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rf315_projectpdf.C
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1 /// \file
2 /// \ingroup tutorial_roofit
3 /// \notebook
4 /// Multidimensional models: marginizalization of multi-dimensional p.d.f.s through integration
5 ///
6 /// \macro_image
7 /// \macro_output
8 /// \macro_code
9 /// \author 07/2008 - Wouter Verkerke
10 
11 #include "RooRealVar.h"
12 #include "RooDataHist.h"
13 #include "RooGaussian.h"
14 #include "RooProdPdf.h"
15 #include "RooPolyVar.h"
16 #include "TH1.h"
17 #include "TCanvas.h"
18 #include "TAxis.h"
19 #include "RooPlot.h"
20 #include "RooNumIntConfig.h"
21 #include "RooConstVar.h"
22 using namespace RooFit;
23 
24 void rf315_projectpdf()
25 {
26  // C r e a t e p d f m ( x , y ) = g x ( x | y ) * g ( y )
27  // --------------------------------------------------------------
28 
29  // Increase default precision of numeric integration
30  // as this exercise has high sensitivity to numeric integration precision
31  RooAbsPdf::defaultIntegratorConfig()->setEpsRel(1e-8);
32  RooAbsPdf::defaultIntegratorConfig()->setEpsAbs(1e-8);
33 
34  // Create observables
35  RooRealVar x("x", "x", -5, 5);
36  RooRealVar y("y", "y", -2, 2);
37 
38  // Create function f(y) = a0 + a1*y
39  RooRealVar a0("a0", "a0", 0);
40  RooRealVar a1("a1", "a1", -1.5, -3, 1);
41  RooPolyVar fy("fy", "fy", y, RooArgSet(a0, a1));
42 
43  // Create gaussx(x,f(y),sx)
44  RooRealVar sigmax("sigmax", "width of gaussian", 0.5);
45  RooGaussian gaussx("gaussx", "Gaussian in x with shifting mean in y", x, fy, sigmax);
46 
47  // Create gaussy(y,0,2)
48  RooGaussian gaussy("gaussy", "Gaussian in y", y, RooConst(0), RooConst(2));
49 
50  // Create gaussx(x,sx|y) * gaussy(y)
51  RooProdPdf model("model", "gaussx(x|y)*gaussy(y)", gaussy, Conditional(gaussx, x));
52 
53  // M a r g i n a l i z e m ( x , y ) t o m ( x )
54  // ----------------------------------------------------
55 
56  // modelx(x) = Int model(x,y) dy
57  RooAbsPdf *modelx = model.createProjection(y);
58 
59  // U s e m a r g i n a l i z e d p . d . f . a s r e g u l a r 1 - D p . d . f .
60  // ------------------------------------------------------------------------------------------
61 
62  // Sample 1000 events from modelx
63  RooAbsData *data = modelx->generateBinned(x, 1000);
64 
65  // Fit modelx to toy data
66  modelx->fitTo(*data, Verbose());
67 
68  // Plot modelx over data
69  RooPlot *frame = x.frame(40);
70  data->plotOn(frame);
71  modelx->plotOn(frame);
72 
73  // Make 2D histogram of model(x,y)
74  TH1 *hh = model.createHistogram("x,y");
75  hh->SetLineColor(kBlue);
76 
77  TCanvas *c = new TCanvas("rf315_projectpdf", "rf315_projectpdf", 800, 400);
78  c->Divide(2);
79  c->cd(1);
80  gPad->SetLeftMargin(0.15);
81  frame->GetYaxis()->SetTitleOffset(1.4);
82  frame->Draw();
83  c->cd(2);
84  gPad->SetLeftMargin(0.20);
85  hh->GetZaxis()->SetTitleOffset(2.5);
86  hh->Draw("surf");
87 }