def makeBoostedJetPLots(self, sel, jets, uname):
maxJet = 1
binScaling = 1
plots = []
for i in range(maxJet):
plots.append(
Plot.make1D(f"{uname}_boostedjet{i+1}_pt",
jets[i].pt,
sel,
EqB(60, 170., 800.),
title=f"{utils.getCounter(i+1)} jet p_{{T}} [GeV]",
plotopts=utils.getOpts(uname)))
plots.append(
Plot.make1D(f"{uname}_boostedjet{i+1}_eta",
jets[i].eta,
sel,
EqB(50 // binScaling, -2.4, 2.4),
title=f"{utils.getCounter(i+1)} jet eta",
plotopts=utils.getOpts(uname)))
plots.append(
Plot.make1D(f"{uname}_boostedjet{i+1}_phi",
jets[i].phi,
sel,
EqB(50 // binScaling, -3.1416, 3.1416),
title=f"{utils.getCounter(i+1)} jet phi",
plotopts=utils.getOpts(uname)))
plots.append(
Plot.make1D(f"{uname}_boostedjet{i+1}_mass",
jets[i].phi,
sel,
EqB(50 // binScaling, -3.1416, 3.1416),
title=f"{utils.getCounter(i+1)} jet mass [GeV]",
plotopts=utils.getOpts(uname)))
return plots
def MakeEllipsesPLots(self, sel, bjets, lepton, wp, uname, suffix):
plots = []
binScaling = 1
for key in sel.keys():
tagger = key.replace(wp, "")
bjets_ = safeget(bjets, tagger, wp)
plots.append(
Plot.make1D(
"jj_M_{0}_{1}_hZA_lljj_{2}_mll_and_met_cut".format(
suffix, uname, key),
op.invariant_mass(bjets_[0].p4, bjets_[1].p4),
sel.get(key),
EqB(60 // binScaling, 0., 1000.),
title="invariant mass of two b-tagged jets wrt {0} Discriminator"
.format(suffix, key),
xTitle="mjj {0} {1} [GeV]".format(suffix, key),
plotopts=utils.getOpts(uname, **{"log-y": False})))
plots.append(
Plot.make1D(
"lljj_M_{0}_{1}_hZA_lljj_{2}_mll_and_met_cut".format(
suffix, uname, key), (lepton[0].p4 + lepton[1].p4 +
bjets_[0].p4 + bjets_[1].p4).M(),
sel.get(key),
EqB(60 // binScaling, 0., 1000.),
title=
"invariant mass of 2 leptons two b-tagged jets wrt {0} Discriminator"
.format(suffix, key),
xTitle="mlljj {0} {1} [GeV]".format(suffix, key),
plotopts=utils.getOpts(uname, **{"log-y": False})))
plots.append(
Plot.make2D(
"Mjj_vs_Mlljj_{0}_{1}_hZA_lljj_{2}_mll_and_met_cut".format(
suffix, uname,
key), (op.invariant_mass(bjets_[0].p4, bjets_[1].p4),
(lepton[0].p4 + lepton[1].p4 + bjets_[0].p4 +
bjets_[1].p4).M()),
sel.get(key), (EqB(60 // binScaling, 0.,
1000.), EqB(60 // binScaling, 0., 1000.)),
title="mlljj vs mjj invariant mass {0} wrt {1} Discriminator".
format(suffix, key),
plotopts=utils.getOpts(uname, **{"log-y": False})))
plots.append(
Plot.make1D(
"ll_M_{0}_{1}_hZA_lljj_{2}_mll_and_met_cut".format(
suffix, uname, key),
op.invariant_mass(lepton[0].p4, lepton[1].p4),
sel.get(key),
EqB(60 // binScaling, 70., 110.),
title=" dilepton invariant mass {0} wrt {1} Discriminator".
format(suffix, key),
xTitle="mll {0} {1} [GeV]".format(suffix, key),
plotopts=utils.getOpts(uname)))
return plots
def makeControlPlotsForZpic(self, sel, lepton, uname):
plots = []
for i in range(2):
if "mu" in uname:
flav = "Muon"
if "el" in uname:
flav = "Electron"
plots.append(
Plot.make1D(f"{uname}_lep{i+1}_pt",
lepton[i].pt,
sel,
EqB(60 // binScaling, 30., 530.),
title="%s p_{T} [GeV]" % flav,
plotopts=utils.getOpts(uname)))
plots.append(
Plot.make1D(f"{uname}_lep{i+1}_eta",
lepton[i].eta,
sel,
EqB(50 // binScaling, -2.4, 2.4),
title="%s eta" % flav,
plotopts=utils.getOpts(uname, **{"log-y": False})))
plots.append(
Plot.make1D(f"{uname}_lep{i+1}_phi",
lepton[i].phi,
sel,
EqB(50 // binScaling, -3.1416, 3.1416),
title="%s phi" % flav,
plotopts=utils.getOpts(uname, **{"log-y": False})))
plots.append(
Plot.make1D("{0}_mll".format(uname),
op.invariant_mass(lepton[0].p4, lepton[1].p4),
sel,
EqB(60, 70., 110.),
title="mll [GeV]",
plotopts=utils.getOpts(uname)))
plots.append(
Plot.make1D("{0}_llpT".format(uname),
(dilepton[0].p4 + dilepton[1].p4).Pt(),
sel,
EqB(60, 0., 450.),
title="dilepton P_{T} [GeV]",
plotopts=utils.getOpts(uname)))
# FIXME
#plots.append(Plot.make1D("{0}_nVX".format(uname),
# t.PV.npvs, sel,
# EqB(10, 0., 60.),
# title="Distrubtion of the number of the reconstructed vertices",
# xTitle="number of reconstructed vertices "))
#plots.append(Plot.make2D("{0}_Electron_dzdxy".format(uname),
# (lepton[0].dz ,lepton[0].dxy), sel,
# (EqB(10, 0., 2.),
# EqB(10, 0., 2.)) ,
# title="Electron in Barrel/EndCAP region" ))
return plots
def MakeExtraMETPlots(self, sel, lepton, met, uname, suffix):
binScaling = 1
plots = []
for key in sel.keys():
plots.append(
Plot.make1D("{0}_{1}_{2}_MET_pt".format(uname, key, suffix),
met.pt,
sel.get(key),
EqB(60 // binScaling, 0., 600.),
title="MET p_{T} [GeV]",
plotopts=utils.getOpts(uname, **{"log-y": False})))
plots.append(
Plot.make1D("{0}_{1}_{2}_MET_phi".format(uname, key, suffix),
met.phi,
sel.get(key),
EqB(60 // binScaling, -3.1416, 3.1416),
title="MET #phi",
plotopts=utils.getOpts(uname, **{"log-y": False})))
plots.append(
Plot.make1D("{0}_{1}_{2}_MET_eta".format(uname, key, suffix),
met.phi,
sel.get(key),
EqB(60 // binScaling, -2.4, 2.4),
title="MET #eta",
plotopts=utils.getOpts(uname, **{"log-y": False})))
for i in range(2):
plots.append(
Plot.make1D(
f"{uname}_{key}_{suffix}_MET_lep{i+1}_deltaPhi".format(
uname=uname, key=key, suffix=suffix),
op.Phi_mpi_pi(lepton[i].phi - met.phi),
sel.get(key),
EqB(60 // binScaling, -3.1416, 3.1416),
title="#Delta #phi (lepton, MET)",
plotopts=utils.getOpts(uname, **{"log-y": False})))
MT = op.sqrt(
2. * met.pt * lepton[i].p4.Pt() *
(1. - op.cos(op.Phi_mpi_pi(met.phi - lepton[i].p4.Phi()))))
plots.append(
Plot.make1D(f"{uname}_{key}_{suffix}_MET_MT_lep{i+1}".format(
uname=uname, key=key, suffix=suffix),
MT,
sel.get(key),
EqB(60 // binScaling, 0., 600.),
title="Lepton M_{T} [GeV]",
plotopts=utils.getOpts(uname, **{"log-y": False})))
return plots
def definePlots(self, t, noSel, sample=None, sampleCfg=None):
from bamboo.plots import Plot, CutFlowReport, SummedPlot
from bamboo.plots import EquidistantBinning as EqB
from bamboo import treefunctions as op
isMC = self.isMC(sample)
if isMC:
noSel = noSel.refine("mcWeight", weight=[t.genWeight])
noSel = noSel.refine(
"trig",
cut=op.OR(t.HLT.HIL3DoubleMu0,
t.HLT.HIEle20_Ele12_CaloIdL_TrackIdL_IsoVL_DZ))
plots = []
muons = op.select(t.Muon, lambda mu: mu.pt > 20.)
twoMuSel = noSel.refine("twoMuons", cut=[op.rng_len(muons) > 1])
plots.append(
Plot.make1D("dimu_M",
op.invariant_mass(muons[0].p4, muons[1].p4),
twoMuSel,
EqB(100, 20., 120.),
title="Dimuon invariant mass",
plotopts={
"show-overflow": False,
"legend-position": [0.2, 0.6, 0.5, 0.9]
}))
return plots
def makeResolvedBJetPlots(self, sel, bjets, wp, uname):
plots = []
binScaling = 1
for key in sel.keys():
tagger = key.replace(wp, "")
bjets_ = safeget(bjets, tagger, wp)
plots.append(
Plot.make1D("{0}_nBJets_{1}".format(uname, key),
op.rng_len(bjets_),
sel.get(key),
EqB(5, 2., 6.),
xTitle="Jets multiplicty {0}".format(key),
plotopts=utils.getOpts(uname)))
for i in range(1):
plots.append(
Plot.make1D(
f"{uname}_bjet{i+1}_pT_{key}",
bjets_[i].pt,
sel.get(key),
EqB(60, 0., 800.),
title=
f"{utils.getCounter(i+1)}-highest bjet pT {key} [GeV]",
plotopts=utils.getOpts(uname)))
plots.append(
Plot.make1D(
f"{uname}_bjet{i+1}_eta_{key}",
bjets_[i].eta,
sel.get(key),
EqB(50 // binScaling, -2.4, 2.4),
title=f"{utils.getCounter(i+1)}-highest bjet eta {key}",
plotopts=utils.getOpts(uname)))
plots.append(
Plot.make1D(
f"{uname}_bjet{i+1}_eta_{key}",
bjets_[i].phi,
sel.get(key),
EqB(50 // binScaling, -3.1416, 3.1416),
title=f"{utils.getCounter(i+1)}-highest bjet phi {key}",
plotopts=utils.getOpts(uname)))
return plots
def makeControlPlotsForFinalSel(self, sel, bjets, dilepton, uname):
plots = []
binScaling = 1
for key in sel.keys():
tagger = key.replace(wp, "")
bjets_ = safeget(bjets, tagger, wp)
plots.append(
Plot.make1D("{0}_TwoBtaggedJets_pT_{1}".format(uname, key),
(bjets_[0].p4 + bjets_[1].p4).Pt(),
sel.get(key),
EqB(60, 170., 800.),
title="di-bjet P_{T} [GeV]",
plotopts=utils.getOpts(uname)))
plots.append(
Plot.make1D("{0}_mlljj_btagged_{1}".format(uname, key),
(lepton[0].p4 + lepton[1].p4 + bjets_[0].p4 +
bjets_[1].p4).M(),
sel.get(key),
EqB(60, 170., 1000.),
title="mlljj [GeV]",
plotopts=utils.getOpts(uname)))
plots.append(
Plot.make1D("{0}_mjj_btagged_{1}".format(uname, key),
op.invariant_mass(bjets_[0].p4 + bjets_[1].p4),
sel.get(key),
EqB(60, 170., 800.),
title="mjj [GeV]",
plotopts=utils.getOpts(uname)))
plots.append(
Plot.make2D("{0}_mlljjvsmjj_btagged_{1}".format(uname, key),
(op.invariant_mass(bjets_[0].p4 + bjets_[1].p4),
(lepton[0].p4 + lepton[1].p4 + bjets_[0].p4 +
bjets_[1].p4).M()),
sel.get(key),
(EqB(60, 170., 1000.), EqB(60, 170., 1000.)),
title="mlljj vs mjj invariant mass [GeV]",
plotopts=utils.getOpts(uname)))
return plots
def makeBoostedJetPLots(self, sel, bjets, wp, uname):
maxJet = 1
binScaling = 1
plots = []
for key in sel.keys():
tagger = key.replace(wp, "")
bjets_ = safeget(bjets, tagger, wp)
for i in range(maxJet):
plots.append(
Plot.make1D(f"{uname}_boostedjet{i+1}_pt",
bjets_[i].pt,
sel,
EqB(60, 170., 800.),
title=f"{utils.getCounter(i+1)} jet p_{{T}} [GeV]",
plotopts=utils.getOpts(uname)))
plots.append(
Plot.make1D(f"{uname}_boostedjet{i+1}_eta",
bjets_[i].eta,
sel,
EqB(50 // binScaling, -2.4, 2.4),
title=f"{utils.getCounter(i+1)} jet eta",
plotopts=utils.getOpts(uname)))
plots.append(
Plot.make1D(f"{uname}_boostedjet{i+1}_phi",
bjets_[i].phi,
sel,
EqB(50 // binScaling, -3.1416, 3.1416),
title=f"{utils.getCounter(i+1)} jet phi",
plotopts=utils.getOpts(uname)))
plots.append(
Plot.make1D(f"{uname}_boostedjet{i+1}_mass",
bjets_[i].phi,
sel,
EqB(50 // binScaling, -3.1416, 3.1416),
title=f"{utils.getCounter(i+1)} jet mass [GeV]",
plotopts=utils.getOpts(uname)))
return plots
def MakeMETPlots(self, sel, corrmet, met, uname, suffix):
plots = []
binScaling = 1
for key in sel.keys():
plots.append(
Plot.make1D("met_pt_{0}_{1}_hZA_lljj_{2}".format(
suffix, uname, key),
met.pt,
sel.get(key),
EqB(60 // binScaling, 0., 600.),
title="MET p_{T} [GeV]",
plotopts=utils.getOpts(uname, **{"log-y": False})))
plots.append(
Plot.make1D("xycorrmet_pt_{0}_{1}_hZA_lljj_{2}".format(
suffix, uname, key),
corrmet.pt,
sel.get(key),
EqB(60 // binScaling, 0., 600.),
title="corrMET p_{T} [GeV]",
plotopts=utils.getOpts(uname, **{"log-y": False})))
return plots
def makeResolvedJetPlots(self, sel, jets, uname):
maxJet = 2
binScaling = 1
plots = []
for i in range(maxJet):
plots.append(
Plot.make1D(f"{uname}_jet{i+1}_pt",
jets[i].pt,
sel,
EqB(60 // binScaling, 30., 730. - max(4, i) * 100),
title=f"{utils.getCounter(i+1)} jet p_{{T}} [GeV]",
plotopts=utils.getOpts(uname)))
plots.append(
Plot.make1D(f"{uname}_jet{i+1}_eta",
jets[i].eta,
sel,
EqB(50 // binScaling, -2.4, 2.4),
title=f"{utils.getCounter(i+1)} jet eta",
plotopts=utils.getOpts(uname, **{"log-y": False})))
plots.append(
Plot.make1D(f"{uname}_jet{i+1}_phi",
jets[i].phi,
sel,
EqB(50 // binScaling, -3.1416, 3.1416),
title=f"{utils.getCounter(i+1)} jet phi",
plotopts=utils.getOpts(uname, **{"log-y": False})))
plots.append(
Plot.make1D(f"{uname}_jet_DR",
op.deltaR(jets[0].p4, jets[1].p4),
sel,
EqB(50, 0.3, 3.),
title="Jets DR",
plotopts=utils.getOpts(uname, **{"log-y": False})))
plots.append(
Plot.make1D(f"{uname}_jet_M",
op.invariant_mass(jets[0].p4, jets[1].p4),
sel,
EqB(60, 0., 400.),
title="dijets invariant mass [GeV]",
plotopts=utils.getOpts(uname)))
plots.append(
Plot.make1D(f"{uname}_jet_pT", (jets[0].p4 + jets[1].p4).Pt(),
sel,
EqB(60, 0., 600.),
title=" dijets p_{T} [GeV]",
plotopts=utils.getOpts(uname)))
return plots
def definePlots(self, t, noSel, sample=None, sampleCfg=None):
from bamboo.plots import CutFlowReport, SummedPlot
from bamboo.plots import EquidistantBinning as EqB
from bamboo import treefunctions as op
isMC = self.isMC(sample)
trigCut, trigWeight = None, None
if isMC:
trigCut = op.OR(t.HLT.HIEle20_Ele12_CaloIdL_TrackIdL_IsoVL_DZ, t.HLT.HIL3DoubleMu0, t.HLT.HIL3Mu20, t.HLT.HIEle20_WPLoose_Gsf)
trigWeight = op.switch(op.OR(t.HLT.HIEle20_Ele12_CaloIdL_TrackIdL_IsoVL_DZ, t.HLT.HIL3DoubleMu0), op.c_float(1.),
op.switch(t.HLT.HIL3Mu20, op.c_float(306.913/308.545), op.c_float(264.410/308.545))) ## FIXME these are wrong - you will get the final values from team A
else:
## trigger order: dielectron, dimuon or single muon, single electron
pd = sample.split("_")[0]
if pd == "SingleMuon":
trigCut = op.AND(op.NOT(t.HLT.HIEle20_Ele12_CaloIdL_TrackIdL_IsoVL_DZ),
op.OR(t.HLT.HIL3DoubleMu0, t.HLT.HIL3Mu20))
elif pd == "HighEGJet":
trigCut = op.OR(t.HLT.HIEle20_Ele12_CaloIdL_TrackIdL_IsoVL_DZ,
op.AND(op.NOT(op.OR(t.HLT.HIL3DoubleMu0, t.HLT.HIL3Mu20)),
t.HLT.HIEle20_WPLoose_Gsf))
noSel = noSel.refine("trig", cut=trigCut, weight=trigWeight)
plots = []
def isGoodElectron(el, ptCut=10.):
return op.AND(
el.pt > ptCut,
op.abs(el.eta) < 2.5,
el.lostHits == 0, ## do you want this?
op.abs(el.sip3d) < 8.,
op.abs(el.dxy) < .05,
op.abs(el.dz ) < .1,
el.miniPFRelIso_all < 0.085,
el.mvaTTH > 0.125,
op.NOT(op.AND(el.jet.isValid, op.OR(el.jet.btagDeepB > .1522, el.jet.btagDeepB <= -999.)))
)
def isGoodMuon(mu, ptCut=10.):
return op.AND(
mu.pt > ptCut,
op.abs(mu.eta) < 2.4,
mu.mediumPromptId,
op.abs(mu.sip3d) < 8.,
op.abs(mu.dxy) < .05,
op.abs(mu.dz ) < .1,
mu.miniPFRelIso_all < 0.325,
mu.mvaTTH > 0.55,
op.NOT(op.AND(mu.jet.isValid, op.OR(mu.jet.btagDeepB > .1522, mu.jet.btagDeepB <= -999.)))
)
goodLeptons = {
"el" : op.select(t.Electron, partial(isGoodElectron, ptCut=15.)),
"mu" : op.select(t.Muon, partial(isGoodMuon, ptCut=15.))
}
plots += [
Plot.make1D("trig_nLeptons15", op.rng_len(goodLeptons["el"])+op.rng_len(goodLeptons["mu"]), noSel, EqB(15, 0., 15.)),
Plot.make1D("trig_nEl15", op.rng_len(goodLeptons["el"]), noSel, EqB(15, 0., 15.)),
Plot.make1D("trig_nMu15", op.rng_len(goodLeptons["mu"]), noSel, EqB(15, 0., 15.))
]
from bamboo.scalefactors import get_scalefactor
sf_loose = {
"mu": get_scalefactor("lepton", "Muon_RecoToLoose", sfLib=scalefactors_lepMVA, paramDefs=binningVariables_nano_noScaleSyst, systName="muLoose"),
"el": get_scalefactor("lepton", "Electron_RecoToLoose", sfLib=scalefactors_lepMVA, paramDefs=binningVariables_nano_noScaleSyst, systName="elLoose")
}
sf_tight = {
"mu": get_scalefactor("lepton", "Muon_LooseToTight", sfLib=scalefactors_lepMVA, paramDefs=binningVariables_nano_noScaleSyst, systName="muTight"),
"el": get_scalefactor("lepton", "Electron_LooseToTight", sfLib=scalefactors_lepMVA, paramDefs=binningVariables_nano_noScaleSyst, systName="elTight")
}
nGoodLeptons = op.rng_len(goodLeptons["el"])+op.rng_len(goodLeptons["mu"])
hasTwoGoodLeptons = noSel.refine("has2Lep", cut=(nGoodLeptons > 1)) # avoid overlap with 1l
jets = op.sort(op.select(t.Jet, lambda j : op.AND(
j.pt > 25.,
op.abs(j.eta) < 2.4,
j.jetId & 0x2,
op.AND(
op.NOT(op.rng_any(goodLeptons["el"], lambda l : op.deltaR(l.p4, j.p4) < 0.4)),
op.NOT(op.rng_any(goodLeptons["mu"], lambda l : op.deltaR(l.p4, j.p4) < 0.4)))
)), lambda j : -j.pt)
## WP: see https://twiki.cern.ch/twiki/bin/viewauth/CMS/BtagRecommendation94X
loosebjets = op.select(jets, lambda j : j.btagDeepB > 0.1522)
mediumbjets = op.select(jets, lambda j : j.btagDeepB > 0.4941)
for fl1,fl2 in product(*repeat(goodLeptons.keys(), 2)):
dilepSel = lambda l1,l2 : op.AND(
l1.charge != l2.charge,
(l1.p4+l2.p4).M() > 12.
)
if fl1 == fl2:
lGood = op.sort(goodLeptons[fl1], lambda l : -l.pt)
dilep = op.combine(lGood, N=2, pred=dilepSel)
else:
l1Good = op.sort(goodLeptons[fl1], lambda l : -l.pt)
l2Good = op.sort(goodLeptons[fl2], lambda l : -l.pt)
dilep = op.combine((l1Good, l2Good), pred=dilepSel)
ll = dilep[0]
hasDilep = hasTwoGoodLeptons.refine(f"hasDilep{fl1}{fl2}", cut=(op.rng_len(dilep) > 0, ll[0].pt > 25.),
weight=([ sf_loose[fl1](ll[0]), sf_loose[fl2](ll[1]), sf_tight[fl1](ll[0]), sf_tight[fl2](ll[1]) ] if isMC else None))
plots += [
Plot.make1D(f"dilepton_{fl1}{fl2}_Mll", (ll[0].p4+ll[1].p4).M(), hasDilep, EqB(50, 70, 120.), title="Dilepton mass"),
]
# for il,ifl in enumerate((fl1, fl2)):
## plots += [
# Plot.make1D(f"dilepton_{fl1}{fl2}_L{il:d}PT", ll[il].pt, hasDilep, EqB(50, 0., 100.), title=f"Lepton {il:d} PT"),
# Plot.make1D(f"dilepton_{fl1}{fl2}_L{il:d}ETA", ll[il].eta, hasDilep, EqB(50, -2.5, 2.5), title=f"Lepton {il:d} ETA"),
# ]
# plots += [
# Plot.make1D(f"dilepton_{fl1}{fl2}_nJets", op.rng_len(jets), hasDilep, EqB(15, 0, 15.), title="Jet multiplicity"),
# Plot.make1D(f"dilepton_{fl1}{fl2}_nLooseBJets", op.rng_len(loosebjets), hasDilep, EqB(15, 0, 15.), title="Loose b-jet multiplicity"),
# Plot.make1D(f"dilepton_{fl1}{fl2}_nMediumBJets", op.rng_len(mediumbjets), hasDilep, EqB(15, 0, 15.), title="Medium b-jet multiplicity")
# ]
return plots
def __init__(self, name):
self.name = name
self.plotopts = dict()
self.axisTitles = ("Yield", )
self.binnings = [EqB(1, 0., 1.)]
def createHistos(self):
''' Create all the histos for the analysis '''
### Analysis histos
for key_chan in channel:
ichan = channnel[key_chan]
# Event
self.NewHisto('HT', ichan, 80, 0, 400)
self.NewHisto('MET', ichan, 30, 0, 150)
self.NewHisto('NJets',ichan, 8 ,-0.5, 7.5)
self.NewHisto('Btags',ichan, 4 ,-0.5, 3.5)
self.NewHisto('Vtx', ichan, 10, -0.5, 9.5)
self.NewHisto('NBtagNJets', ichan, 7, -0.5, 6.5)
self.NewHisto('NBtagNJets_3bins', ichan, 3, -0.5, 2.5)
# Leptons
self.NewHisto('Lep0Pt', ichan, 20, 20, 120)
self.NewHisto('Lep1Pt', ichan, 16, 10, 90)
self.NewHisto('Lep0Eta', ichan, 50, -2.5, 2.5)
self.NewHisto('Lep1Eta', ichan, 50, -2.5, 2.5)
self.NewHisto('Lep0Phi', ichan, 20, -1, 1)
self.NewHisto('Lep1Phi', ichan, 20, -1, 1)
self.NewHisto('DilepPt', ichan, 40, 0, 200)
self.NewHisto('InvMass', ichan, 60, 0, 300)
self.NewHisto('DYMass', ichan, 200, 70, 110)
self.NewHisto('DYMassBB', ichan, 200, 70, 110)
self.NewHisto('DYMassBE', ichan, 200, 70, 110)
self.NewHisto('DYMassEB', ichan, 200, 70, 110)
self.NewHisto('DYMassEE', ichan, 200, 70, 110)
self.NewHisto('DeltaPhi', ichan, 20, 0, 1)
if ichan == chan[ch.ElMu]:
self.NewHisto('ElecEta', 'ElMu', 50, -2.5, 2.5)
self.NewHisto('MuonEta', 'ElMu', 50, -2.5, 2.5)
self.NewHisto('ElecPt', 'ElMu', 20, 10, 110)
self.NewHisto('MuonPt', 'ElMu', 20, 10, 110)
self.NewHisto('ElecPhi', 'ElMu', 20, -1, 1)
self.NewHisto('MuonPhi', 'ElMu', 20, -1, 1)
def FillHistograms(self, leptons, jets, pmet, ich, ilev, isys):
''' Fill all the histograms. Take the inputs from lepton list, jet list, pmet '''
if self.SS: return # Do not fill histograms for same-sign events
if not len(leptons) >= 2: return # Just in case
# Re-calculate the observables
lep0 = leptons[0]; lep1 = leptons[1]
l0pt = lep0.Pt(); l1pt = lep1.Pt()
l0eta = lep0.Eta(); l1eta = lep1.Eta()
l0phi = lep0.Phi(); l1phi = lep1.Phi()
dphi = DeltaPhi(lep0, lep1)
mll = InvMass(lep0, lep1)
dipt = DiPt(lep0, lep1)
mupt = 0; elpt = 0
mueta = 0; eleta = 0
muphi = 0; elphi = 0
if ich == channel.ElMu:
if lep0.IsMuon():
mu = lep0
el = lep1
else:
mu = lep1
el = lep0
elpt = el.Pt(); mupt = mu.Pt()
eleta = el.Eta(); mueta = mu.Eta()
elphi = el.Phi(); muphi = mu.Phi()
met = pmet.Pt()
ht = 0;
### Fill the histograms
#if ich == ch.ElMu and ilev == lev.dilepton: print 'Syst = ', isys, ', weight = ', self.weight
self.GetHisto('HT', ich).Fill(ht)
self.GetHisto('MET', ich).Fill(met)
self.GetHisto('NJets',ich).Fill(njet)
self.GetHisto('Btags',ich).Fill(nbtag)
self.GetHisto('Vtx', ich).Fill(self.nvtx)
self.GetHisto("InvMass", ich, ).Fill(mll)
# Leptons
self.GetHisto('Lep0Pt', ich).Fill(l0pt)
self.GetHisto('Lep1Pt', ich).Fill(l1pt)
self.GetHisto('Lep0Eta', ich).Fill(l0eta)
self.GetHisto('Lep1Eta', ich).Fill(l1eta)
self.GetHisto('Lep0Phi', ich).Fill(l0phi/3.141592)
self.GetHisto('Lep1Phi', ich).Fill(l1phi/3.141592)
self.GetHisto('DilepPt', ich).Fill(dipt, self.weight)
self.GetHisto('DeltaPhi', ich).Fill(dphi/3.141592)
self.GetHisto('InvMass', ich).Fill(mll, self.weight)
if mll > 70 and mll < 110:
self.GetHisto('DYMass', ich).Fill(mll)
l0eta = abs(l0eta); l1eta = abs(l1eta)
if ich == chan.ElEl:
if l0eta <= 1.479 and l1eta <= 1.479: self.GetHisto('DYMassBB', ich).Fill(mll)
elif l0eta <= 1.479 and l1eta > 1.479: self.GetHisto('DYMassBE', ich).Fill(mll)
elif l0eta > 1.479 and l1eta <= 1.479: self.GetHisto('DYMassEB', ich).Fill(mll)
elif l0eta > 1.479 and l1eta > 1.479: self.GetHisto('DYMassEE', ich).Fill(mll)
if ich == chan.ElMu:
self.GetHisto('ElecEta', ich).Fill(eleta)
self.GetHisto('ElecPt', ich).Fill(elpt)
self.GetHisto('ElecPhi', ich).Fill(elphi)
self.GetHisto('MuonEta', ich).Fill(mueta)
self.GetHisto('MuonPt', ich).Fill(mupt)
self.GetHisto('MuonPhi', ich).Fill(muphi)
muons = op.select(t.Muon, lambda mu : mu.pt > 20.)
twoMuSel = noSel.refine("twoMuons", cut=[ op.rng_len(muons) > 1 ])
plots.append(Plot.make1D("dimu_M",
op.invariant_mass(muons[0].p4, muons[1].p4), twoMuSel, EqB(100, 20., 120.),
title="Dimuon invariant mass", plotopts={"show-overflow":False,
"legend-position": [0.2, 0.6, 0.5, 0.9]}))
electrons = op.select(t.Electron, lambda el : el.pt > 22.)
twoElSel = noSel.refine("twoElectrons", cut=[ op.rng_len(electrons) > 1 ])
plots.append(Plot.make1D("diel_M",
op.invariant_mass(electrons[0].p4, electrons[1].p4), twoElSel, EqB(100, 20., 120.),
title="Dielectron invariant mass", plotopts={"show-overflow":False,
"legend-position": [0.2, 0.6, 0.5, 0.9]}))
return plots
def definePlots(self, t, noSel, sample=None, sampleCfg=None):
from bamboo.plots import Plot, CutFlowReport
from bamboo.plots import EquidistantBinning as EqB
from bamboo import treefunctions as op
plots = []
#definitions
electrons = op.select(t.elec, lambda el : op.AND(
el.pt > 20., op.abs(el.eta) < 2.5
))
muons = op.select(t.muon, lambda mu : op.AND(
mu.pt > 20., op.abs(mu.eta) < 2.5
))
cleanedElectrons = op.select(electrons, lambda el : op.NOT(
op.rng_any(muons, lambda mu : op.deltaR(el.p4, mu.p4) < 0.3 )
))
# we are taking the second isopass to be on which is equal to the medium working point
isolatedElectrons = op.select(cleanedElectrons, lambda el : el.isopass & (1<<2) )
identifiedElectrons = op.select(isolatedElectrons, lambda el : el.idpass & (1<<2) )
cleanedMuons = op.select(muons, lambda mu : op.NOT(
op.rng_any(electrons, lambda el : op.deltaR(mu.p4, el.p4) < 0.3 )
))
isolatedMuons = op.select(cleanedMuons, lambda mu : mu.isopass & (1<<2) )
identifiedMuons = op.select(isolatedMuons, lambda mu : mu.idpass & (1<<2) )
InvMassMuMU = op.invariant_mass(identifiedMuons[0].p4, identifiedMuons[1].p4 )
cleanedJets = op.select(t.jetpuppi, lambda j : op.AND(
op.NOT(op.rng_any(identifiedElectrons, lambda el : op.deltaR(el.p4, j.p4) < 0.3) ),
op.NOT(op.rng_any(identifiedMuons, lambda mu : op.deltaR(mu.p4, j.p4) < 0.3) )
))
cleanedGoodJets = op.select(cleanedJets, lambda j : op.AND(
j.pt > 30, op.abs(j.eta) < 2.5
))
btaggedJets = op.select(cleanedGoodJets, lambda j : j.btag & (1<<2))
met = op.select(t.metpuppi)
#selections
#selection1 : Oppositely charged MuMu selection
sel1 = noSel.refine("nmumu", cut = [op.AND(
(op.rng_len(identifiedMuons) > 1), (op.product(identifiedMuons[0].charge, identifiedMuons[1].charge) < 0 ))])
#selection2 : Invariant mass selection
sel2 = sel1.refine("InvM", cut = [op.NOT(op.in_range(76, InvMassMuMU, 106))])
#selection3 : two jets selection
sel3 = sel2.refine("njet", cut = [op.rng_len(cleanedGoodJets) > 1])
#selection4 : at least 1 among two leading jets is b-tagged
sel4 = sel3.refine("btag", cut = [op.OR(
cleanedGoodJets[0].btag & (1<<2), cleanedGoodJets[1].btag & (1<<2))])
#selection5 : MET > 40 GeV
sel5 = sel4.refine("MET", cut = [met[0].pt > 40])
#plots
#noSel
plots.append(Plot.make1D("nJetsNoSel", op.rng_len(cleanedGoodJets), noSel, EqB(10, 0., 10.), title="nJets"))
plots.append(Plot.make1D("nbtaggedJetsNoSel", op.rng_len(btaggedJets), noSel, EqB(10, 0., 10.), title="nbtaggedJets"))
plots.append(Plot.make1D("nMuNoSel", op.rng_len(identifiedMuons), noSel, EqB(15, 0., 15.), title="nMuons"))
plots.append(Plot.make1D("METptNoSel", met[0].pt, noSel, EqB(50, 0., 250), title="MET_PT"))
#sel1
plots.append(Plot.make1D("nJetsSel1", op.rng_len(cleanedGoodJets), sel1, EqB(10, 0., 10.), title="nJets"))
plots.append(Plot.make1D("nbtaggedJetsSel1", op.rng_len(btaggedJets), sel1, EqB(10, 0., 10.), title="nbtaggedJets"))
plots.append(Plot.make1D("nMuSel1", op.rng_len(identifiedMuons), sel1, EqB(10, 0., 10.), title="nMuons"))
plots.append(Plot.make1D("InvMassTwoMuonsSel1", InvMassMuMU, sel1, EqB(30, 0, 300), title="m(ll)"))
plots.append(Plot.make1D("LeadingMuonPTSel1", muons[0].pt, sel1, EqB(30, 0., 250.), title=" Leading Muon PT"))
plots.append(Plot.make1D("SubLeadingMuonPTSel1", muons[1].pt, sel1, EqB(30, 0., 250.), title="SubLeading Muon PT"))
plots.append(Plot.make1D("LeadingMuonEtaSel1", muons[0].eta, sel1, EqB(30, -3, 3), title=" Leading Muon eta"))
plots.append(Plot.make1D("SubLeadingMuonEtaSel1", muons[1].eta, sel1, EqB(30, -3, 3), title="SubLeading Muon eta"))
plots.append(Plot.make1D("METptSel1", met[0].pt, sel1, EqB(50, 0., 250), title="MET_PT"))
#sel2
plots.append(Plot.make1D("nJetsSel2", op.rng_len(cleanedGoodJets), sel2, EqB(10, 0., 10.), title="nJets"))
plots.append(Plot.make1D("nbtaggedJetsSel2", op.rng_len(btaggedJets), sel2, EqB(10, 0., 10.), title="nbtaggedJets"))
plots.append(Plot.make1D("nMuSel2", op.rng_len(identifiedMuons), sel2, EqB(10, 0., 10.), title="nMuons"))
plots.append(Plot.make1D("InvMassTwoMuonsSel2", InvMassMuMU, sel2, EqB(20, 20., 300.), title="m(ll)"))
plots.append(Plot.make1D("LeadingMuonPTSel2", muons[0].pt, sel2, EqB(30, 0., 250.), title=" Leading Muon PT"))
plots.append(Plot.make1D("SubLeadingMuonPTSel2", muons[1].pt, sel2, EqB(30, 0., 200.), title=" SubLeading Muon PT"))
plots.append(Plot.make1D("LeadingMuonEtaSel2", muons[0].eta, sel2, EqB(30, -3, 3), title=" Leading Muon Eta"))
plots.append(Plot.make1D("SubLeadingMuonEtaSel2", muons[1].eta, sel2, EqB(30, -3, 3), title=" SubLeading Muon Eta"))
plots.append(Plot.make1D("METptSel2", met[0].pt, sel2, EqB(50, 0., 250), title="MET_PT"))
#sel3
plots.append(Plot.make1D("nJetsSel3", op.rng_len(cleanedGoodJets), sel3, EqB(10, 0., 10.), title="nJets"))
plots.append(Plot.make1D("nbtaggedJetsSel3", op.rng_len(btaggedJets), sel3, EqB(10, 0., 10.), title="nbtaggedJets"))
plots.append(Plot.make1D("LeadingJetPTSel3", cleanedGoodJets[0].pt, sel3, EqB(50, 0., 350.), title="Leading jet PT"))
plots.append(Plot.make1D("SubLeadingJetPTSel3", cleanedGoodJets[1].pt, sel3, EqB(50, 0., 350.), title="SubLeading jet PT"))
plots.append(Plot.make1D("LeadingJetEtaSel3", cleanedGoodJets[0].eta, sel3, EqB(30, -3, 3), title="Leading jet Eta"))
plots.append(Plot.make1D("SubLeadingJetEtaSel3", cleanedGoodJets[1].eta, sel3, EqB(30, -3, 3), title="SubLeading jet Eta"))
plots.append(Plot.make1D("nMuSel3", op.rng_len(identifiedMuons), sel3, EqB(10, 0., 10.), title="nMuons"))
plots.append(Plot.make1D("LeadingMuonPTSel3", muons[0].pt, sel3, EqB(30, 0., 250.), title=" Leading Muon PT"))
plots.append(Plot.make1D("SubLeadingMuonPTSel3", muons[1].pt, sel3, EqB(30, 0., 200.), title=" SubLeading Muon PT"))
plots.append(Plot.make1D("LeadingMuonEtaSel3", muons[0].eta, sel3, EqB(30, -3, 3), title=" Leading Muon Eta"))
plots.append(Plot.make1D("SubLeadingMuonEtaSel3", muons[1].eta, sel3, EqB(30, -3, 3), title=" SubLeading Muon Eta"))
plots.append(Plot.make1D("InvMassTwoMuonsSel3", InvMassMuMU, sel3, EqB(30, 0, 300), title="m(ll)"))
plots.append(Plot.make1D("METptSel3", met[0].pt, sel3, EqB(50, 0., 250), title="MET_PT"))
#sel4
plots.append(Plot.make1D("nJetsSel4", op.rng_len(cleanedGoodJets), sel4, EqB(10, 0, 10), title="nJets"))
plots.append(Plot.make1D("nbtaggedJetsSel4", op.rng_len(btaggedJets), sel4, EqB(10, 0., 10.), title="nbtaggedJets"))
plots.append(Plot.make1D("LeadingJetPTSel4", cleanedGoodJets[0].pt, sel4, EqB(50, 0., 250.), title="Leading jet PT"))
plots.append(Plot.make1D("SubLeadingJetPTSel4", cleanedGoodJets[1].pt, sel4, EqB(50, 0., 250.), title="SubLeading jet PT"))
plots.append(Plot.make1D("LeadingJetEtaSel4", cleanedGoodJets[0].eta, sel4, EqB(30, -3, 3.), title="Leading jet Eta"))
plots.append(Plot.make1D("SubLeadingJetEtaSel4", cleanedGoodJets[1].eta, sel4, EqB(30, -3, 3.), title="SubLeading jet Eta"))
plots.append(Plot.make1D("nMuSel4", op.rng_len(identifiedMuons), sel4, EqB(10, 0., 10.), title="nMuons"))
plots.append(Plot.make1D("LeadingMuonPTSel4", muons[0].pt, sel4, EqB(30, 0., 250.), title=" Leading Muon PT"))
plots.append(Plot.make1D("SubLeadingMuonPTSel4", muons[1].pt, sel4, EqB(30, 0., 200.), title=" SubLeading Muon PT"))
plots.append(Plot.make1D("LeadingMuonEtaSel4", muons[0].eta, sel4, EqB(30, -3, 3), title=" Leading Muon Eta"))
plots.append(Plot.make1D("SubLeadingMuonEtaSel4", muons[1].eta, sel4, EqB(30, -3, 3), title=" SubLeading Muon Eta"))
plots.append(Plot.make1D("InvMassTwoMuonsSel4", InvMassMuMU, sel4, EqB(30, 0, 300), title="m(ll)"))
plots.append(Plot.make1D("METptSel4", met[0].pt, sel4, EqB(50, 0., 250), title="MET_PT"))
#sel5
plots.append(Plot.make1D("nJetsSel5", op.rng_len(cleanedGoodJets), sel5, EqB(10, 0, 10), title="nJets"))
plots.append(Plot.make1D("nbtaggedJetsSel5", op.rng_len(btaggedJets), sel5, EqB(10, 0., 10.), title="nbtaggedJets"))
plots.append(Plot.make1D("LeadingJetPTSel5", cleanedGoodJets[0].pt, sel5, EqB(50, 0., 250.), title="Leading jet PT"))
plots.append(Plot.make1D("SubLeadingJetPTSel5", cleanedGoodJets[1].pt, sel5, EqB(50, 0., 250.), title="SubLeading jet PT"))
plots.append(Plot.make1D("LeadingJetEtaSel5", cleanedGoodJets[0].eta, sel5, EqB(30, -3, 3.), title="Leading jet Eta"))
plots.append(Plot.make1D("SubLeadingJetEtaSel5", cleanedGoodJets[1].eta, sel5, EqB(30, -3, 3.), title="SubLeading jet Eta"))
plots.append(Plot.make1D("nMuSel5", op.rng_len(identifiedMuons), sel5, EqB(10, 0., 10.), title="nMuons"))
plots.append(Plot.make1D("LeadingMuonPTSel5", muons[0].pt, sel5, EqB(30, 0., 250.), title=" Leading Muon PT"))
plots.append(Plot.make1D("SubLeadingMuonPTSel5", muons[1].pt, sel5, EqB(30, 0., 200.), title=" SubLeading Muon PT"))
plots.append(Plot.make1D("LeadingMuonEtaSel5", muons[0].eta, sel5, EqB(30, -3, 3), title=" Leading Muon Eta"))
plots.append(Plot.make1D("SubLeadingMuonEtaSel5", muons[1].eta, sel5, EqB(30, -3, 3), title=" SubLeading Muon Eta"))
plots.append(Plot.make1D("InvMassTwoMuonsSel5", InvMassMuMU, sel5, EqB(30, 0, 300), title="m(ll)"))
plots.append(Plot.make1D("METptSel5", met[0].pt, sel5, EqB(50, 0., 250), title="MET_PT > 40"))
# Efficiency Report on terminal and the .tex output
cfr = CutFlowReport("yields")
cfr.add(noSel, "Sel0: No selection")
cfr.add(sel1, "Sel1: nMuMu >= 2")
cfr.add(sel2, "Sel2: InvM")
cfr.add(sel3, "Sel3: nJet >= 2")
cfr.add(sel4, "Sel4: btag")
cfr.add(sel5, "Sel5: MET")
plots.append(cfr)
return plots
def definePlots(self, t, noSel, sample=None, sampleCfg=None):
from bamboo.plots import Plot, CutFlowReport, SummedPlot
from bamboo.plots import EquidistantBinning as EqB
from bamboo import treefunctions as op
isMC = self.isMC(sample)
trigCut, trigWeight = None, None
if isMC:
noSel = noSel.refine("mcWeight", weight=[ t.genWeight, t.puWeight, t.PrefireWeight ])
trigCut = op.OR(t.HLT.HIEle20_Ele12_CaloIdL_TrackIdL_IsoVL_DZ, t.HLT.HIL3DoubleMu0, t.HLT.HIL3Mu20, t.HLT.HIEle20_WPLoose_Gsf)
## TODO add a correction for prescaled triggers
else:
## suggested trigger order: dielectron, dimuon or single muon, single electron (to minimise loss due to prescales). Electron triggered-events should be taken from the HighEGJet primary datasets, muon-triggered events from the SingleMuon primary datset
pd = sample.split("_")[0]
if pd == "SingleMuon":
## TODO fill trigger cut
elif pd == "HighEGJet":
## TODO fill trigger cut
noSel = noSel.refine("trig", cut=trigCut, weight=trigWeight)
plots = []
goodLeptons = {
"el" : op.select(t.Electron, partial(isGoodElectron, ptCut=15.)),
"mu" : op.select(t.Muon, partial(isGoodMuon, ptCut=15.))
}
plots += [
Plot.make1D("trig_nLeptons15", op.rng_len(goodLeptons["el"])+op.rng_len(goodLeptons["mu"]), noSel, EqB(15, 0., 15.)),
Plot.make1D("trig_nEl15", op.rng_len(goodLeptons["el"]), noSel, EqB(15, 0., 15.)),
Plot.make1D("trig_nMu15", op.rng_len(goodLeptons["mu"]), noSel, EqB(15, 0., 15.))
]
from bamboo.scalefactors import get_scalefactor
sf_loose = {
"mu": get_scalefactor("lepton", "Muon_RecoToLoose", sfLib=scalefactors_lepMVA, paramDefs=binningVariables_nano_noScaleSyst, systName="muLoose"),
"el": get_scalefactor("lepton", "Electron_RecoToLoose", sfLib=scalefactors_lepMVA, paramDefs=binningVariables_nano_noScaleSyst, systName="elLoose")
}
sf_tight = {
"mu": get_scalefactor("lepton", "Muon_LooseToTight", sfLib=scalefactors_lepMVA, paramDefs=binningVariables_nano_noScaleSyst, systName="muTight"),
"el": get_scalefactor("lepton", "Electron_LooseToTight", sfLib=scalefactors_lepMVA, paramDefs=binningVariables_nano_noScaleSyst, systName="elTight")
}
nGoodLeptons = op.rng_len(goodLeptons["el"])+op.rng_len(goodLeptons["mu"])
hasTwoGoodLeptons = noSel.refine("has2Lep", cut=(nGoodLeptons > 1)) # avoid overlap with 1l
jets = op.sort(op.select(t.Jet, lambda j : op.AND(
j.pt > 25., ## you decide...
op.abs(j.eta) < 2.4,
j.jetId & 0x2, ## tight JetID
op.AND( ## lepton-jet cross-cleaning
op.NOT(op.rng_any(goodLeptons["el"], lambda l : op.deltaR(l.p4, j.p4) < 0.4)),
op.NOT(op.rng_any(goodLeptons["mu"], lambda l : op.deltaR(l.p4, j.p4) < 0.4)))
)), lambda j : -j.pt)
for fl1,fl2 in product(*repeat(goodLeptons.keys(), 2)):
dilepSel = lambda l1,l2 : op.AND(
l1.charge != l2.charge,
(l1.p4+l2.p4).M() > 12.
)
if fl1 == fl2:
lGood = op.sort(goodLeptons[fl1], lambda l : -l.pt)
dilep = op.combine(lGood, N=2, pred=dilepSel)
else:
l1Good = op.sort(goodLeptons[fl1], lambda l : -l.pt)
l2Good = op.sort(goodLeptons[fl2], lambda l : -l.pt)
dilep = op.combine((l1Good, l2Good), pred=dilepSel)
ll = dilep[0]
hasDilep = hasTwoGoodLeptons.refine(f"hasDilep{fl1}{fl2}", cut=(op.rng_len(dilep) > 0, ll[0].pt > 25.),
weight=([ sf_loose[fl1](ll[0]), sf_loose[fl2](ll[1]), sf_tight[fl1](ll[0]), sf_tight[fl2](ll[1]) ] if isMC else None))
plots += [
Plot.make1D(f"dilepton_{fl1}{fl2}_Mll", (ll[0].p4+ll[1].p4).M(), hasDilep, EqB(50, 70, 120.), title="Dilepton mass"),
]
for il,ifl in enumerate((fl1, fl2)):
plots += [
Plot.make1D(f"dilepton_{fl1}{fl2}_L{il:d}PT", ll[il].pt, hasDilep, EqB(50, 0., 100.), title=f"Lepton {il:d} PT"),
Plot.make1D(f"dilepton_{fl1}{fl2}_L{il:d}ETA", ll[il].eta, hasDilep, EqB(50, -2.5, 2.5), title=f"Lepton {il:d} ETA"),
]
plots += [
Plot.make1D(f"dilepton_{fl1}{fl2}_nJets", op.rng_len(jets), hasDilep, EqB(15, 0, 15.), title="Jet multiplicity"),
]
return plots
def definePlots(self, t, noSel, sample=None, sampleCfg=None):
from bamboo.plots import Plot, CutFlowReport, SummedPlot
from bamboo.plots import EquidistantBinning as EqB
from bamboo import treefunctions as op
isMC = self.isMC(sample)
if sampleCfg.get("alt-syst"):
noSel = noSel.refine("withoutsyst", autoSyst=False)
plots = []
trigCut, trigWeight = None, None
if isMC:
muR = op.systematic(op.c_float(1.),
name="muR",
up=t.PSWeight[2],
down=t.PSWeight[0])
muF = op.systematic(op.c_float(1.),
name="muF",
up=t.PSWeight[3],
down=t.PSWeight[1])
noSel = noSel.refine(
"mcWeight",
weight=[t.genWeight, t.puWeight, t.PrefireWeight, muR, muF])
trigCut = op.OR(t.HLT.HIEle20_Ele12_CaloIdL_TrackIdL_IsoVL_DZ,
t.HLT.HIL3DoubleMu0, t.HLT.HIL3Mu20,
t.HLT.HIEle20_WPLoose_Gsf)
trigWeight = op.switch(
op.OR(t.HLT.HIEle20_Ele12_CaloIdL_TrackIdL_IsoVL_DZ,
t.HLT.HIL3DoubleMu0), op.c_float(1.),
op.switch(t.HLT.HIL3Mu20, op.c_float(306.913 / 308.545),
op.c_float(264.410 / 308.545))
) ## FIXME these are wrong - you will get the final values from team A
else:
## trigger order: dielectron, dimuon or single muon, single electron
pd = sample.split("_")[0]
if pd == "SingleMuon":
trigCut = op.AND(
op.NOT(t.HLT.HIEle20_Ele12_CaloIdL_TrackIdL_IsoVL_DZ),
op.OR(t.HLT.HIL3DoubleMu0, t.HLT.HIL3Mu20))
elif pd == "HighEGJet":
trigCut = op.OR(
t.HLT.HIEle20_Ele12_CaloIdL_TrackIdL_IsoVL_DZ,
op.AND(op.NOT(op.OR(t.HLT.HIL3DoubleMu0, t.HLT.HIL3Mu20)),
t.HLT.HIEle20_WPLoose_Gsf))
noSel = noSel.refine("trig", cut=trigCut, weight=trigWeight)
#plots += [Plot.make1D("nTotalEvents", op.rng_len([1]), noSel , EqB(1, 0, 1.), title="nTotalEvents")]
plots.append(
Plot.make1D("nTotalJets",
op.rng_len(t.Jet),
noSel,
EqB(15, 0, 15.),
title="Initial Jet multiplicity"))
#noSel = noSel.refine("trig", cut=op.OR(t.HLT.HIL3DoubleMu0, t.HLT.HIEle20_Ele12_CaloIdL_TrackIdL_IsoVL_DZ))
# plots = []
goodLeptons = {
"el":
op.select(
t.Electron, lambda el: op.AND(el.pt > 15.,
op.abs(el.p4.Eta()) < 2.5)
), # op.select(t.Electron, partial(isGoodElectron, ptCut=15.)),
"mu":
op.select(t.Muon, lambda mu: mu.pt > 20.
) # op.select(t.Muon, partial(isGoodMuon, ptCut=15.))
}
plots += [
Plot.make1D(
"trig_nLeptons15",
op.rng_len(goodLeptons["el"]) + op.rng_len(goodLeptons["mu"]),
noSel, EqB(15, 0., 15.)),
Plot.make1D("trig_nEl15", op.rng_len(goodLeptons["el"]), noSel,
EqB(15, 0., 15.)),
Plot.make1D("trig_nMu15", op.rng_len(goodLeptons["mu"]), noSel,
EqB(15, 0., 15.))
]
from bamboo.scalefactors import get_scalefactor
sf_loose = {
"mu":
get_scalefactor("lepton",
"Muon_RecoToLoose",
sfLib=scalefactors_lepMVA,
paramDefs=binningVariables_nano_noScaleSyst,
systName="muLoose"),
"el":
get_scalefactor("lepton",
"Electron_RecoToLoose",
sfLib=scalefactors_lepMVA,
paramDefs=binningVariables_nano_noScaleSyst,
systName="elLoose")
}
sf_tight = {
"mu":
get_scalefactor("lepton",
"Muon_LooseToTight",
sfLib=scalefactors_lepMVA,
paramDefs=binningVariables_nano_noScaleSyst,
systName="muTight"),
"el":
get_scalefactor("lepton",
"Electron_LooseToTight",
sfLib=scalefactors_lepMVA,
paramDefs=binningVariables_nano_noScaleSyst,
systName="elTight")
}
nGoodLeptons = op.rng_len(goodLeptons["el"]) + op.rng_len(
goodLeptons["mu"])
hasTwoGoodLeptons = noSel.refine(
"has2Lep", cut=(nGoodLeptons > 1)) # avoid overlap with 1l
jets = op.sort(
op.select(
t.Jet, lambda j: op.AND(
j.pt > 25.,
op.abs(j.eta) < 2.4, j.jetId & 0x2,
op.AND(
op.NOT(
op.rng_any(goodLeptons["el"], lambda l: op.deltaR(
l.p4, j.p4) < 0.4)),
op.NOT(
op.rng_any(goodLeptons["mu"], lambda l: op.deltaR(
l.p4, j.p4) < 0.4))))), lambda j: -j.pt)
## WP: see https://twiki.cern.ch/twiki/bin/viewauth/CMS/BtagRecommendation94X
loosebjets = op.select(jets, lambda j: j.btagDeepB > 0.1522)
mediumbjets = op.select(jets, lambda j: j.btagDeepB > 0.4941)
for fl1, fl2 in product(*repeat(goodLeptons.keys(), 2)):
dilepSel = lambda l1, l2: op.AND(l1.charge != l2.charge,
(l1.p4 + l2.p4).M() > 12.)
if fl1 == fl2:
lGood = op.sort(goodLeptons[fl1], lambda l: -l.pt)
dilep = op.combine(lGood, N=2, pred=dilepSel)
else:
l1Good = op.sort(goodLeptons[fl1], lambda l: -l.pt)
l2Good = op.sort(goodLeptons[fl2], lambda l: -l.pt)
dilep = op.combine((l1Good, l2Good), pred=dilepSel)
ll = dilep[0]
hasDilep = hasTwoGoodLeptons.refine(
f"hasDilep{fl1}{fl2}",
cut=(op.rng_len(dilep) > 0, ll[0].pt > 25.),
weight=([
sf_loose[fl1](ll[0]), sf_loose[fl2](ll[1]), sf_tight[fl1](
ll[0]), sf_tight[fl2](ll[1])
] if isMC else None))
plots += [
Plot.make1D(f"dilepton_{fl1}{fl2}_Mll",
(ll[0].p4 + ll[1].p4).M(),
hasDilep,
EqB(50, 70, 120.),
title="Dilepton mass"),
]
for il, ifl in enumerate((fl1, fl2)):
plots += [
Plot.make1D(f"dilepton_{fl1}{fl2}_L{il:d}PT",
ll[il].pt,
hasDilep,
EqB(50, 0., 100.),
title=f"Lepton {il:d} PT"),
Plot.make1D(f"dilepton_{fl1}{fl2}_L{il:d}ETA",
ll[il].eta,
hasDilep,
EqB(50, -2.5, 2.5),
title=f"Lepton {il:d} ETA"),
]
plots += [
Plot.make1D(f"dilepton_{fl1}{fl2}_nJets",
op.rng_len(jets),
hasDilep,
EqB(15, 0, 15.),
title="Jet multiplicity"),
Plot.make1D(f"dilepton_{fl1}{fl2}_nLooseBJets",
op.rng_len(loosebjets),
hasDilep,
EqB(15, 0, 15.),
title="Loose b-jet multiplicity"),
Plot.make1D(f"dilepton_{fl1}{fl2}_nMediumBJets",
op.rng_len(mediumbjets),
hasDilep,
EqB(15, 0, 15.),
title="Medium b-jet multiplicity"),
#Plot.make1D(f"dilepton_{fl1}{fl2}_nSelectedEvents", 1, hasDilep, EqB(1, 0, 1.), title="nSelectedEvents")
]
#muons = op.select(t.Muon, lambda mu : mu.pt > 20.)
#twoMuSel = noSel.refine("twoMuons", cut=[ op.rng_len(muons) > 1 ])
#electrons = op.select(t.Electron, lambda el : op.AND(el.pt > 15. , op.abs(el.p4.Eta()) < 2.5))
#twoElSel = noSel.refine("twoElectrons", cut=[ op.rng_len(electrons) > 1 ])
#oselmu = op.combine((electrons, muons))
#leptons = oselmu[0]
#twoLepSel = noSel.refine("twoLeptons", cut=[ op.rng_len(electrons) == 1 , op.rng_len(muons) == 1 ])
#jets = op.select(t.Jet, lambda j : j.pt > 30.)
#bjets = op.select(jets, lambda j : j.btagDeepFlavB > 0.2217)
#plots.append(Plot.make1D("dimu_M",
# op.invariant_mass(muons[0].p4, muons[1].p4), twoMuSel, EqB(100, 20., 120.),
# title="Dimuon invariant mass", plotopts={"show-overflow":False,
# "legend-position": [0.2, 0.6, 0.5, 0.9]}))
#plots.append(Plot.make1D("diel_M",
# op.invariant_mass(electrons[0].p4, electrons[1].p4), twoElSel, EqB(100, 20., 120.),
# title="Dielectron invariant mass", plotopts={"show-overflow":False,
# "legend-position": [0.2, 0.6, 0.5, 0.9]}))
#plots.append(Plot.make1D("dilep_M",
# op.invariant_mass(leptons[0].p4, leptons[1].p4) , twoLepSel, EqB(100, 20., 120.),
# title="Dimuon invariant mass", plotopts={"show-overflow":False,
# "legend-position": [0.2, 0.6, 0.5, 0.9]}))
#plots.append(SummedPlot("Mjj", plots, title="m(jj)"))
#plots.append(Plot.make1D("nJets_dimu",op.rng_len(jets), twoMuSel, EqB(10, -0.5, 9.5),
# title="Jet multiplicity", plotopts={"show-overflow":False,
# "legend-position": [0.2, 0.6, 0.5, 0.9]}))
#plots.append(Plot.make1D("nBJets_dimu",op.rng_len(bjets), twoMuSel, EqB(10, -0.5, 9.5),
# title="Jet multiplicity", plotopts={"show-overflow":False,
# "legend-position": [0.2, 0.6, 0.5, 0.9]}))
#plots.append(Plot.make1D("nJets_diel",op.rng_len(jets), twoElSel, EqB(10, -0.5, 9.5),
# title="Jet multiplicity", plotopts={"show-overflow":False,
# "legend-position": [0.2, 0.6, 0.5, 0.9]}))
#plots.append(Plot.make1D("nBJets_diel",op.rng_len(bjets), twoElSel, EqB(10, -0.5, 9.5),
# title="Jet multiplicity", plotopts={"show-overflow":False,
# "legend-position": [0.2, 0.6, 0.5, 0.9]}))
#plots.append(Plot.make1D("nJets_elmu",op.rng_len(jets), twoLepSel, EqB(10, -0.5, 9.5),
# title="Jet multiplicity", plotopts={"show-overflow":False,
# "legend-position": [0.2, 0.6, 0.5, 0.9]}))
#plots.append(Plot.make1D("nBJets_elmu",op.rng_len(bjets), twoLepSel, EqB(10, -0.5, 9.5),
# title="Jet multiplicity", plotopts={"show-overflow":False,
# "legend-position": [0.2, 0.6, 0.5, 0.9]}))
return plots
def makeControlPlotsForBasicSel(self, sel, jets, dilepton, uname):
binScaling = 1
plots = []
plots.append(
Plot.make1D("{0}_leadJetPT".format(uname),
jets[0].pt,
sel,
EqB(60, 0., 450.),
title="P_{T} (leading Jet) [GeV]",
plotopts=utils.getOpts(uname)))
plots.append(
Plot.make1D("{0}_subleadJetPT".format(uname),
jets[1].pt,
sel,
EqB(60, 0., 450.),
title="P_{T} (sub-leading Jet) [GeV]",
plotopts=utils.getOpts(uname)))
plots.append(
Plot.make1D("{0}_leadJetETA".format(uname),
jets[0].eta,
sel,
EqB(10, -2.4, 2.4),
title="Eta (leading Jet)",
plotopts=utils.getOpts(uname)))
plots.append(
Plot.make1D("{0}_subleadJetETA".format(uname),
jets[1].eta,
sel,
EqB(10, -2.4, 2.4),
title="Eta (sub-leading Jet)",
plotopts=utils.getOpts(uname)))
for i in range(2):
plots.append(
Plot.make1D(f"{uname}_jet{i+1}_phi",
jets[i].phi,
sel,
EqB(50 // binScaling, -3.1416, 3.1416),
title=f"{utils.getCounter(i+1)} jet phi",
plotopts=utils.getOpts(uname, **{"log-y": False})))
plots.append(
Plot.make1D("{0}_jjpT".format(uname), (jets[0].p4 + jets[1].p4).pt,
sel,
EqB(100, 0., 450.),
title="dijet P_{T} [GeV]",
plotopts=utils.getOpts(uname)))
plots.append(
Plot.make1D("{0}_jjPhi".format(uname), (jets[0].p4 + jets[1].p4).phi,
sel,
EqB(50 // binScaling, -3.1416, 3.1416),
title="dijet phi",
plotopts=utils.getOpts(uname)))
plots.append(
Plot.make1D("{0}_jjEta".format(uname), (jets[0].p4 + jets[1].p4).eta,
sel,
EqB(50 // binScaling, -2.4, 2.4),
title="dijet eta",
plotopts=utils.getOpts(uname)))
plots.append(
Plot.make1D("{0}_mjj".format(uname),
op.invariant_mass(jets[0].p4, jets[1].p4),
sel,
EqB(100, 0., 800.),
title="mjj [GeV]",
plotopts=utils.getOpts(uname)))
plots.append(
Plot.make1D("{0}_mlljj".format(uname),
(dilepton[0].p4 + dilepton[1].p4 + jets[0].p4 +
jets[1].p4).M(),
sel,
EqB(100, 0., 1000.),
title="mlljj [GeV]",
plotopts=utils.getOpts(uname)))
plots.append(
Plot.make2D(
"{0}_mlljjvsmjj".format(uname),
(op.invariant_mass(jets[0].p4, jets[1].p4),
(dilepton[0].p4 + dilepton[1].p4 + jets[0].p4 + jets[1].p4).M()),
sel, (EqB(1000, 0., 1000.), EqB(1000, 0., 1000.)),
title="mlljj vs mjj invariant mass [Gev]",
plotopts=utils.getOpts(uname)))
return plots