# rf205_compplot¶

Addition and convolution: options for plotting components of composite pdfs.

Author: Clemens Lange, Wouter Verkerke (C++ version)
This notebook tutorial was automatically generated with ROOTBOOK-izer from the macro found in the ROOT repository on Wednesday, November 30, 2022 at 11:22 AM.

In [1]:
import ROOT

Welcome to JupyROOT 6.27/01


## Set up composite pdf¶

Declare observable x

In [2]:
x = ROOT.RooRealVar("x", "x", 0, 10)


Create two Gaussian PDFs g1(x,mean1,sigma) anf g2(x,mean2,sigma) and their parameters

In [3]:
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)

[#0] WARNING:InputArguments -- The parameter 'sigma1' with range [-1e+30, 1e+30] of the RooGaussian 'sig1' exceeds the safe range of (0, inf). Advise to limit its range.
[#0] WARNING:InputArguments -- The parameter 'sigma2' with range [-1e+30, 1e+30] of the RooGaussian 'sig2' exceeds the safe range of (0, inf). Advise to limit its range.


Sum the signal components into a composite signal pdf

In [4]:
sig1frac = ROOT.RooRealVar("sig1frac", "fraction of component 1 in signal", 0.8, 0.0, 1.0)
sig = ROOT.RooAddPdf("sig", "Signal", [sig1, sig2], [sig1frac])


Build Chebychev polynomial pdf

In [5]:
a0 = ROOT.RooRealVar("a0", "a0", 0.5, 0.0, 1.0)
a1 = ROOT.RooRealVar("a1", "a1", -0.2, 0.0, 1.0)
bkg1 = ROOT.RooChebychev("bkg1", "Background 1", x, [a0, a1])


Build expontential pdf

In [6]:
alpha = ROOT.RooRealVar("alpha", "alpha", -1)
bkg2 = ROOT.RooExponential("bkg2", "Background 2", x, alpha)


Sum the background components into a composite background pdf

In [7]:
bkg1frac = ROOT.RooRealVar("sig1frac", "fraction of component 1 in background", 0.2, 0.0, 1.0)
bkg = ROOT.RooAddPdf("bkg", "Signal", [bkg1, bkg2], [sig1frac])


Sum the composite signal and background

In [8]:
bkgfrac = ROOT.RooRealVar("bkgfrac", "fraction of background", 0.5, 0.0, 1.0)
model = ROOT.RooAddPdf("model", "g1+g2+a", [bkg, sig], [bkgfrac])


## Set up basic plot with data and full pdf¶

Generate a data sample of 1000 events in x from model

In [9]:
data = model.generate({x}, 1000)


Plot data and complete PDF overlaid

In [10]:
xframe = x.frame(Title="Component plotting of pdf=(sig1+sig2)+(bkg1+bkg2)")
data.plotOn(xframe)
model.plotOn(xframe)

Out[10]:
<cppyy.gbl.RooPlot object at 0xa15a2b0>

Clone xframe for use below

In [11]:
xframe2 = xframe.Clone("xframe2")


## Make component by object reference¶

Plot single background component specified by object reference

In [12]:
ras_bkg = {bkg}
model.plotOn(xframe, Components=ras_bkg, LineColor="r")

Out[12]:
<cppyy.gbl.RooPlot object at 0xa15a2b0>
[#1] INFO:Plotting -- RooAbsPdf::plotOn(model) directly selected PDF components: (bkg)
[#1] INFO:Plotting -- RooAbsPdf::plotOn(model) indirectly selected PDF components: (bkg1,bkg2)


Plot single background component specified by object reference

In [13]:
ras_bkg2 = {bkg2}
model.plotOn(xframe, Components=ras_bkg2, LineStyle="--", LineColor="r")

Out[13]:
<cppyy.gbl.RooPlot object at 0xa15a2b0>
[#1] INFO:Plotting -- RooAbsPdf::plotOn(model) directly selected PDF components: (bkg2)
[#1] INFO:Plotting -- RooAbsPdf::plotOn(model) indirectly selected PDF components: (bkg)


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')

In [14]:
ras_bkg_sig2 = {bkg, sig2}
model.plotOn(xframe, Components=ras_bkg_sig2, LineStyle=":")

Out[14]:
<cppyy.gbl.RooPlot object at 0xa15a2b0>
[#1] INFO:Plotting -- RooAbsPdf::plotOn(model) directly selected PDF components: (bkg,sig2)
[#1] INFO:Plotting -- RooAbsPdf::plotOn(model) indirectly selected PDF components: (bkg1,bkg2,sig)


## Make component by name/regexp¶

Plot single background component specified by name

In [15]:
model.plotOn(xframe2, Components="bkg", LineColor="c")

Out[15]:
<cppyy.gbl.RooPlot object at 0xa299ed0>
[#1] INFO:Plotting -- RooAbsPdf::plotOn(model) directly selected PDF components: (bkg)
[#1] INFO:Plotting -- RooAbsPdf::plotOn(model) indirectly selected PDF components: (bkg1,bkg2)


Plot multiple background components specified by name

In [16]:
model.plotOn(xframe2, Components="bkg1,sig2", LineStyle=":", LineColor="c")

Out[16]:
<cppyy.gbl.RooPlot object at 0xa299ed0>
[#1] INFO:Plotting -- RooAbsPdf::plotOn(model) directly selected PDF components: (bkg1,sig2)
[#1] INFO:Plotting -- RooAbsPdf::plotOn(model) indirectly selected PDF components: (bkg,sig)


Plot multiple background components specified by regular expression on name

In [17]:
model.plotOn(xframe2, Components="sig*", LineStyle="--", LineColor="c")

Out[17]:
<cppyy.gbl.RooPlot object at 0xa299ed0>
[#1] INFO:Plotting -- RooAbsPdf::plotOn(model) directly selected PDF components: (sig,sig1,sig2)
[#1] INFO:Plotting -- RooAbsPdf::plotOn(model) indirectly selected PDF components: ()


Plot multiple background components specified by multiple regular expressions on name

In [18]:
model.plotOn(xframe2, Invisible=True, Components="bkg1,sig*", LineStyle="--", LineColor="y")

Out[18]:
<cppyy.gbl.RooPlot object at 0xa299ed0>
[#1] INFO:Plotting -- RooAbsPdf::plotOn(model) directly selected PDF components: (bkg1,sig,sig1,sig2)
[#1] INFO:Plotting -- RooAbsPdf::plotOn(model) indirectly selected PDF components: (bkg)


Draw the frame on the canvas

In [19]:
c = ROOT.TCanvas("rf205_compplot", "rf205_compplot", 800, 400)
c.Divide(2)
c.cd(1)
xframe.GetYaxis().SetTitleOffset(1.4)
xframe.Draw()
c.cd(2)
xframe2.GetYaxis().SetTitleOffset(1.4)
xframe2.Draw()

c.SaveAs("rf205_compplot.png")

Info in <TCanvas::Print>: png file rf205_compplot.png has been created


Draw all canvases

In [20]:
from ROOT import gROOT
gROOT.GetListOfCanvases().Draw()