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ntuple_analyser.py
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ntuple_analyser.py
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#!/usr/bin/env python
from ROOT import TH1D, TFile, TLorentzVector, TProfile, TProfile2D, TVector2, TVector3
#from __future__ import print_function
from bin.NtupleDataFormat import Ntuple
import sys
import optparse
import itertools
import math
from array import array
# The purpose of this file is to demonstrate mainly the objects
# that are in the HGCalNtuple
pdgid = {
"photon": 22,
"electron": 11,
"muon": 13,
"elec_photon": 11,
}
def createHist(opt, varname, params):
if "pt" in varname and "resolution" not in varname:
h = TH1D(varname, "", 50, params["plotPtRange"][0], params["plotPtRange"][1])
h.GetXaxis().SetTitle("p_{T} [GeV]")
h.GetYaxis().SetTitle("N")
elif "eta" in varname and "resolution" not in varname:
h = TH1D(varname, "", 50, params["plotEtaRange"][0], params["plotEtaRange"][1])
h.GetXaxis().SetTitle("#eta")
h.GetYaxis().SetTitle("N")
elif "phi" in varname:
h = TH1D(varname, "", 50, params["plotPhiRange"][0], params["plotPhiRange"][1])
h.GetXaxis().SetTitle("#phi")
h.GetYaxis().SetTitle("N")
elif "mass" in varname:
h = TH1D(varname, "", 50, params["plotMassRange"][0], params["plotMassRange"][1])
h.GetXaxis().SetTitle("mass [GeV]")
h.GetYaxis().SetTitle("N")
elif "idpass" in varname:
h = TH1D(varname, "", 20, 0, 20)
h.GetXaxis().SetTitle("ID bit value")
h.GetYaxis().SetTitle("N")
elif "isopass" in varname:
h = TH1D(varname, "", 20, 0, 20)
h.GetXaxis().SetTitle("isolation bit value")
h.GetYaxis().SetTitle("N")
elif "resolution" in varname:
h = TH1D(varname, "", 100,params["plotResoRange"][0], params["plotResoRange"][1])
h.GetXaxis().SetTitle("p_{T}^{reco} / p_{T}^{gen}")
h.GetYaxis().SetTitle("N")
elif "multi" in varname:
if "full" in opt.outFile:
h = TH1D(varname, "", params["plotNObjRange_Full"][1], params["plotNObjRange_Full"][0], params["plotNObjRange_Full"][1])
else:
h = TH1D(varname, "", params["plotNObjRange_Delp"][1], params["plotNObjRange_Delp"][0], params["plotNObjRange_Delp"][1])
h.GetXaxis().SetTitle("multiplicity")
h.GetYaxis().SetTitle("Events")
h.Sumw2()
return h
def create2dHist(varname, params, title):
if "to_pt" in varname:
h = TProfile(varname, title, 50, params["plotPtRange"][0], params["plotPtRange"][1])
h.GetXaxis().SetTitle("gen p_{T} [GeV]")
if "response" in varname:
title = title.replace(")*#varepsilon(#","+")
title = title.replace("#varepsilon","response")
h.GetYaxis().SetTitle("Reco_pt/Gen_pt")
elif 'efficiency' in varname:
h.GetYaxis().SetTitle("gen object efficiency")
elif 'Effi' in varname:
h.GetXaxis().SetTitle("reco pt [GeV]")
h.GetYaxis().SetTitle("object efficiency")
elif 'nonprompt' in varname:
h.GetYaxis().SetTitle("gen object nonprompt efficiency")
elif 'fakerate' in varname:
title = title.replace(")*#varepsilon(#","+")
title = title.replace("#varepsilon","fakerate")
h.GetXaxis().SetTitle("reco p_{T} [GeV]")
h.GetYaxis().SetTitle("mistag rate")
elif "tagRate" in varname:
if TauTagStudy:
h.GetXaxis().SetTitle("#tau_{vis} p_{T} [GeV]")
else:
h.GetXaxis().SetTitle("jet p_{T} [GeV]")
h.GetYaxis().SetTitle("tagging efficiency")
elif "to_eta" in varname:
h = TProfile(varname, title, 50, params["plotEtaRange"][0], params["plotEtaRange"][1])
h.GetXaxis().SetTitle("gen #eta [GeV]")
if "response" in varname:
title = title.replace(")*#varepsilon(#","+")
title = title.replace("#varepsilon","response")
h.GetYaxis().SetTitle("Reco_pt/Gen_pt")
elif 'efficiency' in varname:
h.GetYaxis().SetTitle("gen object efficiency")
elif 'Effi' in varname:
h.GetXaxis().SetTitle("reco #eta [GeV]")
h.GetYaxis().SetTitle("object efficiency")
elif 'nonprompt' in varname:
h.GetYaxis().SetTitle("gen object nonprompt efficiency")
elif 'fakerate' in varname:
title = title.replace(")*#varepsilon(#","+")
title = title.replace("#varepsilon","fakerate")
h.GetXaxis().SetTitle("reco #eta [GeV]")
h.GetYaxis().SetTitle("mistag rate")
elif "tagRate" in varname:
if TauTagStudy:
h.GetXaxis().SetTitle("#tau_{vis} #eta")
else:
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["etaSlices"]]
ptbins.append(params["ptSlices"][-1][1])
etabins.append(params["etaSlices"][-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
ptbinsext.append(ptbins[iedge] + int(j*binwidth/nsplits)) # low, low+0*width/3, low+width/3, low+2*width/3
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
etabinsext.append(etabins[iedge] + j*binwidth/nsplits) # low, low+0*width/3, low+width/3, low+2*width/3
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("gen p_{T} [GeV]")
h.GetYaxis().SetTitle("gen #eta")
if "fake" in varname:
title = title.replace(")*#varepsilon(#","+")
title = title.replace("#varepsilon","fakerate")
h = TProfile2D(varname, title, len(xbins)-1, xbins, len(ybins)-1, ybins)
h.GetXaxis().SetTitle("reco p_{T} [GeV]")
h.GetYaxis().SetTitle("reco #eta")
if "tagRate_2D" 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 findHadronFlav(genparts, jet, dR):
isbHad = False
iscHad = False
for g in genparts: # check if there exists one b-hadron
gVec = 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):
isbPar = False
iscPar = False
for g in genparts: # check if there exists one b-hadron
gVec = 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 # any not 4 or 5 case
def runBtagStudy(ntuple, maxEvents, outfileName, dumptcl):
tot_nevents = 0
outputF = TFile(outfileName, "RECREATE")
obj = "jetpuppi"
#dumptcl = False
params = {
"dR": 0.5,
"ptMin": 20,
"etaSlices": [[0, 1.5], [1.5, 2.5], [2.5, 4], [4, 1e5] ], ## use 1e5 as "Inf"
"ptSlices": [[20, 50], [50, 100], [100, 500], [500, 1e5] ],
"sliceSplit": 3, # 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_2D", "cMistagRate_2D", "lightMistagRate_2D"]
for hname in hnames2D:
for quality in params["bitids"]:
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 %1000) == 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 = TLorentzVector()
pVec.SetPtEtaPhiM(p.pt(), p.eta(), p.phi(), p.mass())
jetParFlav = findPartonFlav(genparts, pVec, params['dR'])
#print "pt ", p.pt(), " eta ", p.eta(), " HadFlav ", jetHadFlav, " btag ", p.btag()
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_2D_" + 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_2D_" + 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_2D_" + 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()
outputF.Close()
def findZ(genparts, ptCut, etaCut):
v= TVector2(0, 0)
for g in genparts:
if abs(g.pid())==23:
d1 = g.d1()
if d1<0:
continue
gd1 = genparts[d1]
if ( abs(gd1.pid())==11 or abs(gd1.pid()==13) ) and g.pt() > ptCut and abs(g.eta()) < etaCut :
v.SetMagPhi(g.pt(),g.phi())
return v
return v
def findRecoZ(leptons, ptCut, etaCut, idCut, isoCut):
if leptons[0].charge()*leptons[1].charge() > 0:
return TVector3(0,0,0)
v1= TVector3(0,0,0)
v2= TVector3(0,0,0)
if (leptons[0].pt() > ptCut and abs(leptons[0].eta()) <etaCut and leptons[0].idpass() > idCut and leptons[0].isopass() > isoCut
and leptons[1].pt() > ptCut and abs(leptons[1].eta()) <etaCut and leptons[1].idpass() > idCut and leptons[1].isopass() > isoCut) :
v1.SetPtEtaPhi(leptons[0].pt(), leptons[0].eta(), leptons[0].phi())
v2.SetPtEtaPhi(leptons[1].pt(), leptons[1].eta(), leptons[1].phi())
return v1+v2
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 createMetHist(varname, xTitle, nBinsX, xMin, xMax):
h = TH1D(varname, "", nBinsX, xMin, xMax)
h.GetXaxis().SetTitle(xTitle)
h.GetYaxis().SetTitle("Events")
return h
def runMETStudy(ntuple, maxEvents, outfileName, dumptcl):
tot_nevents = 0
outputF = TFile(outfileName, "RECREATE")
## create histo
metHists = {}
metHists['genht_pt30_eta5'] = createMetHist('genht_pt30_eta5', "H_{T} gen [GeV]", 50, 0, 500)
metHists['npuVtx'] = createMetHist('npuVtx', "npuVertices", 40, 100, 300)
metHists['z_pt'] = createMetHist('z_pt', "p_{T}(Z) [GeV]", 40, 0, 150)
metHists['genz_pt'] = createMetHist('genz_pt', "p_{T}(gen Z) [GeV]", 40, 0, 150)
metHists['met'] = createMetHist('met', "p_{T,miss} [GeV]", 40, 0, 150)
metHists['met_reco10'] = createMetHist('met_reco10', "p_{T,miss} from puppi jets of 10 GeV [GeV]", 40, 0, 150)
metHists['met_reco20'] = createMetHist('met_reco20', "p_{T,miss} from puppi jets of 20 GeV [GeV]", 40, 0, 150)
metHists['met_reco30'] = createMetHist('met_reco30', "p_{T,miss} from puppi jets of 30 GeV [GeV]", 40, 0, 150)
metHists['met_recoid10'] = createMetHist('met_recoid10', "p_{T,miss} from puppi jets w/ ID of 10 GeV [GeV]", 40, 0, 150)
metHists['met_recoid20'] = createMetHist('met_recoid20', "p_{T,miss} from puppi jets w/ ID of 20 GeV [GeV]", 40, 0, 150)
metHists['met_recoid30'] = createMetHist('met_recoid30', "p_{T,miss} from puppi jets w/ ID of 30 GeV [GeV]", 40, 0, 150)
metHists['met_p'] = createMetHist('met_p', "parallel p_{T,miss} [GeV]", 40, 0, 150)
metHists['met_t'] = createMetHist('met_t', "transverse p_{T,miss} [GeV]", 40, 0, 150)
metHists['u_p'] = createMetHist('u_p', "u_{p} [GeV]", 40, 0, 150)
metHists['u_t'] = createMetHist('u_t', "u_{t} [GeV]", 40, 0, 150)
twodvarList=['genz_pt','genht_pt30_eta5','npuVtx']
varList = ['z_pt', 'met', 'met_p', 'met_t', 'u_p', 'u_t', 'met_reco10', 'met_reco20', 'met_reco30', 'met_recoid10', 'met_recoid20', 'met_recoid30']
varAllList = varList +twodvarList
for v in varList:
for twodv in twodvarList:
metHists[v+'_VS_'+twodv] = TProfile(v+'_VS_'+twodv, "", metHists[twodv].GetNbinsX(), metHists[twodv].GetXaxis().GetBinLowEdge(1), metHists[twodv].GetXaxis().GetBinUpEdge(metHists[twodv].GetNbinsX()), "S")
metHists[v+'_VS_'+twodv].GetXaxis().SetTitle(metHists[twodv].GetXaxis().GetTitle())
metHists[v+'_VS_'+twodv].GetYaxis().SetTitle(metHists[v].GetXaxis().GetTitle())
## study
for event in ntuple:
if maxEvents > 0 and event.entry() >= maxEvents:
break
if (tot_nevents %1000) == 0 :
print '... processed {} events ...'.format(event.entry()+1)
tot_nevents += 1
genparts = event.genparticles()
genjets = event.genjets()
mets = event.metspuppi()
electrons = event.electrons()
muons = event.muons()
jets = event.jetspuppi()
recomet10x = 0
recomet10y = 0
recoidmet10x = 0
recoidmet10y = 0
recomet20x = 0
recomet20y = 0
recoidmet20x = 0
recoidmet20y = 0
recomet30x = 0
recomet30y = 0
recoidmet30x = 0
recoidmet30y = 0
for jet in jets:
if jet.pt() > 10 and abs(jet.eta()) < 5:
recomet10x = recomet10x - jet.pt()*math.cos(jet.phi())
recomet10y = recomet10y - jet.pt()*math.sin(jet.phi())
if jet.pt() > 20:
recomet20x = recomet20x - jet.pt()*math.cos(jet.phi())
recomet20y = recomet20y - jet.pt()*math.sin(jet.phi())
if jet.pt() > 30:
recomet30x = recomet30x - jet.pt()*math.cos(jet.phi())
recomet30y = recomet30y - jet.pt()*math.sin(jet.phi())
if jet.idpass() > 0:
recoidmet10x = recoidmet10x - jet.pt()*math.cos(jet.phi())
recoidmet10y = recoidmet10y - jet.pt()*math.sin(jet.phi())
if jet.pt() > 20:
recoidmet20x = recoidmet20x - jet.pt()*math.cos(jet.phi())
recoidmet20y = recoidmet20y - jet.pt()*math.sin(jet.phi())
if jet.pt() > 30:
recoidmet30x = recoidmet30x - jet.pt()*math.cos(jet.phi())
recoidmet30y = recoidmet30y - jet.pt()*math.sin(jet.phi())
recomet10 = math.sqrt(recomet10x**2 + recomet10y**2)
recoidmet10 = math.sqrt(recoidmet10x**2 + recoidmet10y**2)
recomet20 = math.sqrt(recomet20x**2 + recomet20y**2)
recoidmet20 = math.sqrt(recoidmet20x**2 + recoidmet20y**2)
recomet30 = math.sqrt(recomet30x**2 + recomet30y**2)
recoidmet30 = math.sqrt(recoidmet30x**2 + recoidmet30y**2)
if len(electrons)>1:
leptons = electrons
elif len(muons)>1:
leptons = muons
else:
continue
z3d = findRecoZ(leptons, 15., 2., 0, 0)
z = TVector2(0,0)
z.SetMagPhi(z3d.Pt(), z3d.Phi())
z_pt = z.Mod()
if not (z_pt>10.): continue
genz = findZ(genparts, 15., 2.)
genz_pt = genz.Mod()
if not (genz_pt>10.): continue
genht_pt30_eta5 = doSum(genjets, 30., 5.)
met_v = TVector2(0,0)
met_v.SetMagPhi(mets[0].pt(),mets[0].phi())
met = mets[0].pt()
met_p = met_v.Proj(z).Mod()
met_t = met_v.Norm(z).Mod()
u_p = (z+met_v).Proj(z).Mod()
u_t = (z+met_v).Norm(z).Mod()
genjet_size_pt30_eta5 = doCount(genjets, 30., 5.)
vtx_size = event.vtxSize()
npuVtx = event.npuVertices()
trueInt = event.trueInteractions()
var = {}
var['genht_pt30_eta5'] = genht_pt30_eta5
var['npuVtx'] = npuVtx
var['z_pt'] = z_pt
var['genz_pt'] = genz_pt
var['met'] = met
var['met_reco10'] = recomet10
var['met_recoid10'] = recoidmet10
var['met_reco20'] = recomet20
var['met_recoid20'] = recoidmet20
var['met_reco30'] = recomet30
var['met_recoid30'] = recoidmet30
var['met_p'] = met_p
var['met_t'] = met_t
var['u_p']= u_p
var['u_t']= u_t
for v in varAllList:
metHists[v].Fill(var[v])
for v in varList:
for twodv in twodvarList:
metHists[v+'_VS_'+twodv].Fill(var[twodv], var[v])
## write event level var hists
outputF.cd()
for h in metHists.keys():
metHists[h].Write()
for i in twodvarList:
up_over_qt=outputF.Get("u_p_VS_"+i).Clone()
up_over_qt.Divide(outputF.Get("z_pt_VS_"+i))
up_over_qt.Write("up_over_qt_VS_"+i)
ut=outputF.Get("met_t_VS_"+i).Clone()
ut_rms= TH1D("ut_rms_VS_"+i, "", metHists[i].GetNbinsX(), 0, metHists[i].GetXaxis().GetBinUpEdge(metHists[i].GetNbinsX()))
ut_rms.GetXaxis().SetTitle(metHists[i].GetXaxis().GetTitle())
ut_rms.GetYaxis().SetTitle("RMS u_{T}")
for imtt in range(1,ut.GetNbinsX()+1):
ut_rms.SetBinContent(imtt, ut.GetBinError(imtt)*math.sqrt(ut.GetBinEntries(imtt)))
ut_rms.Write()
up_plus_qt =outputF.Get("met_p_VS_"+i).Clone()
up_plus_qt_rms = TH1D("up_plus_qt_rms_VS_"+i, "", metHists[i].GetNbinsX(),0,metHists[i].GetXaxis().GetBinUpEdge(metHists[i].GetNbinsX()))
up_plus_qt_rms.GetXaxis().SetTitle(metHists[i].GetXaxis().GetTitle())
up_plus_qt_rms.GetYaxis().SetTitle("RMS u_{P}+q_{T}")
for imtt in range(1,up_plus_qt.GetNbinsX()+1):
up_plus_qt_rms.SetBinContent(imtt, up_plus_qt.GetBinError(imtt)*math.sqrt(up_plus_qt.GetBinEntries(imtt)))
up_plus_qt_rms.Write()
outputF.Close()
def nDaughters(gen):
"""Returns the number of daughters of a genparticle."""
return gen.d2() - gen.d1()
def finalDaughters(gen, daughters=None):
"""Returns the list of final daughters of a genparticle."""
if daughters is None:
daughters = []
for i in range(gen.d1(), gen.d2()+1):
daughter = genparts[i]
if nDaughters(daughter) == 0:
daughters.append(daughter)
else:
finalDaughters(daughter, daughters)
return daughters
def hadronic(tau):
"""Returns the given object if it is a hadronic tau."""
hadronic = True
for d in finalDaughters(tau):
if abs(d.pid()) in [11, 13]:
hadronic = False
if hadronic:
return tau
def hadronicTaus(ptmin, etamax):
"""Returns the given object if it is a hadronic tau."""
hadtaus=[]
for part in genparts:
pdgCode = abs(part.pid())
if pdgCode != 15: continue
if part.pt() < ptmin: continue
if abs(part.eta()) > etamax: continue
if part.d1() < 0: continue
if part.d2() < part.d1(): continue
badtau=False
for i in range(part.d1(), part.d2()+1):
daughter1 = genparts[i]
pdgCode = abs(daughter1.pid())
if pdgCode in [11, 13, 15]: badtau=True
elif pdgCode == 24:
if daughter1.d1() < 0: badtau=True
for j in range(daughter1.d1(), daughter1.d2()+1):
daughter2 = genparts[j]
pdgCode = abs(daughter2.pid())
if pdgCode in [11, 13]: badtau=True
if not badtau:
hadtaus.append(part)
return hadtaus
def fourmomentum(gen):
"""Returns the four-momentum representation of a particle."""
'''
Px = gen.pt()*math.cos(gen.phi())
Py = gen.pt()*math.sin(gen.phi())
Pz = gen.pt()*math.sinh(gen.eta())
M = gen.mass()
c = 1
P = math.sqrt(Px**2 + Py**2 + Pz**2)
E = math.sqrt(P**2*c**2 + M**2*c**4)
pVec = TLorentzVector()
pVec.SetPxPyPzE(Px, Py, Pz, E)
return pVec
'''
pVec = TLorentzVector()
pVec.SetPtEtaPhiM(gen.pt(), gen.eta(), gen.phi(), gen.mass())
return pVec
def visibleP4(gen):
"""Returns the four-momentum of the visible parts of tau objects."""
daughter = finalDaughters(gen)
taumomentum = TLorentzVector()
for d in daughter:
if abs(d.pid()) not in [12, 14, 16]:
taumomentum += fourmomentum(d)
return taumomentum
def Momentum(gen):
"""Returns the four-momentum of the particle"""
momentum = TLorentzVector()
momentum.SetPtEtaPhiM(gen.pt(), gen.eta(), gen.phi(), gen.mass())
return momentum
def filterDR(obj, collection):
"""Returns the given object filtered from the given collection."""
objVec = TLorentzVector()
objVec.SetPtEtaPhiM(obj.pt(), obj.eta(), obj.phi(), obj.mass())
for p in collection:
pVec = TLorentzVector()
pVec.SetPtEtaPhiM(p.pt(), p.eta(), p.phi(), p.mass())
if objVec.DeltaR(pVec) > 0.3:
return obj
def findJetFlavourPtEta(jet, genhadronictaus, genlight, genelectrons, genmuons, dR):
flav=-1
pt=9999
eta=9999
jVec = TLorentzVector()
jVec.SetPtEtaPhiM(jet.pt(), jet.eta(), jet.phi(), jet.mass())
for g in genhadronictaus: # check if there exists one b-hadron
if jVec.DeltaR(g) < dR:
flav=15
pt=g.Pt()
eta=g.Eta()
if flav==-1:
for g in genlight: # check if there exists one b-hadron
if jVec.DeltaR(g) < dR:
flav=1
pt=g.Pt()
eta=g.Eta()
if flav==-1:
for g in genelectrons: # check if there exists one b-hadron
if jVec.DeltaR(g) < dR:
flav=11
pt=g.Pt()
eta=g.Eta()
if flav==-1:
for g in genmuons: # check if there exists one b-hadron
if jVec.DeltaR(g) < dR:
flav=13
pt=g.Pt()
eta=g.Eta()
## pile-up jets will have light flavour
if flav==-1:
flav=1
pt=jet.pt()
eta=jet.eta()
return flav, pt, eta
def findTauTag(jet, taus, dR):
tag=0
jVec = TLorentzVector()
jVec.SetPtEtaPhiM(jet.pt(), jet.eta(), jet.phi(), jet.mass())
## find closest reco tau
drmin=dR
best_tau=None
for tau in taus: # check if there exists one b-hadron
tauVec = TLorentzVector()
tauVec.SetPtEtaPhiM(tau.pt(), tau.eta(), tau.phi(), tau.mass())
if jVec.DeltaR(tauVec) < drmin:
drmin=jVec.DeltaR(tauVec)
best_tau=tau
if best_tau is not None:
tag=best_tau.isopass()
return tag
def runTautagStudy(ntuple, maxEvents, outfileName, dumptcl):
"""Creates Tautagging histograms."""
tot_nevents = 0
outputF = TFile(outfileName, "RECREATE")
obj = "tau"
#dumptcl = False
params = {
"dR": 0.4,
"ptMin": 20,
"etaSlices": [[0, 1.5], [1.5, 3.0], [3.0, 4.0], [4.0, 1e5] ],
"ptSlices": [[20, 50], [50, 100], [100, 500], [500, 1e5] ],
"sliceSplit": 3,
"plotPtRange": [0, 500],
"plotEtaRange": [-5, 5],
"bitids": [
["looseID", (1 << 0), "#varepsilon(looseID)"],
["mediumID", (1 << 1), "#varepsilon(mediumID)"],
["tightID", (1 << 2), "#varepsilon(tightID)"],
]
}
## create histos
hists = {}
for cut in ["nocut"]+params["etaSlices"]:
hnames = ["tautagRate_to_pt",
"elecMistagRate_to_pt", "muonMistagRate_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 = ["tautagRate_to_eta",
"elecMistagRate_to_eta", "muonMistagRate_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 = ["tautagRate_efficiency2D",
"elecMistagRate_efficiency2D", "muonMistagRate_efficiency2D", "lightMistagRate_efficiency2D"]
for hname in hnames2D:
for quality in params["bitids"]:
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 % 1000) == 0:
print '... processed {} events ...'.format(event.entry()+1)
tot_nevents += 1
taus = [p for p in event.taus() if p.pt() > params["ptMin"]]
electrons = event.electrons()
muons = event.muons()
jets = event.jetspuppi()
#isolated_electrons = [p for p in electrons if p.pt() > params["ptMin"] and bool((p.isopass() & 1)) and bool(p.idpass() & 1)]
#isolated_muons= [p for p in muons if p.pt() > params["ptMin"] and (p.isopass() & 1) == 1 and (p.idpass() & 1) == 1]
#elec_filtered_taus = [filterDR(tau, isolated_electrons) for tau in taus if filterDR(tau, isolated_electrons) is not None]
#all_filtered_taus = [filterDR(tau, isolated_muons) for tau in elec_filtered_taus if filterDR(tau, isolated_muons) is not None]
#all_filtered_taus = elec_filtered_taus
filtered_taus = []
for tau in taus:
#print '--- tau ----'
#print tau.pt(), tau.eta(), tau.phi(), tau.mass()
mom_tau = TLorentzVector()
mom_tau.SetPtEtaPhiM(tau.pt(), tau.eta(), tau.phi(), tau.mass())
#print '--- electrons ----'
bad_tau=False
for p in electrons:
mom_lep = TLorentzVector()
mom_lep.SetPtEtaPhiM(p.pt(), p.eta(), p.phi(), p.mass())
#print ' ', p.pt(), p.eta(), p.phi(), p.mass(), mom_lep.DeltaR(mom_tau), bool((p.isopass() & 0)) and bool(p.idpass() & 0)
if p.pt() > params["ptMin"] and bool((p.isopass() & 1)) and bool(p.idpass() & 1) and mom_lep.DeltaR(mom_tau) < 0.4:
bad_tau=True
for p in muons:
mom_lep = TLorentzVector()
mom_lep.SetPtEtaPhiM(p.pt(), p.eta(), p.phi(), p.mass())
#print ' ', p.pt(), p.eta(), p.phi(), p.mass(), mom_lep.DeltaR(mom_tau), bool((p.isopass() & 0)) and bool(p.idpass() & 0)
if p.pt() > params["ptMin"] and bool((p.isopass() & 1)) and bool(p.idpass() & 1) and mom_lep.DeltaR(mom_tau) < 0.4:
bad_tau=True
if not bad_tau:
filtered_taus.append(tau)
#print taus
#print filtered_taus
global genparts
genparts = event.genparticles()
n=0
genelectrons = [Momentum(p) for p in genparts if abs(p.pid()) == 11 and p.pt() > params["ptMin"] and p.status()==1]
genmuons = [Momentum(p) for p in genparts if abs(p.pid()) == 13 and p.pt() > params["ptMin"] and p.status()==1]
#gentaus = [p for p in genparts if abs(p.pid()) == 15 and p.pt() > params["ptMin"]]
#gentaus = [p for p in genparts if abs(p.pid()) == 15 and p.pt() > params["ptMin"]]
#genhadronictaus = [visibleP4(hadronic(tau)) for tau in gentaus if hadronic(tau) != None and visibleP4(hadronic(tau)).Pt() > params["ptMin"]] # visible hadronic taus
#genhadronictaus = [visibleP4(hadronic(tau)) for tau in gentaus if hadronic(tau) != None ] # visible hadronic taus
gentaus = hadronicTaus(params["ptMin"], 4.0)
genhadronictaus = [visibleP4(tau) for tau in gentaus]
genlight = [Momentum(p) for p in genparts if p.pt() > params["ptMin"] and (abs(p.pid()) == 4 or abs(p.pid()) == 3 or abs(p.pid()) == 2 or abs(p.pid()) == 1)] # creating a list here for the pids makes code run slower
'''
print ' -- list of hadronic taus -- '
n=0
for p in genparts:
#print n, p.pid(), visibleP4(p).Pt(), visibleP4(p).Eta()
#print n, p.pid(), p.pt(), p.eta(), p.phi(), p.mass(), p.d1(), p.d2()
n+=1
n=0
for p in gentaus:
print n, p.pid(), visibleP4(p).Pt(), visibleP4(p).Eta()
#print n, p.pid(), p.pt(), p.eta(), p.phi(), p.mass(), p.d1(), p.d2()
n+=1
'''
'''(
def fillEfficiencyHistos(obj, gen_coll, reco_coll, params, histlabel):
for gen in gen_coll:
isTagged = dict()
for quality in params["bitids"]:
isTagged[quality[0]] = 0
#print 'gen: ', gen.Pt(), gen.Eta(), gen.Phi(), gen.M()
for tau in reco_coll:
#print ' tau ', tau.pt(), tau.eta(), tau.phi(), tau.mass(), tau.isopass(), quality[0], quality[1], '{0:03b}'.format((tau.isopass() & quality[1]))
tVec = TLorentzVector()
tVec.SetPtEtaPhiM(tau.pt(), tau.eta(), tau.phi(), tau.mass())
if tVec.DeltaR(gen) < params["dR"]:
for quality in params["bitids"]:
#print ' tau ', tau.pt(), tau.eta(), tau.phi(), tau.mass(), tau.isopass(), quality[0], quality[1], int(bool((tau.isopass() & quality[1]))), '{0:03b}'.format((tau.isopass() & quality[1]))
isTagged[quality[0]] = int(bool(tau.isopass() & quality[1]))
#print ' tau ', tau.pt(), tau.eta(), tau.phi(), tau.mass(), isTagged[quality[0]], tVec.DeltaR(gen)
for quality in params["bitids"]:
hists[obj+"_"+histlabel+"_to_eta_" +
quality[0]].Fill(gen.Eta(), isTagged[quality[0]])
hists[obj+"_"+histlabel+"_to_pt_" +
quality[0]].Fill(gen.Pt(), isTagged[quality[0]])
hists[obj+"_"+histlabel+"_efficiency2D_" +
quality[0]].Fill(gen.Pt(), gen.Eta(), isTagged[quality[0]])
for cut in params["ptSlices"]:
cutname = str(cut[0]) + "to" + str(cut[1])
cutname = (cutname.replace('.', 'p')
).replace('100000p0', 'Inf')
if cut[0] <= gen.Pt() < cut[1]:
for quality in params["bitids"]:
hists[obj+"_"+histlabel+"_to_eta_"+quality[0] +
"_" + cutname].Fill(gen.Eta(), isTagged[quality[0]])
for cut in params["etaSlices"]:
cutname = str(cut[0]) + "to" + str(cut[1])
cutname = (cutname.replace('.', 'p')
).replace('100000p0', 'Inf')
if cut[0] < abs(gen.Eta()) <= cut[1]:
for quality in params["bitids"]:
hists[obj+"_"+histlabel+"_to_pt_"+quality[0] +
"_" + cutname].Fill(gen.Pt(), isTagged[quality[0]])
taucoll = filtered_taus
#taucoll = taus
fillEfficiencyHistos(obj, genhadronictaus, taucoll, params, 'tautagRate')
fillEfficiencyHistos(obj, genelectrons, taucoll, params, 'elecMistagRate')
fillEfficiencyHistos(obj, genmuons, taucoll, params, 'muonMistagRate')
fillEfficiencyHistos(obj, genlight, taucoll, params, 'lightMistagRate')
'''
tau_coll = taus
#tau_coll = filtered_taus
### alternative definition based on jets
#print "--- new event ---"
for jet in jets:
### first find jet flavour
jet_flavour_pt_eta = findJetFlavourPtEta(jet, genhadronictaus, genlight, genelectrons, genmuons, 0.5)
jet_tautag = findTauTag(jet, tau_coll, 0.5)
jet_flavour = jet_flavour_pt_eta[0]
jet_genpt = jet_flavour_pt_eta[1]
jet_geneta = jet_flavour_pt_eta[2]
#if jet_flavour == 15:
# print 'jet ', jet.pt(), jet_genpt, jet.eta(), jet_geneta, jet_flavour, jet_tautag
isTagged = dict()
for quality in params["bitids"]:
isTagged[quality[0]] = int(bool(jet_tautag & quality[1]))
def fillTauHistos(obj, gen_pt, gen_eta, params, histlabel):
for quality in params["bitids"]:
hists[obj+"_"+histlabel+"_to_eta_" +
quality[0]].Fill(gen_eta, isTagged[quality[0]])
hists[obj+"_"+histlabel+"_to_pt_" +
quality[0]].Fill(gen_pt, isTagged[quality[0]])
hists[obj+"_"+histlabel+"_efficiency2D_" +
quality[0]].Fill(gen_pt, gen_eta, isTagged[quality[0]])
for cut in params["ptSlices"]:
cutname = str(cut[0]) + "to" + str(cut[1])
cutname = (cutname.replace('.', 'p')
).replace('100000p0', 'Inf')
if cut[0] <= gen_pt < cut[1]:
for quality in params["bitids"]:
hists[obj+"_"+histlabel+"_to_eta_"+quality[0] +
"_" + cutname].Fill(gen_eta, isTagged[quality[0]])
for cut in params["etaSlices"]:
cutname = str(cut[0]) + "to" + str(cut[1])
cutname = (cutname.replace('.', 'p')
).replace('100000p0', 'Inf')
if cut[0] < abs(gen_eta) <= cut[1]:
for quality in params["bitids"]:
hists[obj+"_"+histlabel+"_to_pt_"+quality[0] +
"_" + cutname].Fill(gen_pt, isTagged[quality[0]])
if jet_flavour == 15:
fillTauHistos(obj, jet_genpt, jet_geneta, params, 'tautagRate')
elif jet_flavour == 11:
fillTauHistos(obj, jet_genpt, jet_geneta, params, 'elecMistagRate')
elif jet_flavour == 13:
fillTauHistos(obj, jet_genpt, jet_geneta, params, 'muonMistagRate')
else:
fillTauHistos(obj, jet_genpt, jet_geneta, params, 'lightMistagRate')
outputF.cd()
for h in hists.keys():
hists[h].Write()
outputF.Close()