Organization and simultaneous fits: basic use of the 'object factory' associated with a workspace to rapidly build pdfs functions and their parameter components
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 Tuesday, March 19, 2024 at 07:16 PM.
import ROOT
compact = False
w = ROOT.RooWorkspace("w")
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(coef1pdf1,...coefMpdfM,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)))"
)
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")
False
[#1] INFO:ObjectHandling -- RooWorkspace::import(w) importing dataset modelData [#1] INFO:ObjectHandling -- RooWorkSpace::import(w) changing name of dataset from modelData to 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")
False
[#1] INFO:ObjectHandling -- RooWorkspace::import(w) Resolving name conflict in workspace by changing name of imported node k to k_workspace [#1] INFO:ObjectHandling -- RooWorkspace::import(w) importing RooKeysPdf::k_workspace
Print workspace contents
w.Print()
RooWorkspace(w) w contents variables --------- (a0,a1,bkgfrac,mean,sig1frac,x) p.d.f.s ------- RooChebychev::bkg[ x=x coefList=(a0,a1) ] = 1 RooKeysPdf::k_workspace[ x=x ] = 0.0139016 RooAddPdf::model[ bkgfrac * bkg + [%] * sig ] = 0.5/1 RooAddPdf::sig[ sig1frac * sig1 + [%] * sig2 ] = 7.45331e-07/1 RooGaussian::sig1[ x=x mean=mean sigma=0.5 ] = 1.92875e-22 RooGaussian::sig2[ x=x mean=mean sigma=1 ] = 3.72665e-06 datasets -------- RooDataSet::data(x)