rf205_compplot.py

Go to the documentation of this file.

## \file
## \ingroup tutorial_roofit
## \notebook
## Addition and convolution: options for plotting components of composite p.d.f.s.
##
## \macro_code
##
## \date February 2018
## \author 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")