->Divide(2);
102 c2->cd(1);
103 gPad->SetLeftMargin(0.15);
104 hh_data3->GetZaxis()->SetTitleOffset(1.4);
105 hh_data3->Draw("lego");
106 c2->cd(2);
107 gPad->SetLeftMargin(0.15);
108 hh_pdf3->GetZaxis()->SetTitleOffset(1.4);
109 hh_pdf3->Draw("iso");
110}
@ kBlue
Definition: Rtypes.h:66
#define gPad
Definition: TVirtualPad.h:287
RooArgSet is a container object that can hold multiple RooAbsArg objects.
Definition: RooArgSet.h:29
RooDataSet is a container class to hold unbinned data.
Definition: RooDataSet.h:33
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.
A RooFormulaVar is a generic implementation of a real-valued object, which takes a RooArgList of serv...
Definition: RooFormulaVar.h:30
Plain Gaussian p.d.f.
Definition: RooGaussian.h:24
RooProdPdf is an efficient implementation of a product of PDFs of the form.
Definition: RooProdPdf.h:37
RooRealVar represents a variable that can be changed from the outside.
Definition: RooRealVar.h:39
virtual void SetTitleOffset(Float_t offset=1)
Set distance between the axis and the axis title.
Definition: TAttAxis.cxx:293
virtual void SetFillColor(Color_t fcolor)
Set the fill area color.
Definition: TAttFill.h:37
virtual void SetLineColor(Color_t lcolor)
Set the line color.
Definition: TAttLine.h:40
The Canvas class.
Definition: TCanvas.h:23
TH1 is the base class of all histogram classes in ROOT.
Definition: TH1.h:58
TAxis * GetZaxis()
Definition: TH1.h:322
virtual void Draw(Option_t *option="")
Draw this histogram with options.
Definition: TH1.cxx:3073
RooCmdArg YVar(const RooAbsRealLValue &var, const RooCmdArg &arg=RooCmdArg::none())
RooCmdArg ZVar(const RooAbsRealLValue &var, const RooCmdArg &arg=RooCmdArg::none())
RooConstVar & RooConst(Double_t val)
RooCmdArg Binning(const RooAbsBinning &binning)
const Double_t sigma
return c1
Definition: legend1.C:41
Double_t y[n]
Definition: legend1.C:17
Double_t x[n]
Definition: legend1.C:17
return c2
Definition: legend2.C:14
The namespace RooFit contains mostly switches that change the behaviour of functions of PDFs (or othe...