rf406_cattocatfuncs.py

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## \file
## \ingroup tutorial_roofit
## \notebook -nodraw
## Data and categories: demonstration of discrete-discrete (invertable) functions
##
## \macro_code
## \macro_output
##
## \date February 2018
## \authors Clemens Lange, Wouter Verkerke (C++ version)
 
import ROOT
 
 
# Construct two categories
# ----------------------------------------------
 
# Define a category with labels only
tagCat = ROOT.RooCategory("tagCat", "Tagging category")
tagCat.defineType("Lepton")
tagCat.defineType("Kaon")
tagCat.defineType("NetTagger-1")
tagCat.defineType("NetTagger-2")
tagCat.Print()
 
# Define a category with explicitly numbered states
b0flav = ROOT.RooCategory("b0flav", "B0 flavour eigenstate", {"B0": -1, "B0bar": 1})
b0flav.Print()
 
# Construct a dummy dataset with random values of tagCat and b0flav
x = ROOT.RooRealVar("x", "x", 0, 10)
p = ROOT.RooPolynomial("p", "p", x)
data = p.generate({x, b0flav, tagCat}, 10000)
 
# Create a cat -> cat mapping category
# ---------------------------------------------------------------------
 
# A RooMappedCategory is category.category mapping function based on string expression
# The constructor takes an input category an a default state name to which unassigned
# states are mapped
tcatType = ROOT.RooMappedCategory("tcatType", "tagCat type", tagCat, "Cut based")
 
# Enter fully specified state mappings
tcatType.map("Lepton", "Cut based")
tcatType.map("Kaon", "Cut based")
 
# Enter a wilcard expression mapping
tcatType.map("NetTagger*", "Neural Network")
 
# Make a table of the mapped category state multiplicit in data
mtable = data.table(tcatType)
mtable.Print("v")
 
# Create a cat X cat product category
# ----------------------------------------------------------------------
 
# A SUPER-category is 'product' of _lvalue_ categories. The state names of a super
# category is a composite of the state labels of the input categories
b0Xtcat = ROOT.RooSuperCategory("b0Xtcat", "b0flav X tagCat", {b0flav, tagCat})
 
# Make a table of the product category state multiplicity in data
stable = data.table(b0Xtcat)
stable.Print("v")
 
# Since the super category is an lvalue, is explicitly possible
b0Xtcat.setLabel("{B0bar;Lepton}")
 
# A MULTI-category is a 'product' of any category (function). The state names of a super
# category is a composite of the state labels of the input categories
b0Xttype = ROOT.RooMultiCategory("b0Xttype", "b0flav X tagType", {b0flav, tcatType})
 
# Make a table of the product category state multiplicity in data
xtable = data.table(b0Xttype)
xtable.Print("v")