/// \file /// \ingroup tutorial_roofit /// \notebook -nodraw /// /// 'ADDITION AND CONVOLUTION' RooFit tutorial macro #204 /// /// Extended maximum likelihood fit with alternate range definition /// for observed number of events. /// If multiple ranges are used, or only a part of the data is fitted, /// it is advisable to use a RooAddPdf to extend the model. See tutorial /// 204a. /// /// \macro_output /// \macro_code /// /// \date 07/2008 /// \author Wouter Verkerke #include "RooRealVar.h" #include "RooDataSet.h" #include "RooGaussian.h" #include "RooChebychev.h" #include "RooAddPdf.h" #include "RooExtendPdf.h" #include "RooFitResult.h" #include "TCanvas.h" #include "TAxis.h" #include "RooPlot.h" using namespace RooFit; void rf204_extrangefit() { // S e t u p c o m p o n e n t p d f s // --------------------------------------- // 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 p.d.f. 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 p.d.f. RooRealVar sig1frac("sig1frac", "fraction of component 1 in signal", 0.8, 0., 1.); RooAddPdf sig("sig", "Signal", RooArgList(sig1, sig2), sig1frac); // C o n s t r u c t e x t e n d e d c o m p s wi t h r a n g e s p e c // ------------------------------------------------------------------------------ // Define signal range in which events counts are to be defined x.setRange("signalRange", 4, 6); // Associated nsig/nbkg as expected number of events with sig/bkg _in_the_range_ "signalRange" RooRealVar nsig("nsig", "number of signal events in signalRange", 500, 0., 10000) ; RooRealVar nbkg("nbkg", "number of background events in signalRange", 500, 0, 10000) ; // Use AddPdf to extend the model: RooAddPdf model("model","(g1+g2)+a", RooArgList(bkg,sig), RooArgList(nbkg,nsig)) ; // Clone these models here because the interpretation of normalisation coefficients changes // when different ranges are used: RooAddPdf model2(model); RooAddPdf model3(model); // S a m p l e d a t a , f i t m o d e l // ------------------------------------------- // Generate 1000 events from model so that nsig,nbkg come out to numbers <<500 in fit RooDataSet *data = model.generate(x, 1000); auto canv = new TCanvas("Canvas", "Canvas", 1500, 600); canv->Divide(3,1); // Fit full range // ------------------------------------------- canv->cd(1); // Perform unbinned ML fit to data, full range RooFitResult* r = model.fitTo(*data,Save()) ; r->Print() ; }