////////////////////////////////////////////////////////////////////////// // // 'BASIC FUNCTIONALITY' RooFit tutorial macro #101 // // Fitting, plotting, toy data generation on one-dimensional p.d.f // // pdf = gauss(x,m,s) // // // 07/2008 - Wouter Verkerke // ///////////////////////////////////////////////////////////////////////// //gSystem->AddIncludePath("-I/home/kyletos/Downloads/root-6.06.06/roofit/roofitcore/inc/"); gInterpreter->AddIncludePath("/home/kyletos/Downloads/root-6.06.06/roofit/roofitcore/inc"); //gROOT->ProcessLine(".include /home/kyletos/Downloads/root-6.06.06/roofit/roofitcore/inc/"); #ifndef __CINT__ #include "RooGlobalFunc.h" #endif #include "RooRealVar.h" #include "RooDataSet.h" #include "RooGaussian.h" #include "TCanvas.h" #include "RooPlot.h" #include "TAxis.h" using namespace RooFit ; void rf101_basics() { // S e t u p m o d e l // --------------------- // Declare variables x,mean,sigma with associated name, title, initial value and allowed range RooRealVar x("x","x",-10,10) ; RooRealVar mean("mean","mean of gaussian",1,-10,10) ; RooRealVar sigma("sigma","width of gaussian",1,0.1,10) ; // Build gaussian p.d.f in terms of x,mean and sigma RooGaussian gauss("gauss","gaussian PDF",x,mean,sigma) ; // Construct plot frame in 'x' RooPlot* xframe = x.frame(Title("Gaussian p.d.f.")) ; // P l o t m o d e l a n d c h a n g e p a r a m e t e r v a l u e s // --------------------------------------------------------------------------- // Plot gauss in frame (i.e. in x) gauss.plotOn(xframe) ; // Change the value of sigma to 3 sigma.setVal(3) ; // Plot gauss in frame (i.e. in x) and draw frame on canvas gauss.plotOn(xframe,LineColor(kRed)) ; // G e n e r a t e e v e n t s // ----------------------------- // Generate a dataset of 1000 events in x from gauss RooDataSet* data = gauss.generate(x,10000) ; // Make a second plot frame in x and draw both the // data and the p.d.f in the frame RooPlot* xframe2 = x.frame(Title("Gaussian p.d.f. with data")) ; data->plotOn(xframe2) ; gauss.plotOn(xframe2) ; // F i t m o d e l t o d a t a // ----------------------------- // Fit pdf to data gauss.fitTo(*data) ; // Print values of mean and sigma (that now reflect fitted values and errors) mean.Print() ; sigma.Print() ; // Draw all frames on a canvas TCanvas* c = new TCanvas("rf101_basics","rf101_basics",800,400) ; c->Divide(2) ; c->cd(1) ; gPad->SetLeftMargin(0.15) ; xframe->GetYaxis()->SetTitleOffset(1.6) ; xframe->Draw() ; c->cd(2) ; gPad->SetLeftMargin(0.15) ; xframe2->GetYaxis()->SetTitleOffset(1.6) ; xframe2->Draw() ; }