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rf608_fitresultaspdf.C
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1 /// \file
2 /// \ingroup tutorial_roofit
3 /// \notebook
4 ///
5 /// Likelihood and minimization: representing the parabolic approximation of the fit as a multi-variate Gaussian on the
6 /// parameters of the fitted p.d.f.
7 ///
8 /// \macro_image
9 /// \macro_output
10 /// \macro_code
11 ///
12 /// \date 07/2008
13 /// \author Wouter Verkerke
14 
15 #include "RooRealVar.h"
16 #include "RooDataSet.h"
17 #include "RooGaussian.h"
18 #include "RooConstVar.h"
19 #include "RooAddPdf.h"
20 #include "RooChebychev.h"
21 #include "RooFitResult.h"
22 #include "TCanvas.h"
23 #include "TAxis.h"
24 #include "RooPlot.h"
25 #include "TFile.h"
26 #include "TStyle.h"
27 #include "TH2.h"
28 #include "TH3.h"
29 
30 using namespace RooFit;
31 
33 {
34  // C r e a t e m o d e l a n d d a t a s e t
35  // -----------------------------------------------
36 
37  // Observable
38  RooRealVar x("x", "x", -20, 20);
39 
40  // Model (intentional strong correlations)
41  RooRealVar mean("mean", "mean of g1 and g2", 0, -1, 1);
42  RooRealVar sigma_g1("sigma_g1", "width of g1", 2);
43  RooGaussian g1("g1", "g1", x, mean, sigma_g1);
44 
45  RooRealVar sigma_g2("sigma_g2", "width of g2", 4, 3.0, 5.0);
46  RooGaussian g2("g2", "g2", x, mean, sigma_g2);
47 
48  RooRealVar frac("frac", "frac", 0.5, 0.0, 1.0);
49  RooAddPdf model("model", "model", RooArgList(g1, g2), frac);
50 
51  // Generate 1000 events
52  RooDataSet *data = model.generate(x, 1000);
53 
54  // F i t m o d e l t o d a t a
55  // ----------------------------------
56 
57  RooFitResult *r = model.fitTo(*data, Save());
58 
59  // C r e a t e M V G a u s s i a n p d f o f f i t t e d p a r a m e t e r s
60  // ------------------------------------------------------------------------------------
61 
62  RooAbsPdf *parabPdf = r->createHessePdf(RooArgSet(frac, mean, sigma_g2));
63 
64  // S o m e e x e c e r c i s e s w i t h t h e p a r a m e t e r p d f
65  // -----------------------------------------------------------------------------
66 
67  // Generate 100K points in the parameter space, sampled from the MVGaussian p.d.f.
68  RooDataSet *d = parabPdf->generate(RooArgSet(mean, sigma_g2, frac), 100000);
69 
70  // Sample a 3-D histogram of the p.d.f. to be visualized as an error ellipsoid using the GLISO draw option
71  TH3 *hh_3d = (TH3 *)parabPdf->createHistogram("mean,sigma_g2,frac", 25, 25, 25);
72  hh_3d->SetFillColor(kBlue);
73 
74  // Project 3D parameter p.d.f. down to 3 permutations of two-dimensional p.d.f.s
75  // The integrations corresponding to these projections are performed analytically
76  // by the MV Gaussian p.d.f.
77  RooAbsPdf *pdf_sigmag2_frac = parabPdf->createProjection(mean);
78  RooAbsPdf *pdf_mean_frac = parabPdf->createProjection(sigma_g2);
79  RooAbsPdf *pdf_mean_sigmag2 = parabPdf->createProjection(frac);
80 
81  // Make 2D plots of the 3 two-dimensional p.d.f. projections
82  TH2 *hh_sigmag2_frac = (TH2 *)pdf_sigmag2_frac->createHistogram("sigma_g2,frac", 50, 50);
83  TH2 *hh_mean_frac = (TH2 *)pdf_mean_frac->createHistogram("mean,frac", 50, 50);
84  TH2 *hh_mean_sigmag2 = (TH2 *)pdf_mean_sigmag2->createHistogram("mean,sigma_g2", 50, 50);
85  hh_mean_frac->SetLineColor(kBlue);
86  hh_sigmag2_frac->SetLineColor(kBlue);
87  hh_mean_sigmag2->SetLineColor(kBlue);
88 
89  // Draw the 'sigar'
90  new TCanvas("rf608_fitresultaspdf_1", "rf608_fitresultaspdf_1", 600, 600);
91  hh_3d->Draw("iso");
92 
93  // Draw the 2D projections of the 3D p.d.f.
94  TCanvas *c2 = new TCanvas("rf608_fitresultaspdf_2", "rf608_fitresultaspdf_2", 900, 600);
95  c2->Divide(3, 2);
96  c2->cd(1);
97  gPad->SetLeftMargin(0.15);
98  hh_mean_sigmag2->GetZaxis()->SetTitleOffset(1.4);
99  hh_mean_sigmag2->Draw("surf3");
100  c2->cd(2);
101  gPad->SetLeftMargin(0.15);
102  hh_sigmag2_frac->GetZaxis()->SetTitleOffset(1.4);
103  hh_sigmag2_frac->Draw("surf3");
104  c2->cd(3);
105  gPad->SetLeftMargin(0.15);
106  hh_mean_frac->GetZaxis()->SetTitleOffset(1.4);
107  hh_mean_frac->Draw("surf3");
108 
109  // Draw the distributions of parameter points sampled from the p.d.f.
110  TH1 *tmp1 = d->createHistogram("mean,sigma_g2", 50, 50);
111  TH1 *tmp2 = d->createHistogram("sigma_g2,frac", 50, 50);
112  TH1 *tmp3 = d->createHistogram("mean,frac", 50, 50);
113 
114  c2->cd(4);
115  gPad->SetLeftMargin(0.15);
116  tmp1->GetZaxis()->SetTitleOffset(1.4);
117  tmp1->Draw("lego3");
118  c2->cd(5);
119  gPad->SetLeftMargin(0.15);
120  tmp2->GetZaxis()->SetTitleOffset(1.4);
121  tmp2->Draw("lego3");
122  c2->cd(6);
123  gPad->SetLeftMargin(0.15);
124  tmp3->GetZaxis()->SetTitleOffset(1.4);
125  tmp3->Draw("lego3");
126 }
RooChebychev.h
RooAddPdf
Definition: RooAddPdf.h:32
r
ROOT::R::TRInterface & r
Definition: Object.C:4
RooArgList
Definition: RooArgList.h:21
RooGaussian.h
TStyle.h
x
Double_t x[n]
Definition: legend1.C:17
RooGaussian
Definition: RooGaussian.h:25
RooAddPdf.h
TCanvas.h
TH1::GetZaxis
TAxis * GetZaxis()
Definition: TH1.h:319
RooDataSet.h
TFile.h
RooFitResult
Definition: RooFitResult.h:40
TH3
Definition: TH3.h:31
RooFit
Definition: RooCFunction1Binding.h:29
RooPlot.h
TH2
Definition: TH2.h:30
RooRealVar.h
TH2.h
RooFitResult.h
TH3.h
RooConstVar.h
RooAbsReal::createHistogram
TH1 * createHistogram(const char *varNameList, Int_t xbins=0, Int_t ybins=0, Int_t zbins=0) const
Create and fill a ROOT histogram TH1, TH2 or TH3 with the values of this function for the variables w...
Definition: RooAbsReal.cxx:1291
RooAbsPdf::createProjection
virtual RooAbsPdf * createProjection(const RooArgSet &iset)
Return a p.d.f that represent a projection of this p.d.f integrated over given observables.
Definition: RooAbsPdf.cxx:3362
TCanvas
Definition: TCanvas.h:23
RooAbsPdf::generate
RooDataSet * generate(const RooArgSet &whatVars, Int_t nEvents, const RooCmdArg &arg1, const RooCmdArg &arg2=RooCmdArg::none(), const RooCmdArg &arg3=RooCmdArg::none(), const RooCmdArg &arg4=RooCmdArg::none(), const RooCmdArg &arg5=RooCmdArg::none())
See RooAbsPdf::generate(const RooArgSet&,const RooCmdArg&,const RooCmdArg&,const RooCmdArg&,...
Definition: RooAbsPdf.h:55
TAxis.h
TH1
Definition: TH1.h:57
kBlue
@ kBlue
Definition: Rtypes.h:66
d
#define d(i)
Definition: RSha256.hxx:120
c2
return c2
Definition: legend2.C:14
gPad
#define gPad
Definition: TVirtualPad.h:287
RooDataSet
Definition: RooDataSet.h:33
make_cnn_model.model
model
Definition: make_cnn_model.py:6
RooAbsPdf
Definition: RooAbsPdf.h:40
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
RooFit::Save
RooCmdArg Save(Bool_t flag=kTRUE)
Definition: RooGlobalFunc.cxx:187
RooArgSet
Definition: RooArgSet.h:28
TH1::Draw
virtual void Draw(Option_t *option="")
Draw this histogram with options.
Definition: TH1.cxx:2997
rf608_fitresultaspdf
Definition: rf608_fitresultaspdf.py:1