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rf602_chi2fit.C File Reference

## Detailed Description

Likelihood and minimization: setting up a chi^2 fit to a binned dataset

#include "RooRealVar.h"
#include "RooDataSet.h"
#include "RooGaussian.h"
#include "RooChebychev.h"
#include "TCanvas.h"
#include "TAxis.h"
#include "RooPlot.h"
using namespace RooFit;
{
// S e t u p m o d e l
// ---------------------
// Declare observable x
RooRealVar x("x", "x", 0, 10);
// Create two Gaussian PDFs g1(x,mean1,sigma) anf g2(x,mean2,sigma) and their parameters
RooRealVar mean("mean", "mean of gaussians", 5);
RooRealVar sigma1("sigma1", "width of gaussians", 0.5);
RooRealVar sigma2("sigma2", "width of gaussians", 1);
RooGaussian sig1("sig1", "Signal component 1", x, mean, sigma1);
RooGaussian sig2("sig2", "Signal component 2", x, mean, sigma2);
// Build Chebychev polynomial pdf
RooRealVar a0("a0", "a0", 0.5, 0., 1.);
RooRealVar a1("a1", "a1", 0.2, 0., 1.);
RooChebychev bkg("bkg", "Background", x, RooArgSet(a0, a1));
// Sum the signal components into a composite signal pdf
RooRealVar sig1frac("sig1frac", "fraction of component 1 in signal", 0.8, 0., 1.);
RooAddPdf sig("sig", "Signal", RooArgList(sig1, sig2), sig1frac);
// Sum the composite signal and background
RooRealVar bkgfrac("bkgfrac", "fraction of background", 0.5, 0., 1.);
RooAddPdf model("model", "g1+g2+a", RooArgList(bkg, sig), bkgfrac);
// C r e a t e b i n n e d d a t a s e t
// -----------------------------------------
std::unique_ptr<RooDataSet> d{model.generate(x, 10000)};
std::unique_ptr<RooDataHist> dh{d->binnedClone()};
// Construct a chi^2 of the data and the model.
// When a pdf is used in a chi^2 fit, the probability density scaled
// by the number of events in the dataset to obtain the fit function
// If model is an extended pdf, the expected number events is used
// instead of the observed number of events.
model.chi2FitTo(*dh, {PrintLevel(-1)});
// NB: It is also possible to fit a RooAbsReal function to a RooDataHist
// using chi2FitTo().
// Note that entries with zero bins are _not_ allowed
// for a proper chi^2 calculation and will give error
// messages
std::unique_ptr<RooAbsData> dsmall{d->reduce(EventRange(1, 100))};
std::unique_ptr<RooDataHist> dhsmall{static_cast<RooDataSet&>(*dsmall).binnedClone()};
std::unique_ptr<RooAbsReal> chi2_lowstat{model.createChi2(*dhsmall)};
cout << chi2_lowstat->getVal() << endl;
}
#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
[#0] WARNING:InputArguments -- The parameter 'sigma1' with range [-inf, inf] of the RooGaussian 'sig1' exceeds the safe range of (0, inf). Advise to limit its range.
[#0] WARNING:InputArguments -- The parameter 'sigma2' with range [-inf, inf] of the RooGaussian 'sig2' exceeds the safe range of (0, inf). Advise to limit its range.
[#1] INFO:Minimization -- RooAbsMinimizerFcn::setOptimizeConst: activating const optimization
[#1] INFO:Minimization -- The following expressions have been identified as constant and will be precalculated and cached: (sig1,sig2)
[#1] INFO:Minimization -- The following expressions will be evaluated in cache-and-track mode: (bkg)
[#1] INFO:Minimization -- RooAbsMinimizerFcn::setOptimizeConst: deactivating const optimization
90.865
Date
July 2008

Definition in file rf602_chi2fit.C.