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rf509_wsinteractive.py
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rf509_wsinteractive.py
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# /
#
# 'ORGANIZATION AND SIMULTANEOUS FITS' ROOT.RooFit tutorial macro #509
#
# Easy CINT interactive access to workspace contents through a
# 'C++' namespace in CINT that maps the workspace contents in a typesafe way
#
# *********************************************************************************
# *** NB: ROOT.This macro exploits a feature native to CINT and _cannot_ be compiled ***
# *********************************************************************************
#
# 04/2009 - Wouter Verkerke
#
# /
import ROOT
def rf509_wsinteractive():
# C r e a t e a n d f i l l w o r k s p a c e
# ------------------------------------------------
# Create a workspace named 'w'
# With CINT w could exports its contents to
# a same-name C++ namespace in CINT 'namespace w'.
# but self does not work anymore in CLING.
# so self tutorial is an example on how to
# change the code
w = ROOT.RooWorkspace("w", ROOT.kTRUE)
# Fill workspace with p.d.f. and data in a separate function
fillWorkspace(w)
# Print workspace contents
w.Print()
# self does not work anymore with CLING
# use normal workspace functionality
# U s e w o r k s p a c e c o n t e n t s
# ----------------------------------------------
# Old syntax to use the name space prefix operator to access the workspace contents
#
#d = w.model.generate(w.x,1000)
#r = w.model.fitTo(*d)
# use normal workspace methods
model = w.pdf("model")
x = w.var("x")
d = model.generate(ROOT.RooArgSet(x), 1000)
r = model.fitTo(d)
# old syntax to access the variable x
# frame = w.x.frame()
frame = x.frame()
d.plotOn(frame)
# OLD syntax to ommit x.
# NB: ROOT.The 'w.' prefix can be omitted if namespace w is imported in local namespace
# in the usual C++ way
#
# using namespace w
# model.plotOn(frame)
# model.plotOn(frame, ROOT.RooFit.Components(bkg), ROOT.RooFit.LineStyle(ROOT.kDashed))
# correct syntax
bkg = w.pdf("bkg")
model.plotOn(frame)
ras_bkg = ROOT.RooArgSet(bkg)
model.plotOn(frame, ROOT.RooFit.Components(ras_bkg),
ROOT.RooFit.LineStyle(ROOT.kDashed))
# Draw the frame on the canvas
c = ROOT.TCanvas("rf509_wsinteractive", "rf509_wsinteractive", 600, 600)
ROOT.gPad.SetLeftMargin(0.15)
frame.GetYaxis().SetTitleOffset(1.4)
frame.Draw()
c.SaveAs("rf509_wsinteractive.png")
def fillWorkspace(w):
# C r e a t e p d f a n d f i l l w o r k s p a c e
# --------------------------------------------------------
# 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, 0, 10)
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)
# Build Chebychev polynomial p.d.f.
a0 = ROOT.RooRealVar("a0", "a0", 0.5, 0., 1.)
a1 = ROOT.RooRealVar("a1", "a1", -0.2, 0., 1.)
bkg = ROOT.RooChebychev("bkg", "Background", x, ROOT.RooArgList(a0, a1))
# 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))
# 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))
getattr(w, 'import')(model)
if __name__ == "__main__":
rf509_wsinteractive()