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rf602_chi2fit.C
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1/// \file
2/// \ingroup tutorial_roofit
3/// \notebook -nodraw
4/// Likelihood and minimization: setting up a chi^2 fit to a binned dataset
5///
6/// \macro_code
7/// \macro_output
8///
9/// \date July 2008
10/// \author Wouter Verkerke
11
12#include "RooRealVar.h"
13#include "RooDataSet.h"
14#include "RooGaussian.h"
15#include "RooChebychev.h"
17#include "TCanvas.h"
18#include "TAxis.h"
19#include "RooPlot.h"
20using namespace RooFit;
21
22void rf602_chi2fit()
23{
24
25 // S e t u p m o d e l
26 // ---------------------
27
28 // Declare observable x
29 RooRealVar x("x", "x", 0, 10);
30
31 // Create two Gaussian PDFs g1(x,mean1,sigma) anf g2(x,mean2,sigma) and their parameters
32 RooRealVar mean("mean", "mean of gaussians", 5);
33 RooRealVar sigma1("sigma1", "width of gaussians", 0.5);
34 RooRealVar sigma2("sigma2", "width of gaussians", 1);
35
36 RooGaussian sig1("sig1", "Signal component 1", x, mean, sigma1);
37 RooGaussian sig2("sig2", "Signal component 2", x, mean, sigma2);
38
39 // Build Chebychev polynomial pdf
40 RooRealVar a0("a0", "a0", 0.5, 0., 1.);
41 RooRealVar a1("a1", "a1", 0.2, 0., 1.);
42 RooChebychev bkg("bkg", "Background", x, RooArgSet(a0, a1));
43
44 // Sum the signal components into a composite signal pdf
45 RooRealVar sig1frac("sig1frac", "fraction of component 1 in signal", 0.8, 0., 1.);
46 RooAddPdf sig("sig", "Signal", RooArgList(sig1, sig2), sig1frac);
47
48 // Sum the composite signal and background
49 RooRealVar bkgfrac("bkgfrac", "fraction of background", 0.5, 0., 1.);
50 RooAddPdf model("model", "g1+g2+a", RooArgList(bkg, sig), bkgfrac);
51
52 // C r e a t e b i n n e d d a t a s e t
53 // -----------------------------------------
54
55 std::unique_ptr<RooDataSet> d{model.generate(x, 10000)};
56 std::unique_ptr<RooDataHist> dh{d->binnedClone()};
57
58 // Construct a chi^2 of the data and the model.
59 // When a pdf is used in a chi^2 fit, the probability density scaled
60 // by the number of events in the dataset to obtain the fit function
61 // If model is an extended pdf, the expected number events is used
62 // instead of the observed number of events.
63 model.chi2FitTo(*dh, {PrintLevel(-1)});
64
65 // NB: It is also possible to fit a RooAbsReal function to a RooDataHist
66 // using chi2FitTo().
67
68 // Note that entries with zero bins are _not_ allowed
69 // for a proper chi^2 calculation and will give error
70 // messages
71 std::unique_ptr<RooAbsData> dsmall{d->reduce(EventRange(1, 100))};
72 std::unique_ptr<RooDataHist> dhsmall{static_cast<RooDataSet&>(*dsmall).binnedClone()};
73 std::unique_ptr<RooAbsReal> chi2_lowstat{model.createChi2(*dhsmall)};
74 cout << chi2_lowstat->getVal() << endl;
75}
#define d(i)
Definition RSha256.hxx:102
Efficient implementation of a sum of PDFs of the form.
RooArgList is a container object that can hold multiple RooAbsArg objects.
Definition RooArgList.h:22
RooArgSet is a container object that can hold multiple RooAbsArg objects.
Definition RooArgSet.h:55
Chebychev polynomial p.d.f.
Container class to hold unbinned data.
Definition RooDataSet.h:57
RooFit::OwningPtr< RooDataHist > binnedClone(const char *newName=nullptr, const char *newTitle=nullptr) const
Return binned clone of this dataset.
Plain Gaussian p.d.f.
Definition RooGaussian.h:24
Variable that can be changed from the outside.
Definition RooRealVar.h:37
RooCmdArg EventRange(Int_t nStart, Int_t nStop)
RooCmdArg PrintLevel(Int_t code)
Double_t x[n]
Definition legend1.C:17
The namespace RooFit contains mostly switches that change the behaviour of functions of PDFs (or othe...
Definition JSONIO.h:26