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rf207_comptools.py File Reference

## Namespaces

namespace  rf207_comptools

## Detailed Description

'ADDITION AND CONVOLUTION' RooFit tutorial macro #207 Tools and utilities for manipulation of composite objects

import ROOT
# Set up composite pdf dataset
# --------------------------------------------------------
# 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)
sigma = ROOT.RooRealVar("sigma", "width of gaussians", 0.5)
sig = ROOT.RooGaussian("sig", "Signal component 1", x, mean, sigma)
# Build Chebychev polynomial p.d.f.
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
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("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
bkgfrac = ROOT.RooRealVar("bkgfrac", "fraction of background", 0.5, 0.0, 1.0)
model = ROOT.RooAddPdf("model", "g1+g2+a", [bkg, sig], [bkgfrac])
# Create dummy dataset that has more observables than the above pdf
y = ROOT.RooRealVar("y", "y", -10, 10)
data = ROOT.RooDataSet("data", "data", {x, y})
# Basic information requests
# ---------------------------------------------
# Get list of observables
# ---------------------------------------------
# Get list of observables of pdf in context of a dataset
#
# Observables are define each context as the variables
# shared between a model and a dataset. In self case
# that is the variable 'x'
model_obs = model.getObservables(data)
model_obs.Print("v")
# Get list of parameters
# -------------------------------------------
# Get list of parameters, list of observables
model_params = model.getParameters({x})
model_params.Print("v")
# Get list of parameters, a dataset
# (Gives identical results to operation above)
model_params2 = model.getParameters(data)
model_params2.Print()
# Get list of components
# -------------------------------------------
# Get list of component objects, top-level node
model_comps = model.getComponents()
model_comps.Print("v")
# Modifications to structure of composites
# -------------------------------------------
# Create a second Gaussian
sigma2 = ROOT.RooRealVar("sigma2", "width of gaussians", 1)
sig2 = ROOT.RooGaussian("sig2", "Signal component 1", x, mean, sigma2)
# Create a sum of the original Gaussian plus the second Gaussian
sig1frac = ROOT.RooRealVar("sig1frac", "fraction of component 1 in signal", 0.8, 0.0, 1.0)
sigsum = ROOT.RooAddPdf("sigsum", "sig+sig2", [sig, sig2], [sig1frac])
# Construct a customizer utility to customize model
cust = ROOT.RooCustomizer(model, "cust")
# Instruct the customizer to replace node 'sig' with node 'sigsum'
cust.replaceArg(sig, sigsum)
# Build a clone of the input pdf according to the above customization
# instructions. Each node that requires modified is clone so that the
# original pdf remained untouched. The name of each cloned node is that
# of the original node suffixed by the name of the customizer object
#
# The returned head node own all nodes that were cloned as part of
# the build process so when cust_clone is deleted so will all other
# nodes that were created in the process.
cust_clone = cust.build(ROOT.kTRUE)
# Print structure of clone of model with sig.sigsum replacement.
cust_clone.Print("t")
# The RooCustomizer has the be deleted first.
# Otherwise, it might happen that sig or sigsum are deleted first, in which
# case the internal TLists in the RooCustomizer will complain about deleted
# objects.
del cust
[#0] WARNING:InputArguments -- The parameter 'sigma' with range [-inf, inf] of the RooGaussian 'sig' exceeds the safe range of (0, inf). Advise to limit its range.
1) 0x78b5b20 RooRealVar:: x = 5 L(0 - 10) "x"
1) 0x2a54a30 RooRealVar:: a0 = 0.5 L(0 - 1) "a0"
2) 0x2849ea0 RooRealVar:: a1 = 0.2 L(0 - 1) "a1"
3) 0x2822f90 RooRealVar:: alpha = -1 C L(-INF - +INF) "alpha"
4) 0x13218e0 RooRealVar:: bkg1frac = 0.2 L(0 - 1) "fraction of component 1 in background"
5) 0x7f482d0 RooRealVar:: bkgfrac = 0.5 L(0 - 1) "fraction of background"
6) 0x7115f70 RooRealVar:: mean = 5 C L(-INF - +INF) "mean of gaussians"
7) 0x761b480 RooRealVar:: sigma = 0.5 C L(-INF - +INF) "width of gaussians"
RooArgSet::parameters = (a0,a1,alpha,bkg1frac,bkgfrac,mean,sigma)
1) 0x7f49fe0 RooAddPdf:: model[ bkgfrac * bkg + [%] * sig ] = 0.582695/1 "g1+g2+a"
2) 0x7f41680 RooAddPdf:: bkg[ bkg1frac * bkg1 + [%] * bkg2 ] = 0.16539/1 "Signal"
3) 0x7e6baa0 RooChebychev:: bkg1[ x=x coefficients=(a0,a1) ] = 0.8 "Background 1"
4) 0x7e958f0 RooExponential:: bkg2[ x=x c=alpha ] = 0.00673795 "Background 2"
5) 0x79e4e00 RooGaussian:: sig[ x=x mean=mean sigma=sigma ] = 1 "Signal component 1"
[#0] WARNING:InputArguments -- The parameter 'sigma2' with range [-inf, inf] of the RooGaussian 'sig2' exceeds the safe range of (0, inf). Advise to limit its range.
[#1] INFO:ObjectHandling -- RooCustomizer::build(model): tree node sig will be replaced by sigsum
[#1] INFO:ObjectHandling -- RooCustomizer::build(model) Branch node RooAddPdf::model cloned: depends on a replaced parameter
[#1] INFO:ObjectHandling -- RooCustomizer::build(model) Branch node sig is already replaced
0x7e6baa0/V- RooChebychev::bkg1 = 0.8 [Auto,Dirty]
0x78b5b20/V- RooRealVar::x = 5
0x2a54a30/V- RooRealVar::a0 = 0.5
0x2849ea0/V- RooRealVar::a1 = 0.2
0x13218e0/V- RooRealVar::bkg1frac = 0.2
0x7e958f0/V- RooExponential::bkg2 = 0.00673795 [Auto,Dirty]
0x78b5b20/V- RooRealVar::x = 5
0x2822f90/V- RooRealVar::alpha = -1
0x7f482d0/V- RooRealVar::bkgfrac = 0.5