#include "TH1.h" #include "TF1.h" #include "TLegend.h" #include "TCanvas.h" // Quadratic background function Double_t background(Double_t *x, Double_t *par) { return par[0] + par[1]*x[0] + par[2]*x[0]*x[0]; } // Lorenzian Peak function Double_t lorentzianPeak(Double_t *x, Double_t *par) { return (0.5*par[0]*par[1]/TMath::Pi()) / TMath::Max( 1.e-10,(x[0]-par[2])*(x[0]-par[2]) + .25*par[1]*par[1]); } // Sum of background and peak function Double_t fitFunction(Double_t *x, Double_t *par) { return background(x,par) + lorentzianPeak(x,&par[3]); } void FittingDemo() { //Bevington Exercise by Peter Malzacher, modified by Rene Brun const int nBins = 60; Stat_t data[nBins] = { 6, 1,10,12, 6,13,23,22,15,21, 23,26,36,25,27,35,40,44,66,81, 75,57,48,45,46,41,35,36,53,32, 40,37,38,31,36,44,42,37,32,32, 43,44,35,33,33,39,29,41,32,44, 26,39,29,35,32,21,21,15,25,15}; TCanvas *c1 = new TCanvas("c1","Fitting Demo",10,10,700,500); c1->SetFillColor(33); c1->SetFrameFillColor(41); c1->SetGrid(); TH1F *histo = new TH1F("histo","Lorentzian Peak on Quadratic Background",60,0,3); histo->SetMarkerStyle(21); histo->SetMarkerSize(0.8); histo->SetStats(0); for(int i=0; i < nBins; i++) histo->SetBinContent(i+1,data[i]); // create a TF1 with the range from 0 to 3 and 6 parameters TF1 *fitFcn = new TF1("fitFcn",fitFunction,0,3,6); fitFcn->SetNpx(500); fitFcn->SetLineWidth(4); fitFcn->SetLineColor(kMagenta); // first try without starting values for the parameters // This defaults to 1 for each param. // this results in an ok fit for the polynomial function // however the non-linear part (lorenzian) does not // respond well. fitFcn->SetParameters(1,1,1,1,1,1); histo->Fit("fitFcn","0"); // second try: set start values for some parameters fitFcn->SetParameter(4,0.2); // width fitFcn->SetParameter(5,1); // peak histo->Fit("fitFcn","V+","ep"); // improve the picture: TF1 *backFcn = new TF1("backFcn",background,0,3,3); backFcn->SetLineColor(kRed); TF1 *signalFcn = new TF1("signalFcn",lorentzianPeak,0,3,3); signalFcn->SetLineColor(kBlue); signalFcn->SetNpx(500); Double_t par[6]; // writes the fit results into the par array fitFcn->GetParameters(par); backFcn->SetParameters(par); backFcn->Draw("same"); signalFcn->SetParameters(&par[3]); signalFcn->Draw("same"); // draw the legend TLegend *legend=new TLegend(0.6,0.65,0.88,0.85); legend->SetTextFont(72); legend->SetTextSize(0.04); legend->AddEntry(histo,"Data","lp"); legend->AddEntry(backFcn,"Background fit","l"); legend->AddEntry(signalFcn,"Signal fit","l"); legend->AddEntry(fitFcn,"Global Fit","l"); legend->Draw(); }