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rf309_ndimplot.C
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1/// \file
2/// \ingroup tutorial_roofit
3/// \notebook
4/// 'MULTIDIMENSIONAL MODELS' RooFit tutorial macro #308
5///
6/// Making 2/3 dimensional plots of p.d.f.s and datasets
7///
8/// \macro_image
9/// \macro_output
10/// \macro_code
11/// \author 07/2008 - Wouter Verkerke
12
13
14#include "RooRealVar.h"
15#include "RooDataSet.h"
16#include "RooConstVar.h"
17#include "RooGaussian.h"
18#include "RooProdPdf.h"
19#include "TCanvas.h"
20#include "TAxis.h"
21#include "TH1.h"
22#include "RooPlot.h"
23using namespace RooFit ;
24
25
26void rf309_ndimplot()
27{
28
29 // C r e a t e 2 D m o d e l a n d d a t a s e t
30 // -----------------------------------------------------
31
32 // Create observables
33 RooRealVar x("x","x",-5,5) ;
34 RooRealVar y("y","y",-5,5) ;
35
36 // Create parameters
37 RooRealVar a0("a0","a0",-3.5,-5,5) ;
38 RooRealVar a1("a1","a1",-1.5,-1,1) ;
39 RooRealVar sigma("sigma","width of gaussian",1.5) ;
40
41 // Create interpreted function f(y) = a0 - a1*sqrt(10*abs(y))
42 RooFormulaVar fy("fy","a0-a1*sqrt(10*abs(y))",RooArgSet(y,a0,a1)) ;
43
44 // Create gauss(x,f(y),s)
45 RooGaussian model("model","Gaussian with shifting mean",x,fy,sigma) ;
46
47 // Sample dataset from gauss(x,y)
48 RooDataSet* data = model.generate(RooArgSet(x,y),10000) ;
49
50
51 // 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
52 // -------------------------------------------------------------
53
54 // Create and fill ROOT 2D histogram (20x20 bins) with contents of dataset
55 //TH2D* hh_data = data->createHistogram("hh_data",x,Binning(20),YVar(y,Binning(20))) ;
56 TH1* hh_data = data->createHistogram("x,y",20,20) ;
57
58 // Create and fill ROOT 2D histogram (50x50 bins) with sampling of pdf
59 //TH2D* hh_pdf = model.createHistogram("hh_model",x,Binning(50),YVar(y,Binning(50))) ;
60 TH1* hh_pdf = model.createHistogram("x,y",50,50) ;
61 hh_pdf->SetLineColor(kBlue) ;
62
63
64 // C r e a t e 3 D m o d e l a n d d a t a s e t
65 // -----------------------------------------------------
66
67 // Create observables
68 RooRealVar z("z","z",-5,5) ;
69
70 RooGaussian gz("gz","gz",z,RooConst(0),RooConst(2)) ;
71 RooProdPdf model3("model3","model3",RooArgSet(model,gz)) ;
72
73 RooDataSet* data3 = model3.generate(RooArgSet(x,y,z),10000) ;
74
75
76 // 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
77 // -------------------------------------------------------------
78
79 // Create and fill ROOT 2D histogram (8x8x8 bins) with contents of dataset
80 TH1* hh_data3 = data3->createHistogram("hh_data3",x,Binning(8),YVar(y,Binning(8)),ZVar(z,Binning(8))) ;
81
82 // Create and fill ROOT 2D histogram (20x20x20 bins) with sampling of pdf
83 TH1* hh_pdf3 = model3.createHistogram("hh_model3",x,Binning(20),YVar(y,Binning(20)),ZVar(z,Binning(20))) ;
84 hh_pdf3->SetFillColor(kBlue) ;
85
86
87
88 TCanvas* c1 = new TCanvas("rf309_2dimplot","rf309_2dimplot",800,800) ;
89 c1->Divide(2,2) ;
90 c1->cd(1) ; gPad->SetLeftMargin(0.15) ; hh_data->GetZaxis()->SetTitleOffset(1.4) ; hh_data->Draw("lego") ;
91 c1->cd(2) ; gPad->SetLeftMargin(0.20) ; hh_pdf->GetZaxis()->SetTitleOffset(2.5) ; hh_pdf->Draw("surf") ;
92 c1->cd(3) ; gPad->SetLeftMargin(0.15) ; hh_data->GetZaxis()->SetTitleOffset(1.4) ; hh_data->Draw("box") ;
93 c1->cd(4) ; gPad->SetLeftMargin(0.15) ; hh_pdf->GetZaxis()->SetTitleOffset(2.5) ; hh_pdf->Draw("cont3") ;
94
95 TCanvas* c2 = new TCanvas("rf309_3dimplot","rf309_3dimplot",800,400) ;
96 c2->Divide(2) ;
97 c2->cd(1) ; gPad->SetLeftMargin(0.15) ; hh_data3->GetZaxis()->SetTitleOffset(1.4) ; hh_data3->Draw("lego") ;
98 c2->cd(2) ; gPad->SetLeftMargin(0.15) ; hh_pdf3->GetZaxis()->SetTitleOffset(1.4) ; hh_pdf3->Draw("iso") ;
99
100}
@ kBlue
Definition: Rtypes.h:63
#define gPad
Definition: TVirtualPad.h:286
RooArgSet is a container object that can hold multiple RooAbsArg objects.
Definition: RooArgSet.h:28
RooDataSet is a container class to hold unbinned data.
Definition: RooDataSet.h:31
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.
Plain Gaussian p.d.f.
Definition: RooGaussian.h:25
RooProdPdf is an efficient implementation of a product of PDFs of the form.
Definition: RooProdPdf.h:31
RooRealVar represents a fundamental (non-derived) real valued object.
Definition: RooRealVar.h:36
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:294
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:31
The TH1 histogram class.
Definition: TH1.h:56
TAxis * GetZaxis()
Definition: TH1.h:318
virtual void Draw(Option_t *option="")
Draw this histogram with options.
Definition: TH1.cxx:2974
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
RooCmdArg Binning(const RooAbsBinning &binning)
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)