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ntuple_analysebtag.py
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ntuple_analysebtag.py
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#!/usr/bin/env python
# from __future__ import print_function
from bin.NtupleDataFormat import Ntuple
from ROOT import TH1D, TFile, TLorentzVector, TProfile, TProfile2D
import sys
import optparse
import itertools
from array import array
import math
def findHadronFlav(genparts, jet, dR):
isbHad = False
iscHad = False
for g in genparts: # check if there exists one b-hadron
gVec = ROOT.TLorentzVector()
gVec.SetPtEtaPhiM(g.pt(), g.eta(), g.phi(), g.mass())
if jet.DeltaR(gVec) >= dR:
continue
if 500 < abs(g.pid()) < 600 or 5000 < abs(g.pid()) < 6000:
isbHad = True
break
if 400 < abs(g.pid()) < 500 or 4000 < abs(g.pid()) < 5000:
iscHad = True
if isbHad:
return 5
if iscHad:
return 4
return 1 # any not 4 or 5 case
def findPartonFlav(genparts, jet, dR):
"""Return the PDG ID of gen particles"""
isbPar = False
iscPar = False
for g in genparts:
gVec = ROOT.TLorentzVector()
gVec.SetPtEtaPhiM(g.pt(), g.eta(), g.phi(), g.mass())
if jet.DeltaR(gVec) >= dR:
continue
if abs(g.pid()) == 5:
isbPar = True
break
if abs(g.pid()) == 4:
iscPar = True
if isbPar:
return 5
if iscPar:
return 4
return 1
def doSum(objs, ptCut, etaCut):
s = 0
for j in objs:
if j.pt() > ptCut and abs(j.eta()) < etaCut:
s += j.pt()
return s
def doCount(objs, ptCut, etaCut):
cnt = 0
for j in objs:
if j.pt() > ptCut and abs(j.eta()) < etaCut:
cnt += 1
return cnt
def create2dHist(varname, params, title):
if "to_pt" in varname and "tagRate" in varname:
h = ROOT.TProfile(varname, title, 50,
params["plotPtRange"][0], params["plotPtRange"][1])
h.GetXaxis().SetTitle("jet p_{T} [GeV]")
h.GetYaxis().SetTitle("tagging efficiency")
if "to_eta" in varname and "tagRate" in varname:
h = ROOT.TProfile(varname, title, 50,
params["plotEtaRange"][0], params["plotEtaRange"][1])
h.GetXaxis().SetTitle("jet #eta")
h.GetYaxis().SetTitle("tagging efficiency")
h.Sumw2()
return h
def create2Dmap(varname, params, title, dumptcl):
# use the slices to build a list of bin edges
ptbins = [item[0] for item in params["ptSlices"]]
etabins = [item[0] for item in params["etaSlices2D"]]
ptbins.append(params["ptSlices"][-1][1])
etabins.append(params["etaSlices2D"][-1][1])
# set more realistic caps
if not dumptcl:
if ptbins[-1] > 5e4:
ptbins[-1] = ptbins[-2]*2. # probably somewhere in 200 -- 4000?
if etabins[-1] > 5e4:
etabins[-1] = 5.
ptbinsext = []
for iedge in range(0, len(ptbins)-1):
# print "ptbins"+str(ptbins)
binwidth = ptbins[iedge+1]-ptbins[iedge]
if ptbins[iedge+1] >= 9e4:
ptbinsext.append(ptbins[iedge])
continue # don't subdivide the overflow bin
nsplits = params["sliceSplit"]
if ptbins[iedge+1] >= 150 or ptbins[iedge] == 100:
nsplits = 2
for j in range(0, nsplits): # 0, 1, 2 if sliceSplit = 3
# low, low+0*width/3, low+width/3, low+2*width/3
ptbinsext.append(ptbins[iedge] + int(j*binwidth/nsplits))
ptbinsext.append(ptbins[-1])
# print ptbinsext
etabinsext = []
for iedge in range(0, len(etabins)-1):
# print "etabins"+str(etabins)
binwidth = etabins[iedge+1]-etabins[iedge]
if etabins[iedge+1] >= 9e4:
etabinsext.append(etabins[iedge])
continue # don't subdivide the overflow bin
nsplits = params["sliceSplit"]
if 'electron' in varname and etabins[iedge] == 1.5:
nsplits = 7
for j in range(0, nsplits): # 0, 1, 2 if sliceSplit = 3
# low, low+0*width/3, low+width/3, low+2*width/3
etabinsext.append(etabins[iedge] + j*binwidth/nsplits)
etabinsext.append(etabins[-1])
# print etabinsext
# arrays for ROOT
xbins = array('d', ptbinsext)
ybins = array('d', etabinsext)
if "efficiency" in varname:
h = TProfile2D(varname, title, len(xbins) -
1, xbins, len(ybins)-1, ybins)
h.GetXaxis().SetTitle("jet p_{T} [GeV]")
h.GetYaxis().SetTitle("jet #eta")
h.Sumw2()
return h
def main():
usage = 'usage: %prog [options]'
parser = optparse.OptionParser(usage)
parser.add_option('-i', '--inFile',
dest='inFile',
# /eos/cms/store/group/upgrade/RTB/DelphesFlat_343pre01
help='input file [%default]',
default='/eos/cms/store/group/upgrade/RTB/FullsimFlat_110X/TT_TuneCP5_14TeV_200PU.root',
type='string')
parser.add_option('-o', '--outFile',
dest='outFile',
help='output file [%default]',
default='histo_full/val_btag.root',
type='string')
parser.add_option('-p', '--physObj',
dest='physobject',
help='object to analyze [%default]',
default='jetpuppi',
type='string')
parser.add_option('--maxEvents',
dest='maxEvts',
help='max number of events [%default]',
default=10000,
type=int)
parser.add_option('--dumptcl',
dest='dumptcl',
help='use more bins for making tcl file?',
action="store_true",
default=False)
(opt, args) = parser.parse_args()
inFile = opt.inFile
print(inFile)
ntuple = Ntuple(inFile)
maxEvents = opt.maxEvts
dumptcl = opt.dumptcl
tot_nevents = 0
outputF = ROOT.TFile(opt.outFile, "RECREATE")
obj = opt.physobject
params = {
"dR": 0.5,
"ptRatio": 2.0,
"ptMin": 20,
"etaSlices": [[0, 1.3], [1.3, 2.5], [2.5, 3], [3, 1e5]],
# up to eta = 4 for 2D maps
"etaSlices2D": [[0, 1.3], [1.3, 2.5], [2.5, 3], [3, 4]],
"ptSlices": [[20, 50], [50, 100], [100, 200], [200, 400], [400, 1e5]],
"sliceSplit": 1, # for 2D map, make N divisions of each slice
"plotPtRange": [0, 500],
"plotEtaRange": [-5, 5],
"ids": [
["looseID", 1, "#varepsilon(looseID)"], # btag >= 1
["mediumID", 3, "#varepsilon(mediumID)"],
["tightID", 7, "#varepsilon(tightID)"]],
"bitids": [
["looseID", (1 << 0), "#varepsilon(looseID)"], # btag & (1<<0)
["mediumID", (1 << 1), "#varepsilon(mediumID)"],
["tightID", (1 << 2), "#varepsilon(tightID)"]]
}
## create histo#
hists = {}
for cut in ["nocut"]+params["etaSlices"]:
hnames = ["btagRate_to_pt", "cMistagRate_to_pt",
"lightMistagRate_to_pt"]
for hname in hnames:
for quality in params["bitids"]:
newname = hname+"_"+quality[0]+"_" + \
str(cut[0]) + "to" + str(cut[1])
newname = ((newname.replace('.', 'p')).replace(
'100000p0', 'Inf')).replace('_ntoo', '')
hists[obj+"_" +
newname] = create2dHist(obj+"_"+newname, params, quality[2])
for cut in ["nocut"]+params["ptSlices"]:
hnames = ["btagRate_to_eta", "cMistagRate_to_eta",
"lightMistagRate_to_eta"]
for hname in hnames:
for quality in params["bitids"]:
newname = hname+"_"+quality[0]+"_" + \
str(cut[0]) + "to" + str(cut[1])
newname = ((newname.replace('.', 'p')).replace(
'100000p0', 'Inf')).replace('_ntoo', '')
hists[obj+"_" +
newname] = create2dHist(obj+"_"+newname, params, quality[2])
hnames2D = ["btagRate_efficiency2D",
"cMistagRate_efficiency2D", "lightMistagRate_efficiency2D"]
for hname in hnames2D:
for quality in params["ids"]:
newname = hname+"_"+quality[0]
hists[obj+"_"+newname] = create2Dmap(
obj+"_"+newname, params, quality[2], dumptcl)
# study
for event in ntuple:
if maxEvents > 0 and event.entry() >= maxEvents:
break
if (tot_nevents % 100) == 0: # 1000
print '... processed {} events ...'.format(event.entry()+1)
tot_nevents += 1
genparts = event.genparticles()
jets = event.jetspuppi()
for p in jets:
if p.pt() < params['ptMin']:
continue
pVec = ROOT.TLorentzVector()
pVec.SetPtEtaPhiM(p.pt(), p.eta(), p.phi(), p.mass())
jetParFlav = findPartonFlav(genparts, pVec, params['dR'])
if jetParFlav == 5:
for quality in params["bitids"]:
isTagged = int(bool(p.btag() & quality[1]))
hists[obj+"_btagRate_to_eta_" +
quality[0]].Fill(p.eta(), isTagged)
hists[obj+"_btagRate_to_pt_" +
quality[0]].Fill(p.pt(), isTagged)
hists[obj+"_btagRate_efficiency2D_" +
quality[0]].Fill(p.pt(), p.eta(), isTagged)
for cut in params["ptSlices"]:
cutname = str(cut[0]) + "to" + str(cut[1])
cutname = (cutname.replace('.', 'p')
).replace('100000p0', 'Inf')
if cut[0] <= p.pt() < cut[1]:
for quality in params["bitids"]:
isTagged = int(bool(p.btag() & quality[1]))
hists[obj+"_btagRate_to_eta_"+quality[0] +
"_" + cutname].Fill(p.eta(), isTagged)
for cut in params["etaSlices"]:
cutname = str(cut[0]) + "to" + str(cut[1])
cutname = (cutname.replace('.', 'p')
).replace('100000p0', 'Inf')
if cut[0] < abs(p.eta()) <= cut[1]:
for quality in params["bitids"]:
isTagged = int(bool(p.btag() & quality[1]))
hists[obj+"_btagRate_to_pt_"+quality[0] +
"_" + cutname].Fill(p.pt(), isTagged)
elif jetParFlav == 4:
for quality in params["bitids"]:
isTagged = int(bool(p.btag() & quality[1]))
hists[obj+"_cMistagRate_to_eta_" +
quality[0]].Fill(p.eta(), isTagged)
hists[obj+"_cMistagRate_to_pt_" +
quality[0]].Fill(p.pt(), isTagged)
hists[obj+"_cMistagRate_efficiency2D_" +
quality[0]].Fill(p.pt(), p.eta(), isTagged)
for cut in params["ptSlices"]:
cutname = str(cut[0]) + "to" + str(cut[1])
cutname = (cutname.replace('.', 'p')
).replace('100000p0', 'Inf')
if cut[0] <= p.pt() < cut[1]:
for quality in params["bitids"]:
isTagged = int(bool(p.btag() & quality[1]))
hists[obj+"_cMistagRate_to_eta_"+quality[0] +
"_" + cutname].Fill(p.eta(), isTagged)
for cut in params["etaSlices"]:
cutname = str(cut[0]) + "to" + str(cut[1])
cutname = (cutname.replace('.', 'p')
).replace('100000p0', 'Inf')
if cut[0] < abs(p.eta()) <= cut[1]:
for quality in params["bitids"]:
isTagged = int(bool(p.btag() & quality[1]))
hists[obj+"_cMistagRate_to_pt_"+quality[0] +
"_" + cutname].Fill(p.pt(), isTagged)
else:
for quality in params["bitids"]:
isTagged = int(bool(p.btag() & quality[1]))
hists[obj+"_lightMistagRate_to_eta_" +
quality[0]].Fill(p.eta(), isTagged)
hists[obj+"_lightMistagRate_to_pt_" +
quality[0]].Fill(p.pt(), isTagged)
hists[obj+"_lightMistagRate_efficiency2D_" +
quality[0]].Fill(p.pt(), p.eta(), isTagged)
for cut in params["ptSlices"]:
cutname = str(cut[0]) + "to" + str(cut[1])
cutname = (cutname.replace('.', 'p')
).replace('100000p0', 'Inf')
if cut[0] <= p.pt() < cut[1]:
for quality in params["bitids"]:
isTagged = int(bool(p.btag() & quality[1]))
hists[obj+"_lightMistagRate_to_eta_"+quality[0] +
"_" + cutname].Fill(p.eta(), isTagged)
for cut in params["etaSlices"]:
cutname = str(cut[0]) + "to" + str(cut[1])
cutname = (cutname.replace('.', 'p')
).replace('100000p0', 'Inf')
if cut[0] < abs(p.eta()) <= cut[1]:
for quality in params["bitids"]:
isTagged = int(bool(p.btag() & quality[1]))
hists[obj+"_lightMistagRate_to_pt_"+quality[0] +
"_" + cutname].Fill(p.pt(), isTagged)
outputF.cd()
for h in hists.keys():
hists[h].Write()
if __name__ == "__main__":
main()