## \file ## \ingroup tutorial_roofit ## \notebook ## ## Addition and convolution: options for plotting components of composite p.d.f.s. ## ## \macro_code ## ## \date February 2018 ## \authors Clemens Lange, Wouter Verkerke (C++ version) import ROOT # Set up composite pdf # -------------------------------------- # Declare observable x x = ROOT.RooRealVar("x", "x", 0, 10) # Create two Gaussian PDFs g1(x,mean1,sigma) anf g2(x,mean2,sigma) and # their parameters mean = ROOT.RooRealVar("mean", "mean of gaussians", 5) sigma1 = ROOT.RooRealVar("sigma1", "width of gaussians", 0.5) sigma2 = ROOT.RooRealVar("sigma2", "width of gaussians", 1) sig1 = ROOT.RooGaussian("sig1", "Signal component 1", x, mean, sigma1) sig2 = ROOT.RooGaussian("sig2", "Signal component 2", x, mean, sigma2) # Sum the signal components into a composite signal p.d.f. sig1frac = ROOT.RooRealVar( "sig1frac", "fraction of component 1 in signal", 0.8, 0., 1.) sig = ROOT.RooAddPdf( "sig", "Signal", ROOT.RooArgList(sig1, sig2), ROOT.RooArgList(sig1frac)) # Build Chebychev polynomial p.d.f. a0 = ROOT.RooRealVar("a0", "a0", 0.5, 0., 1.) a1 = ROOT.RooRealVar("a1", "a1", -0.2, 0., 1.) bkg1 = ROOT.RooChebychev("bkg1", "Background 1", x, ROOT.RooArgList(a0, a1)) # Build expontential pdf alpha = ROOT.RooRealVar("alpha", "alpha", -1) bkg2 = ROOT.RooExponential("bkg2", "Background 2", x, alpha) # Sum the background components into a composite background p.d.f. bkg1frac = ROOT.RooRealVar( "sig1frac", "fraction of component 1 in background", 0.2, 0., 1.) bkg = ROOT.RooAddPdf( "bkg", "Signal", ROOT.RooArgList(bkg1, bkg2), ROOT.RooArgList(sig1frac)) # Sum the composite signal and background bkgfrac = ROOT.RooRealVar("bkgfrac", "fraction of background", 0.5, 0., 1.) model = ROOT.RooAddPdf( "model", "g1+g2+a", ROOT.RooArgList(bkg, sig), ROOT.RooArgList(bkgfrac)) # Set up basic plot with data and full pdf # ------------------------------------------------------------------------------ # Generate a data sample of 1000 events in x from model data = model.generate(ROOT.RooArgSet(x), 1000) # Plot data and complete PDF overlaid xframe = x.frame(ROOT.RooFit.Title( "Component plotting of pdf=(sig1+sig2)+(bkg1+bkg2)")) data.plotOn(xframe) model.plotOn(xframe) # Clone xframe for use below xframe2 = xframe.Clone("xframe2") # Make component by object reference # -------------------------------------------------------------------- # Plot single background component specified by object reference ras_bkg = ROOT.RooArgSet(bkg) model.plotOn(xframe, ROOT.RooFit.Components( ras_bkg), ROOT.RooFit.LineColor(ROOT.kRed)) # Plot single background component specified by object reference ras_bkg2 = ROOT.RooArgSet(bkg2) model.plotOn(xframe, ROOT.RooFit.Components(ras_bkg2), ROOT.RooFit.LineStyle( ROOT.kDashed), ROOT.RooFit.LineColor(ROOT.kRed)) # Plot multiple background components specified by object reference # Note that specified components may occur at any level in object tree # (e.g bkg is component of 'model' and 'sig2' is component 'sig') ras_bkg_sig2 = ROOT.RooArgSet(bkg, sig2) model.plotOn(xframe, ROOT.RooFit.Components(ras_bkg_sig2), ROOT.RooFit.LineStyle(ROOT.kDotted)) # Make component by name/regexp # ------------------------------------------------------------ # Plot single background component specified by name model.plotOn(xframe2, ROOT.RooFit.Components( "bkg"), ROOT.RooFit.LineColor(ROOT.kCyan)) # Plot multiple background components specified by name model.plotOn( xframe2, ROOT.RooFit.Components("bkg1,sig2"), ROOT.RooFit.LineStyle( ROOT.kDotted), ROOT.RooFit.LineColor( ROOT.kCyan)) # Plot multiple background components specified by regular expression on # name model.plotOn( xframe2, ROOT.RooFit.Components("sig*"), ROOT.RooFit.LineStyle( ROOT.kDashed), ROOT.RooFit.LineColor( ROOT.kCyan)) # Plot multiple background components specified by multiple regular # expressions on name model.plotOn( xframe2, ROOT.RooFit.Components("bkg1,sig*"), ROOT.RooFit.LineStyle( ROOT.kDashed), ROOT.RooFit.LineColor( ROOT.kYellow), ROOT.RooFit.Invisible()) # Draw the frame on the canvas c = ROOT.TCanvas("rf205_compplot", "rf205_compplot", 800, 400) c.Divide(2) c.cd(1) ROOT.gPad.SetLeftMargin(0.15) xframe.GetYaxis().SetTitleOffset(1.4) xframe.Draw() c.cd(2) ROOT.gPad.SetLeftMargin(0.15) xframe2.GetYaxis().SetTitleOffset(1.4) xframe2.Draw() c.SaveAs("rf205_compplot.png")