rf511_wsfactory_basic.py

## \ingroup tutorial_roofit_main

## \notebook -nodraw

## Organization and simultaneous fits: basic use of the 'object factory' associated with a

## workspace to rapidly build pdfs functions and their parameter components

##

## \macro_code

## \macro_output

##

## \date February 2018

## \authors Clemens Lange, Wouter Verkerke (C++ version)

import ROOT

compact = False

w = ROOT.RooWorkspace("w")

# Creating and adding basic pdfs

# ----------------------------------------------------------------

# Remake example pdf of tutorial rs502_wspacewrite.C:

#

# Basic pdf construction: ClassName.ObjectName(constructor arguments)

# Variable construction : VarName[x,xlo,xhi], VarName[xlo,xhi], VarName[x]

# P.d.f. addition : SUM.ObjectName(coef1*pdf1,...coefM*pdfM,pdfN)

#

if not compact:

# Use object factory to build pdf of tutorial rs502_wspacewrite

w.factory("Gaussian::sig1(x[-10,10],mean[5,0,10],0.5)")

w.factory("Gaussian::sig2(x,mean,1)")

w.factory("Chebychev::bkg(x,{a0[0.5,0.,1],a1[-0.2,0.,1.]})")

w.factory("SUM::sig(sig1frac[0.8,0.,1.]*sig1,sig2)")

w.factory("SUM::model(bkgfrac[0.5,0.,1.]*bkg,sig)")

else:

# Use object factory to build pdf of tutorial rs502_wspacewrite but

# - Contracted to a single line recursive expression,

# - Omitting explicit names for components that are not referred to explicitly later

w.factory(

"SUM::model(bkgfrac[0.5,0.,1.]*Chebychev::bkg(x[-10,10],{a0[0.5,0.,1],a1[-0.2,0.,1.]}), "

"SUM(sig1frac[0.8,0.,1.]*Gaussian(x,mean[5,0,10],0.5), Gaussian(x,mean,1)))"

)

# Advanced pdf constructor arguments

# ----------------------------------------------------------------

#

# P.d.f. constructor arguments may by any type of ROOT.RooAbsArg, also

#

# Double_t -. converted to ROOT.RooConst(...)

# {a,b,c} -. converted to ROOT.RooArgSet() or ROOT.RooArgList() depending on required ctor arg

# dataset name -. converted to ROOT.RooAbsData reference for any dataset residing in the workspace

# enum -. Any enum label that belongs to an enum defined in the (base)

# class

# Make a dummy dataset pdf 'model' and import it in the workspace

data = w["model"].generate({w["x"]}, 1000)

# Cannot call 'import' directly because this is a python keyword:

w.Import(data, Rename="data")

# Construct a KEYS pdf passing a dataset name and an enum type defining the

# mirroring strategy

# w.factory("KeysPdf::k(x,data,NoMirror,0.2)")

# Workaround for pyROOT

x = w["x"]

k = ROOT.RooKeysPdf("k", "k", x, data, ROOT.RooKeysPdf.NoMirror, 0.2)

w.Import(k, RenameAllNodes="workspace")

# Print workspace contents

w.Print()