rf206_treevistools

Addition and convolution: tools for visualization of ROOT.RooAbsArg expression trees

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 Sunday, November 27, 2022 at 11:06 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("bkg1frac", "fraction of component 1 in background", 0.2, 0.0, 1.0)
bkg = ROOT.RooAddPdf("bkg", "Signal", [bkg1, bkg2], [bkg1frac])

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])

Print tree to stdout

In [9]:
model.Print("t")
0x9b490f0 RooAddPdf::model = 0.602695/1 [Auto,Clean] 
  0x9a52fd0/V- RooAddPdf::bkg = 0.20539/1 [Auto,Clean] 
    0x9b13a50/V- RooChebychev::bkg1 = 1 [Auto,Dirty] 
      0x962d060/V- RooRealVar::x = 5
      0x2bbe060/V- RooRealVar::a0 = 0.5
      0x2b95b40/V- RooRealVar::a1 = 0
    0x9b12c70/V- RooRealVar::bkg1frac = 0.2
    0x9b0dea0/V- RooExponential::bkg2 = 0.00673795 [Auto,Dirty] 
      0x962d060/V- RooRealVar::x = 5
      0x26fbe20/V- RooRealVar::alpha = -1
  0x9b5c8b0/V- RooRealVar::bkgfrac = 0.5
  0x9afbd40/V- RooAddPdf::sig = 1/1 [Auto,Clean] 
    0x973c210/V- RooGaussian::sig1 = 1 [Auto,Dirty] 
      0x962d060/V- RooRealVar::x = 5
      0x95545a0/V- RooRealVar::mean = 5
      0x9155590/V- RooRealVar::sigma1 = 0.5
    0x9775950/V- RooRealVar::sig1frac = 0.8
    0x97ad4c0/V- RooGaussian::sig2 = 1 [Auto,Dirty] 
      0x962d060/V- RooRealVar::x = 5
      0x95545a0/V- RooRealVar::mean = 5
      0x90d3920/V- RooRealVar::sigma2 = 1

Print tree to file

In [10]:
model.printCompactTree("", "rf206_asciitree.txt")

Draw composite tree graphically

Print GraphViz DOT file with representation of tree

In [11]:
model.graphVizTree("rf206_model.dot")