def makeJetmultiplictyPlots(selection, jets, suffix, uname, ForBeauty=False):
binScaling = 1
plots = []
plots.append(
Plot.make1D(f"{uname}_%s_Jet_mulmtiplicity" % suffix,
op.rng_len(jets),
selection,
EqBin(10, 0., 10.),
title="Jet mulmtiplicity",
plotopts=utils.getOpts(uname, **{"log-y": True})))
if ForBeauty:
wp = suffix.split('_')[-1]
cut = suffix.replace(wp, '')
print(wp, cut)
for key, sel in selection.items():
tagger = key.replace(wp, "")
bjets = safeget(jets, tagger, wp)
plots.append(
Plot.make1D(f"{uname}_%s_%s%s_Jet_mulmtiplicity" %
(cut, tagger, wp),
op.rng_len(bjets),
sel,
EqBin(10, 0., 10.),
title="Jet mulmtiplicity",
plotopts=utils.getOpts(uname, **{"log-y": True})))
return plots
def definePlots(self, tree, noSel, sample=None, sampleCfg=None):
from bamboo.plots import Plot
from bamboo.plots import EquidistantBinning as EqBin
from bamboo import treefunctions as op
plots = []
verbose = False
trijets = op.combine(tree.Jet, N=3)
hadTop = op.rng_min_element_by(trijets,
fun=lambda comb: op.abs((comb[0].p4+comb[1].p4+comb[2].p4).M()-172.5))
hasTriJet = noSel.refine("hasTriJet", cut=(op.rng_len(trijets) > 0))
hadTop_p4 = op.defineOnFirstUse(hadTop[0].p4 + hadTop[1].p4 + hadTop[2].p4)
plots.append(Plot.make1D("trijet_topPt",
hadTop_p4.Pt(), hasTriJet,
EqBin(100, 15., 40.), title="Trijet p_{T} (GeV/c)"))
plots.append(Plot.make1D("trijet_maxbtag",
op.max(op.max(hadTop[0].btag, hadTop[1].btag), hadTop[2].btag), hasTriJet,
EqBin(100, 0., 1.), title="Trijet maximum b-tag"))
if verbose:
plots.append(Plot.make1D("njets",
op.rng_len(tree.Jet), noSel,
EqBin(20, 0., 20.), title="Number of jets"))
plots.append(Plot.make1D("ntrijets",
op.rng_len(trijets), noSel,
EqBin(100, 0., 1000.), title="Number of 3-jet combinations"))
plots.append(Plot.make1D("trijet_mass",
hadTop_p4.M(), hasTriJet,
EqBin(100, 0., 250.), title="Trijet mass (GeV/c^{2})"))
return plots
def evaluateJPA_1b0Wj(lepton, muons, electrons, ak4jets, jets, bJetsL, bJetsM, met, model, HLL):
#invars = [op.c_float(0.)]*8
invars = [lepton.pt, # leptonPt
bJetCorrPT(jets[0]), # bjet1_ptReg
jets[0].btagDeepFlavB, # bjet1_btagCSV
jets[0].qgl, # bjet1_qgDiscr
op.abs(lepton.eta - jets[0].eta), # dEta_bjet1_lep
op.rng_len(ak4jets), # nJets
op.rng_len(bJetsL), # nBJetLoose
op.rng_len(bJetsM) # nBJetMedium
]
return model(*invars, defineOnFirstUse=False)[0]
def evaluateJPA_2b0Wj(lepton, muons, electrons, ak4jets, jets, bJetsL, bJetsM, met, model, HLL):
#invars = [op.c_float(0.)]*9
invars = [bJetCorrPT(jets[0]), # bjet1_ptReg
jets[0].btagDeepFlavB, # bjet1_btagCSV
bJetCorrPT(jets[1]), # bjet2_ptReg
jets[1].btagDeepFlavB, # bjet2_btagCSV
jets[1].qgl, # bjet2_qgDiscr
op.abs(lepton.eta - jets[1].eta), # dEta_bjet2_lep
(HLL.bJetCorrP4(jets[0]) + HLL.bJetCorrP4(jets[1])).M(), # Hbb_massReg
op.rng_len(ak4jets), # nJets
op.rng_len(bJetsM) # nBJetMedium
]
return model(*invars, defineOnFirstUse=False)[0]
def definePlots(self, tree, noSel, sample=None, sampleCfg=None):
from bamboo.plots import Plot, SummedPlot
from bamboo.plots import EquidistantBinning as EqBin
from bamboo import treefunctions as op
plots = []
# The plot is made for each of the different flavour categories (l+/- l-/+ l') and then summed,
# because concatenation of containers is not (yet) supported.
lepColl = {"El": tree.Electron, "Mu": tree.Muon}
mt3lPlots = []
for dlNm, dlCol in lepColl.items():
dilep = op.combine(
dlCol,
N=2,
pred=(lambda l1, l2: op.AND(l1.charge != l2.charge)))
hasDiLep = noSel.refine("hasDilep{0}{0}".format(dlNm),
cut=(op.rng_len(dilep) > 0))
dilepZ = op.rng_min_element_by(
dilep,
fun=lambda ll: op.abs(
op.invariant_mass(ll[0].p4, ll[1].p4) - 91.2))
for tlNm, tlCol in lepColl.items():
if tlCol == dlCol:
hasTriLep = hasDiLep.refine("hasTrilep{0}{0}{1}".format(
dlNm, tlNm),
cut=(op.rng_len(tlCol) > 2))
residLep = op.select(
tlCol, lambda l: op.AND(l.idx != dilepZ[0].idx, l.idx
!= dilepZ[1].idx))
l3 = op.rng_max_element_by(residLep, lambda l: l.pt)
else:
hasTriLep = hasDiLep.refine("hasTriLep{0}{0}{1}".format(
dlNm, tlNm),
cut=(op.rng_len(tlCol) > 0))
l3 = op.rng_max_element_by(tlCol, lambda l: l.pt)
mtPlot = Plot.make1D(
"3lMT_{0}{0}{1}".format(dlNm, tlNm),
op.sqrt(2 * l3.pt * tree.MET.pt *
(1 - op.cos(l3.phi - tree.MET.phi))),
hasTriLep,
EqBin(100, 15., 250.),
title="M_{T} (GeV/c^2)")
mt3lPlots.append(mtPlot)
plots.append(mtPlot)
plots.append(SummedPlot("3lMT", mt3lPlots))
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 evaluateJPA_1b2Wj(lepton, muons, electrons, ak4jets, jets, bJetsL, bJetsM, met, model, HLL):
#invars = [op.c_float(0.)]*12
invars = [bJetCorrPT(jets[0]), # bjet1_ptReg
jets[0].btagDeepFlavB, # bjet1_btagCSV
bJetCorrPT(jets[1]), # wjet1_ptReg
jets[1].btagDeepFlavB, # wjet1_btagCSV
jets[2].btagDeepFlavB, # wjet2_btagCSV
jets[2].qgl, # wjet2_qgDiscr
HLL.Wjj_simple(jets[1].p4, jets[2].p4).M(), # HadW_mass
op.deltaR(HLL.Wjj_simple(jets[1].p4, jets[2].p4), lepton.p4), # dR_HadW_lep
op.deltaR(jets[1].p4, jets[2].p4), # dR_wjet1wjet2
(HLL.bJetCorrP4(jets[0]) + HLL.Wjj_simple(jets[1].p4, jets[2].p4)).M(), # mTop1 = (WhadP4 + bJet1P4).M()
op.rng_len(ak4jets), # nJets
op.rng_len(bJetsM) # nBJetMedium
]
return model(*invars, defineOnFirstUse=False)[0]
def plotNumber(contName, cont, sel, Nmax, xTitle):
return [
Plot.make1D(contName,
op.rng_len(cont),
sel,
EquidistantBinning(Nmax, 0., Nmax),
xTitle=xTitle)
]
def evaluateJPA_2b1Wj(lepton, muons, electrons, ak4jets, jets, bJetsL, bJetsM, met, model, HLL):
#invars = [op.c_float(0.)]*13
invars = [jets[0].btagDeepFlavB, # bjet1_btagCSV
bJetCorrPT(jets[1]), # bjet2_ptReg
jets[1].btagDeepFlavB, # bjet2_btagCSV
jets[1].qgl, # bjet2_qgDiscr
op.abs(lepton.eta - jets[1].eta), # dEta_bjet2_lep
bJetCorrPT(jets[2]), # wjet1_ptReg
jets[2].btagDeepFlavB, # wjet1_btagCSV
jets[2].qgl, # wjet1_qgDiscr
op.abs(lepton.eta - jets[2].eta), # dEta_wjet1_lep
op.deltaR(jets[0].p4, jets[1].p4), # dR_bjet1bjet2
op.rng_len(ak4jets), # nJets
op.rng_len(bJetsL), # nBJetLoose
op.rng_len(bJetsM) # nBJetMedium
]
return model(*invars, defineOnFirstUse=False)[0]
def plotRecoForGen(sel, gen, reco, lambda_match, name):
n_reco = [
op.select(
reco, lambda r: op.switch(
op.rng_len(gen) > i, lambda_match(gen[i], r), op.c_bool(False))
) for i in range(10)
]
plots = SummedPlot("n_reco_{}_per_gen".format(name), [
Plot.make1D("n_reco_{}_per_gen_{}".format(name, i),
op.rng_len(nre),
sel,
EquidistantBinning(10, 0, 10),
xTitle="N reco {} for gen {}".format(name, i))
for i, nre in enumerate(n_reco)
],
xTitle="N reco {} for each gen".format(name))
return plots
def reco_4l(leptons, lName, baseSel):
## select events with four leptons, and find the best Z candidate
## shared between 4el and 4mu
has4l = baseSel.refine(f"has4{lName}", cut=[
op.rng_len(leptons) == 4,
op.rng_sum(leptons, lambda l : l.charge) == 0,
])
allZcand = op.combine(leptons, N=2, pred=lambda l1,l2 : l1.charge != l2.charge)
bestZ = op.rng_min_element_by(allZcand, lambda ll : op.abs(op.invariant_mass(ll[0].p4, ll[1].p4)-mZ))
otherLeptons = op.select(leptons, partial(lambda l,oz=None : op.AND(l.idx != oz[0].idx, l.idx != oz[1].idx), oz=bestZ))
return has4l, bestZ, otherLeptons
def comp_cosThetaSbetBeamAndHiggs(self, genColl):
genh = op.select(
genColl,
lambda g: op.AND(g.pdgId == 25, g.statusFlags & (0x1 << 13)))
HH_p4 = genh[0].p4 + genh[1].p4
cm = HH_p4.BoostToCM()
boosted_h1 = op.extMethod("ROOT::Math::VectorUtil::boost",
returnType=genh[0].p4._typeName)(genh[0].p4,
cm)
boosted_h2 = op.extMethod("ROOT::Math::VectorUtil::boost",
returnType=genh[1].p4._typeName)(genh[1].p4,
cm)
mHH = op.switch(
op.rng_len(genh) == 2, op.invariant_mass(genh[0].p4, genh[1].p4),
op.c_float(-9999))
cosTheta1 = op.switch(
op.rng_len(genh) == 2, op.abs(boosted_h1.Pz() / boosted_h1.P()),
op.c_float(-9999))
cosTheta2 = op.switch(
op.rng_len(genh) == 2, op.abs(boosted_h1.Pz() / boosted_h2.P()),
op.c_float(-9999))
return [mHH, cosTheta1, cosTheta2]
def evaluateJPA_Hbb1Wj(lepton, muons, electrons, fatJets, jets, bJetsL, bJetsM, met, model, HLL):
#invars = [op.c_float(0.)]*14
invars = [op.switch(fatJets[0].subJet1.btagDeepB > fatJets[0].subJet2.btagDeepB, # dEta_bjet1_lep
op.abs(lepton.eta-fatJets[0].subJet1.eta),
op.abs(lepton.eta-fatJets[0].subJet2.eta)),
bJetCorrPT(jets[0]), # wjet1_ptReg
jets[0].btagDeepB, # wjet1_btagCSV
jets[0].qgl, # wjet1_qgDiscr
op.deltaR(lepton.p4, jets[0].p4), # dR_wjet1_lep
(fatJets[0].subJet1.p4 + fatJets[0].subJet2.p4).Pt(), # Hbb_Pt
op.rng_len(bJetsM) # nBJetMedium
]
return model(*invars, defineOnFirstUse=False)[0]
def controlPlots_2l(self, noSel, muons, electrons):
plots = [
Plot.make1D("nEl", op.rng_len(electrons), noSel, EqBin(10, 0., 10.), xTitle="Number of tight electrons"),
Plot.make1D("nMu", op.rng_len(muons), noSel, EqBin(10, 0., 10.), xTitle="Number of tight muons"),
]
hasOSElEl = noSel.refine("hasOSElEl", cut=[ op.rng_len(electrons) >= 2,
electrons[0].charge != electrons[1].charge, electrons[0].pt > 20., electrons[1].pt > 10. ])
plots.append(Plot.make1D("massZto2e", op.invariant_mass(electrons[0].p4, electrons[1].p4),
hasOSElEl, EqBin(120, 40., 120.), title="mass of Z to 2e",
xTitle="Invariant Mass of Nelectrons=2 (in GeV/c^2)"))
plots += [
Plot.make1D("OSElEl_PTl1", electrons[0].pt, hasOSElEl, EqBin(50, 0., 100.)),
Plot.make1D("OSElEl_PTl2", electrons[1].pt, hasOSElEl, EqBin(50, 0., 100.)),
]
hasOSMuMu = noSel.refine("hasOSMuMu", cut=[ op.rng_len(muons) >= 2,
muons[0].charge != muons[1].charge, muons[0].pt > 20., muons[1].pt > 10. ])
plots.append(Plot.make1D("massZto2mu", op.invariant_mass(muons[0].p4, muons[1].p4),
hasOSMuMu, EqBin(120, 40., 120.), title="mass of Z to 2mu",
xTitle="Invariant Mass of Nmuons=2 (in GeV/c^2)"))
plots += [
Plot.make1D("OSMuMu_PTl1", muons[0].pt, hasOSMuMu, EqBin(50, 0., 100.)),
Plot.make1D("OSMuMu_PTl2", muons[1].pt, hasOSMuMu, EqBin(50, 0., 100.)),
]
return plots
def returnFatjetMVAInputs(self, fatjets):
return {
('fatjet_E', 'Fatjet E [GeV]', (50, 0., 500.)):
op.switch(op.rng_len(fatjets) > 0, fatjets[0].p4.E(), op.c_float(0.)),
('fatjet_Px', 'Fatjet P_x [GeV]', (40, -200., 200.)):
op.switch(op.rng_len(fatjets) > 0, fatjets[0].p4.Px(), op.c_float(0.)),
('fatjet_Py', 'Fatjet P_y [GeV]', (40, -200., 200.)):
op.switch(op.rng_len(fatjets) > 0, fatjets[0].p4.Py(), op.c_float(0.)),
('fatjet_Pz', 'Fatjet P_z [GeV]', (40, -200., 200.)):
op.switch(op.rng_len(fatjets) > 0, fatjets[0].p4.Pz(), op.c_float(0.)),
('fatjet_tau1', 'Fatjet #tau_1', (50, 0., 1.)):
op.switch(op.rng_len(fatjets) > 0, fatjets[0].tau1, op.c_float(0.)),
('fatjet_tau2', 'Fatjet #tau_2', (50, 0., 1.)):
op.switch(op.rng_len(fatjets) > 0, fatjets[0].tau2, op.c_float(0.)),
('fatjet_tau3', 'Fatjet #tau_3', (50, 0., 1.)):
op.switch(op.rng_len(fatjets) > 0, fatjets[0].tau3, op.c_float(0.)),
('fatjet_tau4', 'Fatjet #tau_4', (50, 0., 1.)):
op.switch(op.rng_len(fatjets) > 0, fatjets[0].tau4, op.c_float(0.)),
('fatjet_softdrop', 'Fatjet softdrop mass [GeV]', (50, 0., 1000.)):
op.switch(
op.rng_len(fatjets) > 0, fatjets[0].msoftdrop, op.c_float(0.))
}
def definePlots(self, tree, noSel, sample=None, sampleCfg=None):
from bamboo.plots import Plot
from bamboo.plots import EquidistantBinning as EqBin
from bamboo import treefunctions as op
plots = []
jets40 = op.select(tree.Jet, lambda j: j.pt > 40)
hasTwoJets40 = noSel.refine("twoJets40", cut=(op.rng_len(jets40) >= 2))
plots.append(
Plot.make1D("twoJets40_MET",
tree.MET.pt,
hasTwoJets40,
EqBin(100, 0., 2000.),
title="MET (GeV)"))
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 definePlots(self, tree, noSel, sample=None, sampleCfg=None):
from bamboo.plots import Plot, SummedPlot
from bamboo.plots import EquidistantBinning as EqBin
from bamboo import treefunctions as op
plots = []
metSel = noSel.refine("MET", cut=(tree.met.et > 30000))
trigSel = metSel.refine("trig", cut=op.OR(tree.trigE, tree.trigM))
goodLeptons = op.select(
tree.lep, lambda l: op.AND(l.isTightID, l.pt > 35000., l.ptcone30 /
l.pt < 0.1, l.etcone20 / l.pt < 0.1))
oneLepSel = trigSel.refine("1goodlep",
cut=(op.rng_len(goodLeptons) == 1))
lep = goodLeptons[0]
signalSel = oneLepSel.refine(
"signalRegion",
cut=op.AND(
op.abs(lep.z0 * op.sin(lep.p4.theta())) < 0.5,
op.multiSwitch(
(lep.type == 11,
op.AND(
op.abs(lep.eta) < 2.46,
op.NOT(op.in_range(1.37, op.abs(lep.eta), 1.52)),
op.abs(lep.trackd0pvunbiased /
lep.tracksigd0pvunbiased) < 5)),
(lep.type == 13,
op.AND(
op.abs(lep.eta) < 2.5,
op.abs(lep.trackd0pvunbiased /
lep.tracksigd0pvunbiased) < 3)),
op.c_bool(False))))
metp4 = makePtEtaPhiEP4(tree.met.et, op.c_float(0.), tree.met.phi,
tree.met.et)
plots.append(
Plot.make1D("mt_w", (lep.p4 + metp4).Mt() / 1000.,
signalSel,
EqBin(40, 60., 180.),
title="m_{T}^{W#rightarrow l#nu} (GeV)",
plotopts={"log-y-axis-range": [25., 2.5e8]}))
return plots
def definePlots(self, tree, noSel, sample=None, sampleCfg=None):
from bamboo.plots import Plot
from bamboo.plots import EquidistantBinning as EqBin
from bamboo import treefunctions as op
plots = []
dimu_Z = op.combine(
tree.Muon,
N=2,
pred=(lambda mu1, mu2: op.AND(
mu1.charge != mu2.charge,
op.in_range(60., op.invariant_mass(mu1.p4, mu2.p4), 120.))))
hasDiMuZ = noSel.refine("hasDiMuZ", cut=(op.rng_len(dimu_Z) > 0))
plots.append(
Plot.make1D("dimuZ_MET",
tree.MET.pt,
hasDiMuZ,
EqBin(100, 0., 2000.),
title="MET (GeV)"))
return plots
def definePlots(self, t, noSel, sample=None, sampleCfg=None):
from bamboo.plots import Plot, CutFlowReport, EquidistantBinning, VariableBinning
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))
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))))
cleanedGoodJets30_0to1_5 = op.select(
cleanedJets, lambda j: op.AND(j.pt > 30,
op.abs(j.eta) < 1.5))
cleanedGoodJets30_1_5to3 = op.select(
cleanedJets, lambda j: op.AND(
j.pt > 30,
op.NOT(op.AND(op.abs(j.eta) < 1.5,
op.abs(j.eta) > 3))))
cleanedGoodJets30_3toInf = op.select(
cleanedJets, lambda j: op.AND(j.pt > 30,
op.abs(j.eta) > 3))
cleanedGoodJets50_0to1_5 = op.select(
cleanedJets, lambda j: op.AND(j.pt > 50,
op.abs(j.eta) < 1.5))
cleanedGoodJets50_1_5to3 = op.select(
cleanedJets, lambda j: op.AND(
j.pt > 50,
op.NOT(op.AND(op.abs(j.eta) < 1.5,
op.abs(j.eta) > 3))))
cleanedGoodJets50_3toInf = op.select(
cleanedJets, lambda j: op.AND(j.pt > 50,
op.abs(j.eta) > 3))
cleanedGoodJets100_0to1_5 = op.select(
cleanedJets, lambda j: op.AND(j.pt > 100,
op.abs(j.eta) < 1.5))
cleanedGoodJets100_1_5to3 = op.select(
cleanedJets, lambda j: op.AND(
j.pt > 100,
op.NOT(op.AND(op.abs(j.eta) < 1.5,
op.abs(j.eta) > 3))))
cleanedGoodJets100_3toInf = op.select(
cleanedJets, lambda j: op.AND(j.pt > 100,
op.abs(j.eta) > 3))
cleanedGoodJets30 = op.select(cleanedJets, lambda j: j.pt > 30)
cleanedGoodJets50 = op.select(cleanedJets, lambda j: j.pt > 50)
cleanedGoodJets100 = op.select(cleanedJets, lambda j: j.pt > 100)
met = op.select(t.metpuppi)
sel1 = noSel.refine("nJet30", cut=[op.rng_len(cleanedGoodJets30) > 0])
sel2 = noSel.refine("nJet50", cut=[op.rng_len(cleanedGoodJets50) > 0])
sel3 = noSel.refine("nJet100",
cut=[op.rng_len(cleanedGoodJets100) > 0])
sel1_1 = noSel.refine("nJet30_1",
cut=[op.rng_len(cleanedGoodJets30) > 0])
sel1_1_1 = noSel.refine("nJet30_1_1",
cut=[op.rng_len(cleanedGoodJets30_0to1_5) > 0])
sel1_1_2 = noSel.refine("nJet30_1_2",
cut=[op.rng_len(cleanedGoodJets30_1_5to3) > 0])
sel1_1_3 = noSel.refine("nJet30_1_3",
cut=[op.rng_len(cleanedGoodJets30_3toInf) > 0])
sel2_1 = noSel.refine("nJet50_1",
cut=[op.rng_len(cleanedGoodJets50) > 0])
sel1_2_1 = noSel.refine("nJet50_1_1",
cut=[op.rng_len(cleanedGoodJets50_0to1_5) > 0])
sel1_2_2 = noSel.refine("nJet50_1_2",
cut=[op.rng_len(cleanedGoodJets50_1_5to3) > 0])
sel1_2_3 = noSel.refine("nJet50_1_3",
cut=[op.rng_len(cleanedGoodJets50_3toInf) > 0])
sel3_1 = noSel.refine("nJet100_1",
cut=[op.rng_len(cleanedGoodJets100) > 0])
sel1_3_1 = noSel.refine(
"nJet100_1_1", cut=[op.rng_len(cleanedGoodJets100_0to1_5) > 0])
sel1_3_2 = noSel.refine(
"nJet100_1_2", cut=[op.rng_len(cleanedGoodJets100_1_5to3) > 0])
sel1_3_3 = noSel.refine(
"nJet100_1_3", cut=[op.rng_len(cleanedGoodJets100_3toInf) > 0])
sel1_2 = noSel.refine("nJet30_2",
cut=[op.rng_len(cleanedGoodJets30) > 1])
sel2_1_1 = noSel.refine("nJet30_2_1",
cut=[op.rng_len(cleanedGoodJets30_0to1_5) > 1])
sel2_1_2 = noSel.refine("nJet30_2_2",
cut=[op.rng_len(cleanedGoodJets30_1_5to3) > 1])
sel2_1_3 = noSel.refine("nJet30_2_3",
cut=[op.rng_len(cleanedGoodJets30_3toInf) > 1])
sel2_2 = noSel.refine("nJet50_2",
cut=[op.rng_len(cleanedGoodJets50) > 1])
sel2_2_1 = noSel.refine("nJet50_2_1",
cut=[op.rng_len(cleanedGoodJets50_0to1_5) > 1])
sel2_2_2 = noSel.refine("nJet50_2_2",
cut=[op.rng_len(cleanedGoodJets50_1_5to3) > 1])
sel2_2_3 = noSel.refine("nJet50_2_3",
cut=[op.rng_len(cleanedGoodJets50_3toInf) > 1])
sel3_2 = noSel.refine("nJet100_2",
cut=[op.rng_len(cleanedGoodJets100) > 1])
sel2_3_1 = noSel.refine(
"nJet100_2_1", cut=[op.rng_len(cleanedGoodJets100_0to1_5) > 1])
sel2_3_2 = noSel.refine(
"nJet100_2_2", cut=[op.rng_len(cleanedGoodJets100_1_5to3) > 1])
sel2_3_3 = noSel.refine(
"nJet100_2_3", cut=[op.rng_len(cleanedGoodJets100_3toInf) > 1])
sel1_3 = noSel.refine("nJet30_3",
cut=[op.rng_len(cleanedGoodJets30) > 2])
sel3_1_1 = noSel.refine("nJet30_3_1",
cut=[op.rng_len(cleanedGoodJets30_0to1_5) > 2])
sel3_1_2 = noSel.refine("nJet30_3_2",
cut=[op.rng_len(cleanedGoodJets30_1_5to3) > 2])
sel3_1_3 = noSel.refine("nJet30_3_3",
cut=[op.rng_len(cleanedGoodJets30_3toInf) > 2])
sel2_3 = noSel.refine("nJet50_3",
cut=[op.rng_len(cleanedGoodJets50) > 2])
sel3_2_1 = noSel.refine("nJet50_3_1",
cut=[op.rng_len(cleanedGoodJets50_0to1_5) > 2])
sel3_2_2 = noSel.refine("nJet50_3_2",
cut=[op.rng_len(cleanedGoodJets50_1_5to3) > 2])
sel3_2_3 = noSel.refine("nJet50_3_3",
cut=[op.rng_len(cleanedGoodJets50_3toInf) > 2])
sel3_3 = noSel.refine("nJet100_3",
cut=[op.rng_len(cleanedGoodJets100) > 2])
sel3_3_1 = noSel.refine(
"nJet100_3_1", cut=[op.rng_len(cleanedGoodJets100_0to1_5) > 2])
sel3_3_2 = noSel.refine(
"nJet100_3_2", cut=[op.rng_len(cleanedGoodJets100_1_5to3) > 2])
sel3_3_3 = noSel.refine(
"nJet100_3_3", cut=[op.rng_len(cleanedGoodJets100_3toInf) > 2])
sel1_4 = noSel.refine("nJet30_4",
cut=[op.rng_len(cleanedGoodJets30) > 3])
sel4_1_1 = noSel.refine("nJet30_4_1",
cut=[op.rng_len(cleanedGoodJets30_0to1_5) > 3])
sel4_1_2 = noSel.refine("nJet30_4_2",
cut=[op.rng_len(cleanedGoodJets30_1_5to3) > 3])
sel4_1_3 = noSel.refine("nJet30_4_3",
cut=[op.rng_len(cleanedGoodJets30_3toInf) > 3])
sel2_4 = noSel.refine("nJet50_4",
cut=[op.rng_len(cleanedGoodJets50) > 3])
sel4_2_1 = noSel.refine("nJet50_4_1",
cut=[op.rng_len(cleanedGoodJets50_0to1_5) > 3])
sel4_2_2 = noSel.refine("nJet50_4_2",
cut=[op.rng_len(cleanedGoodJets50_1_5to3) > 3])
sel4_2_3 = noSel.refine("nJet50_4_3",
cut=[op.rng_len(cleanedGoodJets50_3toInf) > 3])
sel3_4 = noSel.refine("nJet100_4",
cut=[op.rng_len(cleanedGoodJets100) > 3])
sel4_3_1 = noSel.refine(
"nJet100_4_1", cut=[op.rng_len(cleanedGoodJets100_0to1_5) > 3])
sel4_3_2 = noSel.refine(
"nJet100_4_2", cut=[op.rng_len(cleanedGoodJets100_1_5to3) > 3])
sel4_3_3 = noSel.refine(
"nJet100_4_3", cut=[op.rng_len(cleanedGoodJets100_3toInf) > 3])
# plots
# # ### 30 GeV
plots.append(
Plot.make1D("nJets_jetPT_30GeV",
op.rng_len(cleanedGoodJets30),
noSel,
EquidistantBinning(15, 0., 15.),
title="nJets (jet p_{T} > 30GeV)"))
plots.append(
Plot.make1D("Jet1_pT_jetPT_30GeV",
cleanedGoodJets30[0].pt,
sel1_1,
EquidistantBinning(50, 0., 4000.),
title="Jet1_pT (jet p_{T} > 30GeV)"))
plots.append(
Plot.make1D("Jet1_eta_jetPT_30GeV",
cleanedGoodJets30[0].eta,
sel1_1,
EquidistantBinning(30, -3, 3),
title="Jet1_eta (jet p_{T} > 30GeV)"))
plots.append(
Plot.make1D("Jet1_pT_0to1_5_jetPT_30GeV",
cleanedGoodJets30_0to1_5[0].pt,
sel1_1_1,
EquidistantBinning(50, 0, 4000),
title="Jet1_pT 0 < eta < 1.5, (jet p_{T} > 30GeV)"))
plots.append(
Plot.make1D("Jet1_pT_1_5to3_jetPT_30GeV",
cleanedGoodJets30_1_5to3[0].pt,
sel1_1_2,
EquidistantBinning(50, 0, 4000),
title="Jet1_pT 1.5 < eta < 3, (jet p_{T} > 30GeV)"))
plots.append(
Plot.make1D("Jet1_pT_3toInf_jetPT_30GeV",
cleanedGoodJets30_3toInf[0].pt,
sel1_1_3,
EquidistantBinning(50, 0, 1000),
title="Jet1_pT eta > 3, (jet p_{T} > 30GeV)"))
plots.append(
Plot.make1D("Jet2_pT_jetPT_30GeV",
cleanedGoodJets30[1].pt,
sel1_2,
EquidistantBinning(50, 0., 4000.),
title="Jet2_pT (jet p_{T} > 30GeV)"))
plots.append(
Plot.make1D("Jet2_eta_jetPT_30GeV",
cleanedGoodJets30[1].eta,
sel1_2,
EquidistantBinning(30, -3, 3),
title="Jet2_eta (jet p_{T} > 30GeV)"))
plots.append(
Plot.make1D("Jet2_pT_0to1_5_jetPT_30GeV",
cleanedGoodJets30_0to1_5[1].pt,
sel2_1_1,
EquidistantBinning(50, 0, 4000),
title="Jet2_pT 0 < eta < 1.5, (jet p_{T} > 30GeV)"))
plots.append(
Plot.make1D("Jet2_pT_1_5to3_jetPT_30GeV",
cleanedGoodJets30_1_5to3[1].pt,
sel2_1_2,
EquidistantBinning(50, 0, 4000),
title="Jet2_pT 1.5 < eta < 3, (jet p_{T} > 30GeV)"))
plots.append(
Plot.make1D("Jet2_pT_3toInf_jetPT_30GeV",
cleanedGoodJets30_3toInf[1].pt,
sel2_1_3,
EquidistantBinning(50, 0, 500),
title="Jet2_pT eta > 3, (jet p_{T} > 30GeV)"))
plots.append(
Plot.make1D("Jet3_pT_jetPT_30GeV",
cleanedGoodJets30[2].pt,
sel1_3,
EquidistantBinning(50, 0., 2000.),
title="Jet3_pT (jet p_{T} > 30GeV)"))
plots.append(
Plot.make1D("Jet3_eta_jetPT_30GeV",
cleanedGoodJets30[2].eta,
sel1_3,
EquidistantBinning(30, -3, 3),
title="Jet3_eta (jet p_{T} > 30GeV)"))
plots.append(
Plot.make1D("Jet3_pT_0to1_5_jetPT_30GeV",
cleanedGoodJets30_0to1_5[2].pt,
sel3_1_1,
EquidistantBinning(50, 0, 2000),
title="Jet3_pT 0 < eta < 1.5, (jet p_{T} > 30GeV)"))
plots.append(
Plot.make1D("Jet3_pT_1_5to3_jetPT_30GeV",
cleanedGoodJets30_1_5to3[2].pt,
sel3_1_2,
EquidistantBinning(50, 0, 2000),
title="Jet3_pT 1.5 < eta < 3, (jet p_{T} > 30GeV)"))
plots.append(
Plot.make1D("Jet3_pT_3toInf_jetPT_30GeV",
cleanedGoodJets30_3toInf[2].pt,
sel3_1_3,
EquidistantBinning(50, 0, 200),
title="Jet3_pT eta > 3, (jet p_{T} > 30GeV)"))
plots.append(
Plot.make1D("Jet4_pT_jetPT_30GeV",
cleanedGoodJets30[3].pt,
sel1_4,
EquidistantBinning(50, 0., 2000.),
title="Jet4_pT (jet p_{T} > 30GeV)"))
plots.append(
Plot.make1D("Jet4_eta_jetPT_30GeV",
cleanedGoodJets30[3].eta,
sel1_4,
EquidistantBinning(30, -3, 3),
title="Jet4_eta (jet p_{T} > 30GeV)"))
plots.append(
Plot.make1D("Jet4_pT_0to1_5_jetPT_30GeV",
cleanedGoodJets30_0to1_5[3].pt,
sel4_1_1,
EquidistantBinning(50, 0, 2000),
title="Jet4_pT 0 < eta < 1.5, (jet p_{T} > 30GeV)"))
plots.append(
Plot.make1D("Jet4_pT_1_5to3_jetPT_30GeV",
cleanedGoodJets30_1_5to3[3].pt,
sel4_1_2,
EquidistantBinning(50, 0, 2000),
title="Jet4_pT 1.5 < eta < 3, (jet p_{T} > 30GeV)"))
plots.append(
Plot.make1D("Jet4_pT_3toInf_jetPT_30GeV",
cleanedGoodJets30_3toInf[3].pt,
sel4_1_3,
EquidistantBinning(50, 0, 200),
title="Jet4_pT eta > 3, (jet p_{T} > 30GeV)"))
plots.append(
Plot.make1D("MET_jetPT_30GeV",
met[0].pt,
sel1,
EquidistantBinning(50, 0, 1000),
title="MET (jet p_{T} > 30GeV)"))
# # ### 50 GeV
plots.append(
Plot.make1D("nJets_jetPT_50GeV",
op.rng_len(cleanedGoodJets50),
noSel,
EquidistantBinning(15, 0., 15.),
title="nJets (jet p_{T} > 50GeV)"))
plots.append(
Plot.make1D("Jet1_pT_jetPT_50GeV",
cleanedGoodJets50[0].pt,
sel2_1,
EquidistantBinning(50, 0., 4000.),
title="Jet1_pT (jet p_{T} > 50GeV)"))
plots.append(
Plot.make1D("Jet1_eta_jetPT_50GeV",
cleanedGoodJets50[0].eta,
sel2_1,
EquidistantBinning(30, -3, 3),
title="Jet1_eta (jet p_{T} > 50GeV)"))
plots.append(
Plot.make1D("Jet1_pT_0to1_5_jetPT_50GeV",
cleanedGoodJets50_0to1_5[0].pt,
sel1_2_1,
EquidistantBinning(50, 0, 4000),
title="Jet1_pT 0 < eta < 1.5, (jet p_{T} > 50GeV)"))
plots.append(
Plot.make1D("Jet1_pT_1_5to3_jetPT_50GeV",
cleanedGoodJets50_1_5to3[0].pt,
sel1_2_2,
EquidistantBinning(50, 0, 4000),
title="Jet1_pT 1.5 < eta < 3, (jet p_{T} > 50GeV)"))
plots.append(
Plot.make1D("Jet1_pT_3toInf_jetPT_50GeV",
cleanedGoodJets50_3toInf[0].pt,
sel1_2_3,
EquidistantBinning(50, 0, 1000),
title="Jet1_pT eta > 3, (jet p_{T} > 50GeV)"))
plots.append(
Plot.make1D("Jet2_pT_jetPT_50GeV",
cleanedGoodJets50[1].pt,
sel2_2,
EquidistantBinning(50, 0., 4000.),
title="Jet2_pT (jet p_{T} > 50GeV)"))
plots.append(
Plot.make1D("Jet2_eta_jetPT_50GeV",
cleanedGoodJets50[1].eta,
sel2_2,
EquidistantBinning(30, -3, 3),
title="Jet2_eta (jet p_{T} > 50GeV)"))
plots.append(
Plot.make1D("Jet2_pT_0to1_5_jetPT_50GeV",
cleanedGoodJets50_0to1_5[1].pt,
sel2_2_1,
EquidistantBinning(50, 0, 4000),
title="Jet2_pT 0 < eta < 1.5, (jet p_{T} > 50GeV)"))
plots.append(
Plot.make1D("Jet2_pT_1_5to3_jetPT_50GeV",
cleanedGoodJets50_1_5to3[1].pt,
sel2_2_2,
EquidistantBinning(50, 0, 4000),
title="Jet2_pT 1.5 < eta < 3, (jet p_{T} > 50GeV)"))
plots.append(
Plot.make1D("Jet2_pT_3toInf_jetPT_50GeV",
cleanedGoodJets50_3toInf[1].pt,
sel2_2_3,
EquidistantBinning(50, 0, 500),
title="Jet2_pT eta > 3, (jet p_{T} > 50GeV)"))
plots.append(
Plot.make1D("Jet3_pT_jetPT_50GeV",
cleanedGoodJets50[2].pt,
sel2_3,
EquidistantBinning(50, 0., 2000.),
title="Jet3_pT (jet p_{T} > 50GeV)"))
plots.append(
Plot.make1D("Jet3_eta_jetPT_50GeV",
cleanedGoodJets50[2].eta,
sel2_3,
EquidistantBinning(30, -3, 3),
title="Jet3_eta (jet p_{T} > 50GeV)"))
plots.append(
Plot.make1D("Jet3_pT_0to1_5_jetPT_50GeV",
cleanedGoodJets50_0to1_5[2].pt,
sel3_2_1,
EquidistantBinning(50, 0, 2000),
title="Jet3_pT 0 < eta < 1.5, (jet p_{T} > 50GeV)"))
plots.append(
Plot.make1D("Jet3_pT_1_5to3_jetPT_50GeV",
cleanedGoodJets50_1_5to3[2].pt,
sel3_2_2,
EquidistantBinning(50, 0, 2000),
title="Jet3_pT 1.5 < eta < 3, (jet p_{T} > 50GeV)"))
plots.append(
Plot.make1D("Jet3_pT_3toInf_jetPT_50GeV",
cleanedGoodJets50_3toInf[2].pt,
sel3_2_3,
EquidistantBinning(50, 0, 200),
title="Jet3_pT eta > 3, (jet p_{T} > 50GeV)"))
plots.append(
Plot.make1D("Jet4_pT_jetPT_50GeV",
cleanedGoodJets50[3].pt,
sel2_4,
EquidistantBinning(50, 0., 2000.),
title="Jet4_pT (jet p_{T} > 50GeV)"))
plots.append(
Plot.make1D("Jet4_eta_jetPT_50GeV",
cleanedGoodJets50[3].eta,
sel2_4,
EquidistantBinning(30, -3, 3),
title="Jet4_eta (jet p_{T} > 50GeV)"))
plots.append(
Plot.make1D("Jet4_pT_0to1_5_jetPT_50GeV",
cleanedGoodJets50_0to1_5[3].pt,
sel4_2_1,
EquidistantBinning(50, 0, 2000),
title="Jet4_pT 0 < eta < 1.5, (jet p_{T} > 30GeV)"))
plots.append(
Plot.make1D("Jet4_pT_1_5to3_jetPT_50GeV",
cleanedGoodJets50_1_5to3[3].pt,
sel4_2_2,
EquidistantBinning(50, 0, 2000),
title="Jet4_pT 1.5 < eta < 3, (jet p_{T} > 50GeV)"))
plots.append(
Plot.make1D("Jet4_pT_3toInf_jetPT_50GeV",
cleanedGoodJets50_3toInf[3].pt,
sel4_2_3,
EquidistantBinning(50, 0, 200),
title="Jet4_pT eta > 3, (jet p_{T} > 50GeV)"))
plots.append(
Plot.make1D("MET_jetPT_50GeV",
met[0].pt,
sel2,
EquidistantBinning(50, 0, 1000),
title="MET (jet p_{T} > 50GeV)"))
# ### 100 GeV
plots.append(
Plot.make1D("nJets_jetPT_100GeV",
op.rng_len(cleanedGoodJets100),
noSel,
EquidistantBinning(15, 0., 15.),
title="nJets (jet p_{T} > 100GeV)"))
plots.append(
Plot.make1D("Jet1_pT_jetPT_100GeV",
cleanedGoodJets100[0].pt,
sel3_1,
EquidistantBinning(50, 0., 4000.),
title="Jet1_pT (jet p_{T} > 100GeV)"))
plots.append(
Plot.make1D("Jet1_eta_jetPT_100GeV",
cleanedGoodJets100[0].eta,
sel3_1,
EquidistantBinning(30, -3, 3),
title="Jet1_eta (jet p_{T} > 100GeV)"))
plots.append(
Plot.make1D("Jet1_pT_0to1_5_jetPT_100GeV",
cleanedGoodJets100_0to1_5[0].pt,
sel1_3_1,
EquidistantBinning(50, 0, 4000),
title="Jet1_pT 0 < eta < 1.5, (jet p_{T} > 100GeV)"))
plots.append(
Plot.make1D("Jet1_pT_1_5to3_jetPT_100GeV",
cleanedGoodJets100_1_5to3[0].pt,
sel1_3_2,
EquidistantBinning(50, 0, 4000),
title="Jet1_pT 1.5 < eta < 3, (jet p_{T} > 100GeV)"))
plots.append(
Plot.make1D("Jet1_pT_3toInf_jetPT_100GeV",
cleanedGoodJets100_3toInf[0].pt,
sel1_3_3,
EquidistantBinning(50, 0, 1000),
title="Jet1_pT eta > 3, (jet p_{T} > 100GeV)"))
plots.append(
Plot.make1D("Jet2_pT_jetPT_100GeV",
cleanedGoodJets100[1].pt,
sel3_2,
EquidistantBinning(50, 0., 4000.),
title="Jet2_pT (jet p_{T} > 100GeV)"))
plots.append(
Plot.make1D("Jet2_eta_jetPT_100GeV",
cleanedGoodJets100[1].eta,
sel3_2,
EquidistantBinning(30, -3, 3),
title="Jet2_eta (jet p_{T} > 100GeV)"))
plots.append(
Plot.make1D("Jet2_pT_0to1_5_jetPT_100GeV",
cleanedGoodJets100_0to1_5[1].pt,
sel2_3_1,
EquidistantBinning(50, 0, 4000),
title="Jet2_pT 0 < eta < 1.5, (jet p_{T} > 100GeV)"))
plots.append(
Plot.make1D("Jet2_pT_1_5to3_jetPT_100GeV",
cleanedGoodJets100_1_5to3[1].pt,
sel2_3_2,
EquidistantBinning(50, 0, 4000),
title="Jet2_pT 1.5 < eta < 3, (jet p_{T} > 100GeV)"))
plots.append(
Plot.make1D("Jet2_pT_3toInf_jetPT_100GeV",
cleanedGoodJets100_3toInf[1].pt,
sel2_3_3,
EquidistantBinning(50, 0, 500),
title="Jet2_pT eta > 3, (jet p_{T} > 100GeV)"))
plots.append(
Plot.make1D("Jet3_pT_jetPT_100GeV",
cleanedGoodJets100[2].pt,
sel3_3,
EquidistantBinning(50, 0., 2000.),
title="Jet3_pT (jet p_{T} > 100GeV)"))
plots.append(
Plot.make1D("Jet3_eta_jetPT_100GeV",
cleanedGoodJets100[2].eta,
sel3_3,
EquidistantBinning(30, -3, 3),
title="Jet3_eta (jet p_{T} > 100GeV)"))
plots.append(
Plot.make1D("Jet3_pT_0to1_5_jetPT_100GeV",
cleanedGoodJets100_0to1_5[2].pt,
sel3_3_1,
EquidistantBinning(50, 0, 2000),
title="Jet3_pT 0 < eta < 1.5, (jet p_{T} > 100GeV)"))
plots.append(
Plot.make1D("Jet3_pT_1_5to3_jetPT_100GeV",
cleanedGoodJets100_1_5to3[2].pt,
sel3_3_2,
EquidistantBinning(50, 0, 2000),
title="Jet3_pT 1.5 < eta < 3, (jet p_{T} > 100GeV)"))
plots.append(
Plot.make1D("Jet3_pT_3toInf_jetPT_100GeV",
cleanedGoodJets100_3toInf[2].pt,
sel3_3_3,
EquidistantBinning(50, 0, 200),
title="Jet3_pT eta > 3, (jet p_{T} > 100GeV)"))
plots.append(
Plot.make1D("Jet4_pT_jetPT_100GeV",
cleanedGoodJets100[3].pt,
sel3_4,
EquidistantBinning(50, 0., 2000.),
title="Jet4_pT (jet p_{T} > 100GeV)"))
plots.append(
Plot.make1D("Jet4_eta_jetPT_100GeV",
cleanedGoodJets100[3].eta,
sel3_4,
EquidistantBinning(30, -3, 3),
title="Jet4_eta (jet p_{T} > 100GeV)"))
plots.append(
Plot.make1D("Jet4_pT_0to1_5_jetPT_100GeV",
cleanedGoodJets100_0to1_5[3].pt,
sel4_3_1,
EquidistantBinning(50, 0, 2000),
title="Jet4_pT 0 < eta < 1.5, (jet p_{T} > 100GeV)"))
plots.append(
Plot.make1D("Jet4_pT_1_5to3_jetPT_100GeV",
cleanedGoodJets100_1_5to3[3].pt,
sel4_3_2,
EquidistantBinning(50, 0, 2000),
title="Jet4_pT 1.5 < eta < 3, (jet p_{T} > 100GeV)"))
plots.append(
Plot.make1D("Jet4_pT_3toInf_jetPT_100GeV",
cleanedGoodJets100_3toInf[3].pt,
sel4_3_3,
EquidistantBinning(50, 0, 200),
title="Jet4_pT eta > 3, (jet p_{T} > 100GeV)"))
plots.append(
Plot.make1D("MET_jetPT_100GeV",
met[0].pt,
sel3,
EquidistantBinning(50, 0, 1000),
title="MET (jet p_{T} > 100GeV)"))
# Efficiency Report on terminal and the .tex output
cfr = CutFlowReport("yields")
cfr.add(noSel, "None")
cfr.add(sel1, "30GeV")
cfr.add(sel2, "50GeV")
cfr.add(sel3, "100GeV")
plots.append(cfr)
return plots
def makeJetsPlots(self, sel, jets, suffix, channel):
"""
Make basic plots
sel = refine selection
jets = bjet container with len(jets)>=1 (we require at least one bjet)
suffix = string identifying the selecton
channel = string identifying the channel of the dilepton (can be "NoChannel")
"""
plots = []
# bjet 1 plots (always present by selection) #
plots.append(
Plot.make1D("%s_leadjetPT_%s" % (channel, suffix),
jets[0].p4.Pt(),
sel,
EquidistantBinning(100, 0, 300.),
title='Transverse momentum of the leading jet',
xTitle="P_{T}(leading jet) [GeV]"))
plots.append(
Plot.make1D("%s_leadjetEta_%s" % (channel, suffix),
jets[0].p4.Eta(),
sel,
EquidistantBinning(20, -3., 3.),
title='Transverse momentum of the leading jet',
xTitle="#eta(leading jet) [GeV]"))
plots.append(
Plot.make1D("%s_leadjetPhi_%s" % (channel, suffix),
jets[0].p4.Phi(),
sel,
EquidistantBinning(20, -3.2, 3.2),
title='Azimutal angle of the leading jet',
xTitle="#phi(leading jet) [GeV]"))
# bjet 2 plots (not necessarily present) #
hasAtLeastTwoBJets = sel.refine("hasAtLeastTwoBJets_%s_%s" %
(channel, suffix),
cut=[op.rng_len(jets) >= 2])
hasOnlyOneBJet = sel.refine("hasAtLeast2BJets_%s_%s" % (channel, suffix),
cut=[op.rng_len(jets) == 1])
# Fill a specific bin apart so that the information is not lost
# PT plot #
plot_hasTwoBJets_PT = Plot.make1D(
"%s_hasSubleadjetPT_%s" % (channel, suffix),
jets[1].p4.Pt(),
hasAtLeastTwoBJets,
EquidistantBinning(100, -10., 300.),
title='Transverse momentum of the subleading jet',
xTitle="P_{T}(subleading jet) [GeV]")
plot_notTwoBJets_PT = Plot.make1D(
"%s_notSubleadjetPT_%s" % (channel, suffix),
op.c_float(-10.),
hasOnlyOneBJet,
EquidistantBinning(100, -10., 300.),
title='Transverse momentum of the subleading jet',
xTitle="P_{T}(subleading jet) [GeV]")
plots.append(
SummedPlot("%s_subleadjetPT_%s" % (channel, suffix),
[plot_hasTwoBJets_PT, plot_notTwoBJets_PT],
xTitle="P_{T}(subleading jet) [GeV]"))
# Eta plot #
plot_hasTwoBJets_Eta = Plot.make1D(
"%s_hasSubleadjetEta_%s" % (channel, suffix),
jets[1].p4.Eta(),
hasAtLeastTwoBJets,
EquidistantBinning(20, -3., 3.),
title='Pseudorapidity of the subleading jet',
xTitle="#eta(subleading jet) [GeV]")
plot_notTwoBJets_Eta = Plot.make1D(
"%s_notSubleadjetEta_%s" % (channel, suffix),
op.c_float(-3.),
hasOnlyOneBJet,
EquidistantBinning(20, -3., 3.),
title='Pseudorapidity of the subleading jet',
xTitle="#eta(subleading jet) [GeV]")
plots.append(
SummedPlot("%s_subleadjetEta_%s" % (channel, suffix),
[plot_hasTwoBJets_Eta, plot_notTwoBJets_Eta],
xTitle="#eta(subleading jet) [GeV]"))
# Phi plot #
plot_hasTwoBJets_Phi = Plot.make1D(
"%s_hasSubleadjetPhi_%s" % (channel, suffix),
jets[1].p4.Phi(),
hasAtLeastTwoBJets,
EquidistantBinning(20, -3.2, 3.2),
title='Azimutal angle of the subleading jet',
xTitle="#phi(subleading jet) [GeV]")
plot_notTwoBJets_Phi = Plot.make1D(
"%s_notSubleadjetPhi_%s" % (channel, suffix),
op.c_float(-3.2),
hasOnlyOneBJet,
EquidistantBinning(20, -3.2, 3.2),
title='Azimutal angle of the subleading jet',
xTitle="#phi(subleading jet) [GeV]")
plots.append(
SummedPlot("%s_subleadjetPhi_%s" % (channel, suffix),
[plot_hasTwoBJets_Phi, plot_notTwoBJets_Phi],
xTitle="#phi(subleading jet) [GeV]"))
# InvMass plot #
plot_hasTwoBJets_invMass = Plot.make1D(
"%s_hasTwoBJets_invMass_%s" % (channel, suffix),
op.invariant_mass(jets[0].p4, jets[1].p4),
hasAtLeastTwoBJets,
EquidistantBinning(100, -10, 500.),
title="Dijet invariant mass (channel %s)" % channel,
xTitle="Invariant mass [GeV]")
plot_notTwoBJets_invMass = Plot.make1D(
"%s_notTwoBJets_invMass_%s" % (channel, suffix),
op.c_float(-10.),
hasAtLeastTwoBJets,
EquidistantBinning(100, -10, 500.),
title="Dijet invariant mass (channel %s)" % channel,
xTitle="Invariant mass [GeV]")
plots.append(
SummedPlot("%s_dijetInvariantMass_%s" % (channel, suffix),
[plot_hasTwoBJets_invMass, plot_notTwoBJets_invMass],
xTitle="Invariant mass [GeV]"))
return plots
def returnHighLevelMVAInputs(self,l1,l2,met,jets,bjets,electrons,muons,channel):
if channel == "ElEl":
cone_l1 = self.getElectronConeP4(l1)
cone_l2 = self.getElectronConeP4(l2)
elif channel == "MuMu":
cone_l1 = self.getMuonConeP4(l1)
cone_l2 = self.getMuonConeP4(l2)
elif channel == "ElMu":
cone_l1 = self.getElectronConeP4(l1)
cone_l2 = self.getMuonConeP4(l2)
else:
raise RuntimeError("Wrong channel")
dijets = op.combine(jets, N=2)
import bamboo.treeoperations as _to
def rng_min(rng, fun=(lambda x : x), typeName="float"):
return op._to.Reduce.fromRngFun(rng, op.c_float(float("+inf"), typeName), ( lambda fn : (
lambda res, elm : op.extMethod("std::min", returnType="Float_t")(res, fn(elm))
) )(fun) )
if self.args.Boosted0Btag or self.args.Boosted1Btag:
VBFJetPairs = self.VBFJetPairsBoosted
elif self.args.Resolved0Btag or self.args.Resolved1Btag or self.args.Resolved2Btag:
VBFJetPairs = self.VBFJetPairsResolved
else:
raise RuntimeError("Wrong selection to be used by the DNN")
return {
('m_bb_bregcorr', 'Di-bjet invariant mass (regcorr) [GeV]', (100,0.,1000.)) : op.multiSwitch((op.rng_len(bjets) == 0, op.c_float(0.)),
(op.rng_len(bjets) == 1, self.HLL.getCorrBp4(bjets[0]).M()),
op.invariant_mass(self.HLL.getCorrBp4(bjets[0]),self.HLL.getCorrBp4(bjets[1]))),
('ht', 'HT(jets) [GeV]', (100,0.,1000.)) : op.rng_sum(jets, lambda j : j.pt),
('min_dr_jets_lep1', 'Min(#Delta R(lead lepton,jets))', (25,0.,5.)) : op.switch(op.rng_len(jets) > 0,
op.switch(cone_l1.Pt() >= cone_l2.Pt(),
self.HLL.MinDR_part1_partCont(cone_l1,jets),
self.HLL.MinDR_part1_partCont(cone_l2,jets)),
op.c_float(0.)),
('min_dr_jets_lep2', 'Min(#Delta R(sublead lepton,jets))', (25,0.,5.)) : op.switch(op.rng_len(jets) > 0,
op.switch(cone_l1.Pt() >= cone_l2.Pt(),
self.HLL.MinDR_part1_partCont(cone_l2,jets),
self.HLL.MinDR_part1_partCont(cone_l1,jets)),
op.c_float(0.)),
('m_ll', 'Dilepton invariant mass [GeV]', (100,0.,1000.)) : op.invariant_mass(cone_l1,cone_l2),
('dr_ll', 'Dilepton #Delta R', (25,0.,5.)) : op.deltaR(cone_l1,cone_l2),
('min_dr_jet', 'Min(#Delta R(jets))', (25,0.,5.)) : op.switch(op.rng_len(dijets) > 0,
op.rng_min(dijets,lambda dijet : op.deltaR(dijet[0].p4,dijet[1].p4)),
op.c_float(0.)),
('min_dhi_jet', 'Min(#Delta #Phi(jets))', (16,0.,3.2)) : op.switch(op.rng_len(dijets) > 0,
rng_min(dijets,lambda dijet : op.abs(op.deltaPhi(dijet[0].p4,dijet[1].p4)),typeName='double'),
op.c_float(0.)),
('m_hh_simplemet_bregcorr','M_{HH} (simple MET) (regcorr) [GeV]', (100,0.,1000.)) : op.invariant_mass(op.rng_sum(bjets,
lambda bjet : self.HLL.getCorrBp4(bjet),
start=self.HLL.empty_p4),
cone_l1,
cone_l2,
met.p4),
('met_ld', 'MET_{LD}', (100,0.,1000.)) : self.HLL.MET_LD_DL(met,jets,electrons,muons),
('dr_bb', 'Di-bjet #Delta R', (25,0.,5.)) : op.switch(op.rng_len(bjets)>=2,
op.deltaR(bjets[0].p4,bjets[1].p4),
op.c_float(0.)),
('min_dr_leps_b1', 'Min(#Delta R(lead bjet,dilepton))', (25,0.,5.)) : op.switch(op.rng_len(bjets)>=1,
self.HLL.MinDR_part1_dipart(bjets[0].p4,[cone_l1,cone_l2]),
op.c_float(0.)),
('min_dr_leps_b2', 'Min(#Delta R(sublead bjet,dilepton))', (25,0.,5.)) : op.switch(op.rng_len(bjets)>=2,
self.HLL.MinDR_part1_dipart(bjets[1].p4,[cone_l1,cone_l2]),
op.c_float(0.)),
('lep1_conept', 'Lead lepton cone-P_T [GeV]', (40,0.,200.)) : op.switch(cone_l1.Pt() >= cone_l2.Pt() , cone_l1.Pt() , cone_l2.Pt()),
('lep2_conept', 'Sublead lepton cone-P_T [GeV]', (40,0.,200.)) : op.switch(cone_l1.Pt() >= cone_l2.Pt() , cone_l2.Pt() , cone_l1.Pt()),
('mww_simplemet', 'M_{WW} (simple MET) [GeV]', (100,0.,1000.)) : op.invariant_mass(cone_l1,cone_l2,met.p4),
('vbf_tag', 'VBF tag', (2,0.,2.)) : op.c_int(op.rng_len(VBFJetPairs)>0),
('boosted_tag', 'Boosted tag', (2,0.,2.)) : op.c_int(op.OR(op.rng_len(self.ak8BJets) > 0, # Boosted 1B
op.AND(op.rng_len(self.ak8BJets) == 0, # Boosted 0B
op.rng_len(self.ak8Jets) > 0,
op.rng_len(self.ak4BJets) == 0))),
('dphi_met_dilep', 'Dilepton-MET #Delta #Phi', (32,-3.2,3.2)) : op.abs(op.deltaPhi(met.p4,(cone_l1+cone_l2))),
('dphi_met_dibjet', 'Dibjet-MET #Delta #Phi', (32,-3.2,3.2)) : op.multiSwitch((op.rng_len(bjets) == 0, op.c_float(0.)),
(op.rng_len(bjets) == 1, op.abs(op.deltaPhi(met.p4,bjets[0].p4))),
op.abs(op.deltaPhi(met.p4,(bjets[0].p4+bjets[1].p4)))),
('dr_dilep_dijet', 'Dilepton-dijet #Delta R', (25,0.,5.)) : op.multiSwitch((op.rng_len(jets) == 0, op.c_float(0.)),
(op.rng_len(jets) == 1, op.deltaR((cone_l1+cone_l2),jets[0].p4)),
op.deltaR((cone_l1+cone_l2),(jets[0].p4+jets[1].p4))),
('dr_dilep_dibjet', 'Dilepton-dibjet #Delta R', (25,0.,5.)) : op.multiSwitch((op.rng_len(bjets) == 0, op.c_float(0.)),
(op.rng_len(bjets) == 1, op.deltaR((cone_l1+cone_l2),bjets[0].p4)),
op.deltaR((cone_l1+cone_l2),(bjets[0].p4+bjets[1].p4))),
('vbf_pair_mass', 'VBF pair M_{jj}', (100,0.,1000.)) : op.switch(op.rng_len(VBFJetPairs)>0,
op.invariant_mass(VBFJetPairs[0][0].p4,VBFJetPairs[0][1].p4),
op.c_float(0.)),
('vbf_pairs_absdeltaeta', 'VBF pair #Delta#eta', (25,0.,5.)) : op.switch(op.rng_len(VBFJetPairs)>0,
op.abs(VBFJetPairs[0][0].eta-VBFJetPairs[0][1].eta),
op.c_float(0.)),
('sphericity', 'None', (1,0.,1.)) : op.c_float(0.),
('sphericity_T', 'None', (1,0.,1.)) : op.c_float(0.),
('aplanarity', 'None', (1,0.,1.)) : op.c_float(0.),
('eventshape_C', 'None', (1,0.,1.)) : op.c_float(0.),
('eventshape_D', 'None', (1,0.,1.)) : op.c_float(0.),
('eventshape_Y', 'None', (1,0.,1.)) : op.c_float(0.),
('foxwolfram1', 'None', (1,0.,1.)) : op.c_float(0.),
('foxwolfram2', 'None', (1,0.,1.)) : op.c_float(0.),
('foxwolfram3', 'None', (1,0.,1.)) : op.c_float(0.),
('foxwolfram4', 'None', (1,0.,1.)) : op.c_float(0.),
('foxwolfram5', 'None', (1,0.,1.)) : op.c_float(0.),
('centrality', 'None', (1,0.,1.)) : op.c_float(0.),
('centrality_jets', 'None', (1,0.,1.)) : op.c_float(0.),
('eigenvalue1', 'None', (1,0.,1.)) : op.c_float(0.),
('eigenvalue2', 'None', (1,0.,1.)) : op.c_float(0.),
('eigenvalue3', 'None', (1,0.,1.)) : op.c_float(0.),
}
def definePlots(self, t, noSel, sample=None, sampleCfg=None):
# Some imports #
from bamboo.analysisutils import forceDefine
era = sampleCfg['era']
# Get pile-up configs #
puWeightsFile = None
if era == "2016":
sfTag = "94X"
puWeightsFile = os.path.join(os.path.dirname(__file__), "data",
"puweights2016.json")
elif era == "2017":
sfTag = "94X"
puWeightsFile = os.path.join(os.path.dirname(__file__), "data",
"puweights2017.json")
elif era == "2018":
sfTag = "102X"
puWeightsFile = os.path.join(os.path.dirname(__file__), "data",
"puweights2018.json")
if self.isMC(sample) and puWeightsFile is not None:
from bamboo.analysisutils import makePileupWeight
noSel = noSel.refine("puWeight",
weight=makePileupWeight(puWeightsFile,
t.Pileup_nTrueInt,
systName="pileup"))
isMC = self.isMC(sample)
plots = []
forceDefine(t._Muon.calcProd, noSel)
#############################################################################
################################ Muons #####################################
#############################################################################
# Wp // 2016- 2017 -2018 : Muon_mediumId // https://twiki.cern.ch/twiki/bin/view/CMS/SWGuideMuonIdRun2#Muon_Isolation
muonsByPt = op.sort(t.Muon, lambda mu: -mu.p4.Pt())
muons = op.select(
muonsByPt, lambda mu: op.AND(mu.p4.Pt() > 10.,
op.abs(mu.p4.Eta()) < 2.4, mu.tightId,
mu.pfRelIso04_all < 0.15))
# Scalefactors #
#if era=="2016":
# doubleMuTrigSF = get_scalefactor("dilepton", ("doubleMuLeg_HHMoriond17_2016"), systName="mumutrig")
# muMediumIDSF = get_scalefactor("lepton", ("muon_{0}_{1}".format(era, sfTag), "id_medium"), combine="weight", systName="muid")
# muMediumISOSF = get_scalefactor("lepton", ("muon_{0}_{1}".format(era, sfTag), "iso_tight_id_medium"), combine="weight", systName="muiso")
# TrkIDSF = get_scalefactor("lepton", ("muon_{0}_{1}".format(era, sfTag), "highpt"), combine="weight")
# TrkISOSF = get_scalefactor("lepton", ("muon_{0}_{1}".format(era, sfTag), "isotrk_loose_idtrk_tightidandipcut"), combine="weight")
#else:
# muMediumIDSF = get_scalefactor("lepton", ("muon_{0}_{1}".format(era, sfTag), "id_medium"), systName="muid")
# muMediumISOSF = get_scalefactor("lepton", ("muon_{0}_{1}".format(era, sfTag), "iso_tight_id_medium"), systName="muiso")
#############################################################################
############################# Electrons ###################################
#############################################################################
#Wp // 2016: Electron_cutBased_Sum16==3 -> medium // 2017 -2018 : Electron_cutBased ==3 --> medium ( Fall17_V2)
# asking for electrons to be in the Barrel region with dz<1mm & dxy< 0.5mm // Endcap region dz<2mm & dxy< 0.5mm
electronsByPt = op.sort(t.Electron, lambda ele: -ele.p4.Pt())
electrons = op.select(
electronsByPt,
lambda ele: op.AND(ele.p4.Pt() > 15.,
op.abs(ele.p4.Eta()) < 2.5, ele.cutBased >= 3)
) # //cut-based ID Fall17 V2 the recomended one from POG for the FullRunII
# Scalefactors #
#elMediumIDSF = get_scalefactor("lepton", ("electron_{0}_{1}".format(era,sfTag), "id_medium"), systName="elid")
#doubleEleTrigSF = get_scalefactor("dilepton", ("doubleEleLeg_HHMoriond17_2016"), systName="eleltrig")
#elemuTrigSF = get_scalefactor("dilepton", ("elemuLeg_HHMoriond17_2016"), systName="elmutrig")
#mueleTrigSF = get_scalefactor("dilepton", ("mueleLeg_HHMoriond17_2016"), systName="mueltrig")
OsElEl = op.combine(
electrons,
N=2,
pred=lambda el1, el2: op.AND(el1.charge != el2.charge,
el1.p4.Pt() > 25,
el2.p4.Pt() > 15))
OsMuMu = op.combine(
muons,
N=2,
pred=lambda mu1, mu2: op.AND(mu1.charge != mu2.charge,
mu1.p4.Pt() > 25,
mu2.p4.Pt() > 15))
OsElMu = op.combine((electrons, muons),
pred=lambda el, mu: op.AND(el.charge != mu.charge,
el.p4.Pt() > 25,
mu.p4.Pt() > 15))
OsMuEl = op.combine((electrons, muons),
pred=lambda el, mu: op.AND(el.charge != mu.charge,
el.p4.Pt() > 15,
mu.p4.Pt() > 25))
hasOsElEl = noSel.refine("hasOsElEl", cut=[op.rng_len(OsElEl) >= 1])
hasOsMuMu = noSel.refine("hasOsMuMu", cut=[op.rng_len(OsMuMu) >= 1])
hasOsElMu = noSel.refine("hasOsElMu", cut=[op.rng_len(OsElMu) >= 1])
hasOsMuEl = noSel.refine("hasOsMuEl", cut=[op.rng_len(OsMuEl) >= 1])
plots.append(
Plot.make1D("ElEl_channel",
op.rng_len(OsElEl),
noSel,
EquidistantBinning(10, 0, 10.),
title='Number of dilepton events in ElEl channel',
xTitle='N_{dilepton} (ElEl channel)'))
plots.append(
Plot.make1D("MuMu_channel",
op.rng_len(OsMuMu),
noSel,
EquidistantBinning(10, 0, 10.),
title='Number of dilepton events in MuMu channel',
xTitle='N_{dilepton} (MuMu channel)'))
plots.append(
Plot.make1D("ElMu_channel",
op.rng_len(OsElMu),
noSel,
EquidistantBinning(10, 0, 10.),
title='Number of dilepton events in ElMu channel',
xTitle='N_{dilepton} (ElMu channel)'))
plots.append(
Plot.make1D("MuEl_channel",
op.rng_len(OsMuEl),
noSel,
EquidistantBinning(10, 0, 10.),
title='Number of dilepton events in MuEl channel',
xTitle='N_{dilepton} (MuEl channel)'))
plots += makeDileptonPlots(self,
sel=hasOsElEl,
dilepton=OsElEl[0],
suffix='hasOsdilep',
channel='ElEl')
plots += makeDileptonPlots(self,
sel=hasOsMuMu,
dilepton=OsMuMu[0],
suffix='hasOsdilep',
channel='MuMu')
plots += makeDileptonPlots(self,
sel=hasOsElMu,
dilepton=OsElMu[0],
suffix='hasOsdilep',
channel='ElMu')
plots += makeDileptonPlots(self,
sel=hasOsMuEl,
dilepton=OsMuEl[0],
suffix='hasOsdilep',
channel='MuEl')
# Dilepton Z peak exclusion (charge already done in previous selection) #
lambda_mllLowerband = lambda dilep: op.in_range(
12., op.invariant_mass(dilep[0].p4, dilep[1].p4), 80.)
lambda_mllUpperband = lambda dilep: op.invariant_mass(
dilep[0].p4, dilep[1].p4) > 100.
lambda_mllCut = lambda dilep: op.OR(lambda_mllLowerband(dilep),
lambda_mllUpperband(dilep))
hasOsElElOutZ = hasOsElEl.refine("hasOsElElOutZ",
cut=[lambda_mllCut(OsElEl[0])])
hasOsMuMuOutZ = hasOsMuMu.refine("hasOsMuMuOutZ",
cut=[lambda_mllCut(OsMuMu[0])])
hasOsElMuOutZ = hasOsElMu.refine("hasOsElMuOutZ",
cut=[lambda_mllCut(OsElMu[0])])
hasOsMuElOutZ = hasOsMuEl.refine("hasOsMuElOutZ",
cut=[lambda_mllCut(OsMuEl[0])])
plots += makeDileptonPlots(self,
sel=hasOsElElOutZ,
dilepton=OsElEl[0],
suffix='hasOsdilep_OutZ',
channel='ElEl')
plots += makeDileptonPlots(self,
sel=hasOsMuMuOutZ,
dilepton=OsMuMu[0],
suffix='hasOsdilep_OutZ',
channel='MuMu')
plots += makeDileptonPlots(self,
sel=hasOsElMuOutZ,
dilepton=OsElMu[0],
suffix='hasOsdilep_OutZ',
channel='ElMu')
plots += makeDileptonPlots(self,
sel=hasOsMuElOutZ,
dilepton=OsMuEl[0],
suffix='hasOsdilep_OutZ',
channel='MuEl')
#############################################################################
################################ Jets #####################################
#############################################################################
# select jets // 2016 - 2017 - 2018 ( j.jetId &2) -> tight jet ID
jetsByPt = op.sort(t.Jet, lambda jet: -jet.p4.Pt())
jetsSel = op.select(jetsByPt,
lambda j: op.AND(j.p4.Pt() > 20.,
op.abs(j.p4.Eta()) < 2.4,
(j.jetId & 2))) # Jets = AK4 jets
fatjetsByPt = op.sort(t.FatJet, lambda fatjet: -fatjet.p4.Pt())
fatjetsSel = op.select(
fatjetsByPt, lambda j: op.AND(j.p4.Pt() > 20.,
op.abs(j.p4.Eta()) < 2.4,
(j.jetId & 2))) # FatJets = AK8 jets
# exclude from the jetsSel any jet that happens to include within its reconstruction cone a muon or an electron.
jets = op.select(
jetsSel, lambda j: op.AND(
op.NOT(
op.rng_any(electrons, lambda ele: op.deltaR(j.p4, ele.p4) <
0.3)),
op.NOT(
op.rng_any(muons, lambda mu: op.deltaR(j.p4, mu.p4) < 0.3))
))
fatjets = op.select(
fatjetsSel, lambda j: op.AND(
op.NOT(
op.rng_any(electrons, lambda ele: op.deltaR(j.p4, ele.p4) <
0.3)),
op.NOT(
op.rng_any(muons, lambda mu: op.deltaR(j.p4, mu.p4) < 0.3))
))
# Boosted and resolved jets categories #
if era == "2016": # Must check that subJet exists before looking at the btag
lambda_boosted = lambda fatjet: op.OR(
op.AND(fatjet.subJet1._idx.result != -1, fatjet.subJet1.
btagDeepB > 0.6321),
op.AND(fatjet.subJet2._idx.result != -1, fatjet.subJet2.
btagDeepB > 0.6321))
lambda_resolved = lambda jet: jet.btagDeepB > 0.6321
elif era == "2017":
lambda_boosted = lambda fatjet: op.OR(
op.AND(fatjet.subJet1._idx.result != -1, fatjet.subJet1.
btagDeepB > 0.4941),
op.AND(fatjet.subJet2._idx.result != -1, fatjet.subJet2.
btagDeepB > 0.4941))
lambda_resolved = lambda jet: jet.btagDeepB > 0.4941
elif era == "2018":
lambda_boosted = lambda fatjet: op.OR(
op.AND(fatjet.subJet1._idx.result != -1, fatjet.subJet1.
btagDeepB > 0.4184),
op.AND(fatjet.subJet2._idx.result != -1, fatjet.subJet2.
btagDeepB > 0.4184))
lambda_resolved = lambda jet: jet.btagDeepB > 0.4184
# Select the bjets we want #
bjetsResolved = op.select(jets, lambda_resolved)
bjetsBoosted = op.select(fatjets, lambda_boosted)
# Define the boosted and Resolved (+exclusive) selections #
hasBoostedJets = noSel.refine("hasBoostedJets",
cut=[op.rng_len(bjetsBoosted) >= 1])
hasNotBoostedJets = noSel.refine("hasNotBoostedJets",
cut=[op.rng_len(bjetsBoosted) == 0])
hasResolvedJets = noSel.refine(
"hasResolvedJets",
cut=[op.rng_len(jets) >= 2,
op.rng_len(bjetsResolved) >= 1])
hasNotResolvedJets = noSel.refine(
"hasNotResolvedJets",
cut=[op.OR(op.rng_len(jets) <= 1,
op.rng_len(bjetsResolved) == 0)])
hasBoostedAndResolvedJets = noSel.refine(
"hasBoostedAndResolvedJets",
cut=[
op.rng_len(bjetsBoosted) >= 1,
op.rng_len(jets) >= 2,
op.rng_len(bjetsResolved) >= 1
])
hasNotBoostedAndResolvedJets = noSel.refine(
"hasNotBoostedAndResolvedJets",
cut=[
op.OR(
op.rng_len(bjetsBoosted) == 0,
op.rng_len(jets) <= 1,
op.rng_len(bjetsResolved) == 0)
])
hasExlusiveResolvedJets = noSel.refine(
"hasExlusiveResolved",
cut=[
op.rng_len(jets) >= 2,
op.rng_len(bjetsResolved) >= 1,
op.rng_len(bjetsBoosted) == 0
])
hasNotExlusiveResolvedJets = noSel.refine(
"hasNotExlusiveResolved",
cut=[
op.OR(
op.OR(
op.rng_len(jets) <= 1,
op.rng_len(bjetsResolved) == 0),
op.AND(
op.rng_len(bjetsBoosted) >= 1,
op.rng_len(jets) >= 2,
op.rng_len(bjetsResolved) >= 1))
])
hasExlusiveBoostedJets = noSel.refine(
"hasExlusiveBoostedJets",
cut=[
op.rng_len(bjetsBoosted) >= 1,
op.OR(op.rng_len(jets) <= 1,
op.rng_len(bjetsResolved) == 0)
])
hasNotExlusiveBoostedJets = noSel.refine(
"hasNotExlusiveBoostedJets",
cut=[
op.OR(
op.rng_len(bjetsBoosted) == 0,
op.AND(
op.rng_len(jets) >= 2,
op.rng_len(bjetsResolved) >= 1))
])
# Counting events from different selections for debugging #
# Passing Boosted selection #
PassedBoosted = Plot.make1D("PassedBoosted",
op.c_int(1),
hasBoostedJets,
EquidistantBinning(2, 0., 2.),
title='Passed Boosted',
xTitle='Passed Boosted')
FailedBoosted = Plot.make1D("FailedBoosted",
op.c_int(0),
hasNotBoostedJets,
EquidistantBinning(2, 0., 2.),
title='Failed Boosted',
xTitle='Failed Boosted')
plots.append(
SummedPlot("BoostedCase", [FailedBoosted, PassedBoosted],
xTitle="Boosted selection"))
# Passing Resolved selection #
PassedResolved = Plot.make1D("PassedResolved",
op.c_int(1),
hasResolvedJets,
EquidistantBinning(2, 0., 2.),
title='Passed Resolved',
xTitle='Passed Resolved')
FailedResolved = Plot.make1D("FailedResolved",
op.c_int(0),
hasNotResolvedJets,
EquidistantBinning(2, 0., 2.),
title='Failed Resolved',
xTitle='Failed Resolved')
plots.append(
SummedPlot("ResolvedCase", [FailedResolved, PassedResolved],
xTitle="Resolved selection"))
# Passing Exclusive Resolved (Resolved AND NOT Boosted) #
PassedExclusiveResolved = Plot.make1D(
"PassedExclusiveResolved",
op.c_int(1),
hasExlusiveResolvedJets,
EquidistantBinning(2, 0., 2.),
title='Passed Exclusive Resolved',
xTitle='Passed Exclusive Resolved')
FailedExclusiveResolved = Plot.make1D(
"FailedExclusiveResolved",
op.c_int(0),
hasNotExlusiveResolvedJets,
EquidistantBinning(2, 0., 2.),
title='Failed Exclusive Resolved',
xTitle='Failed Exclusive Resolved')
plots.append(
SummedPlot("ExclusiveResolvedCase",
[FailedExclusiveResolved, PassedExclusiveResolved],
xTitle="Exclusive Resolved selection"))
# Passing Exclusive Boosted (Boosted AND NOT Resolved) #
PassedExclusiveBoosted = Plot.make1D("PassedExclusiveBoosted",
op.c_int(1),
hasExlusiveBoostedJets,
EquidistantBinning(2, 0., 2.),
title='Passed Exclusive Boosted',
xTitle='Passed Exclusive Boosted')
FailedExclusiveBoosted = Plot.make1D("FailedExclusiveBoosted",
op.c_int(0),
hasNotExlusiveBoostedJets,
EquidistantBinning(2, 0., 2.),
title='Failed Exclusive Boosted',
xTitle='Failed Exclusive Boosted')
plots.append(
SummedPlot("ExclusiveBoostedCase",
[FailedExclusiveBoosted, PassedExclusiveBoosted],
xTitle="Exclusive Boosted selection"))
# Passing Boosted AND Resolved #
PassedBoth = Plot.make1D("PassedBoth",
op.c_int(1),
hasBoostedAndResolvedJets,
EquidistantBinning(2, 0., 2.),
title='Passed Both Boosted and Resolved',
xTitle='Passed Boosted and Resolved')
FailedBoth = Plot.make1D(
"FailedBoth", # Means failed the (Boosted AND Resolved) = either one or the other
op.c_int(0),
hasNotBoostedAndResolvedJets,
EquidistantBinning(2, 0., 2.),
title='Failed combination Boosted and Resolved',
xTitle='Failed combination')
plots.append(
SummedPlot("BoostedAndResolvedCase", [FailedBoth, PassedBoth],
xTitle="Boosted and Resolved selection"))
# Count number of boosted and resolved jets #
plots.append(
Plot.make1D("NBoostedJets",
op.rng_len(bjetsBoosted),
hasBoostedJets,
EquidistantBinning(5, 0., 5.),
title='Number of boosted jets in boosted case',
xTitle='N boosted bjets'))
plots.append(
Plot.make1D(
"NResolvedJets",
op.rng_len(bjetsResolved),
hasExlusiveResolvedJets,
EquidistantBinning(5, 0., 5.),
title='Number of resolved jets in exclusive resolved case',
xTitle='N resolved bjets'))
# Plot number of subjets in the boosted fatjets #
lambda_noSubjet = lambda fatjet: op.AND(
fatjet.subJet1._idx.result == -1,
op.AND(fatjet.subJet2._idx.result == -1))
lambda_oneSubjet = lambda fatjet: op.AND(
fatjet.subJet1._idx.result != -1,
op.AND(fatjet.subJet2._idx.result == -1))
lambda_twoSubjet = lambda fatjet: op.AND(
fatjet.subJet1._idx.result != -1,
op.AND(fatjet.subJet2._idx.result != -1))
hasNoSubjet = hasBoostedJets.refine(
"hasNoSubjet", cut=[lambda_noSubjet(bjetsBoosted[0])])
hasOneSubjet = hasBoostedJets.refine(
"hasOneSubjet", cut=[lambda_oneSubjet(bjetsBoosted[0])])
hasTwoSubjet = hasBoostedJets.refine(
"hasTwoSubjet", cut=[lambda_twoSubjet(bjetsBoosted[0])])
plot_hasNoSubjet = Plot.make1D(
"plot_hasNoSubjet", # Fill bin 0
op.c_int(0),
hasNoSubjet,
EquidistantBinning(3, 0., 3.),
title='Boosted jet without subjet')
plot_hasOneSubjet = Plot.make1D(
"plot_hasOneSubjet", # Fill bin 1
op.c_int(1),
hasOneSubjet,
EquidistantBinning(3, 0., 3.),
title='Boosted jet with one subjet')
plot_hasTwoSubjet = Plot.make1D(
"plot_hasTwoSubjet", # Fill bin 2
op.c_int(2),
hasTwoSubjet,
EquidistantBinning(3, 0., 3.),
title='Boosted jet with two subjets')
plots.append(
SummedPlot(
"NumberOfSubjets",
[plot_hasNoSubjet, plot_hasOneSubjet, plot_hasTwoSubjet],
xTitle="Number of subjets in boosted jet"))
# Plot jets quantities without the dilepton selections #
plots += makeFatJetPlots(self,
sel=hasBoostedJets,
fatjet=bjetsBoosted[0],
suffix="BoostedJets",
channel="NoChannel")
plots += makeJetsPlots(self,
sel=hasResolvedJets,
jets=bjetsResolved,
suffix="ResolvedJets",
channel="NoChannel")
#############################################################################
##################### Jets + Dilepton combination ###########################
#############################################################################
# Combine dilepton and Resolved (Exclusive = NOT Boosted) selections #
hasOsElElOutZResolvedJets = hasOsElElOutZ.refine(
"hasOsElElOutZResolvedJets",
cut=[
op.rng_len(jets) >= 2,
op.rng_len(bjetsResolved) >= 1,
op.rng_len(bjetsBoosted) == 0
])
hasOsMuMuOutZResolvedJets = hasOsMuMuOutZ.refine(
"hasOsMuMuOutZResolvedJets",
cut=[
op.rng_len(jets) >= 2,
op.rng_len(bjetsResolved) >= 1,
op.rng_len(bjetsBoosted) == 0
])
hasOsElMuOutZResolvedJets = hasOsElMuOutZ.refine(
"hasOsElMuOutZResolvedJets",
cut=[
op.rng_len(jets) >= 2,
op.rng_len(bjetsResolved) >= 1,
op.rng_len(bjetsBoosted) == 0
])
hasOsMuElOutZResolvedJets = hasOsMuElOutZ.refine(
"hasOsMuElOutZResolvedJets",
cut=[
op.rng_len(jets) >= 2,
op.rng_len(bjetsResolved) >= 1,
op.rng_len(bjetsBoosted) == 0
])
# Combine dilepton and Boosted selections #
hasOsElElOutZBoostedJets = hasOsElElOutZ.refine(
"hasOsElElOutZBoostedJets", cut=[op.rng_len(bjetsBoosted) >= 1])
hasOsMuMuOutZBoostedJets = hasOsMuMuOutZ.refine(
"hasOsMuMuOutZBoostedJets", cut=[op.rng_len(bjetsBoosted) >= 1])
hasOsElMuOutZBoostedJets = hasOsElMuOutZ.refine(
"hasOsElMuOutZBoostedJets", cut=[op.rng_len(bjetsBoosted) >= 1])
hasOsMuElOutZBoostedJets = hasOsMuElOutZ.refine(
"hasOsMuElOutZBoostedJets", cut=[op.rng_len(bjetsBoosted) >= 1])
# Plot dilepton with OS, Z peak and Resolved jets selections #
plots += makeDileptonPlots(self,
sel=hasOsElElOutZResolvedJets,
dilepton=OsElEl[0],
suffix='hasOsdilep_OutZ_ResolvedJets',
channel='ElEl')
plots += makeDileptonPlots(self,
sel=hasOsMuMuOutZResolvedJets,
dilepton=OsMuMu[0],
suffix='hasOsdilep_OutZ_ResolvedJets',
channel='MuMu')
plots += makeDileptonPlots(self,
sel=hasOsElMuOutZResolvedJets,
dilepton=OsElMu[0],
suffix='hasOsdilep_OutZ_ResolvedJets',
channel='ElMu')
plots += makeDileptonPlots(self,
sel=hasOsMuElOutZResolvedJets,
dilepton=OsMuEl[0],
suffix='hasOsdilep_OutZ_ResolvedJets',
channel='MuEl')
# Plot dilepton with OS dilepton, Z peak and Boosted jets selections #
plots += makeDileptonPlots(self,
sel=hasOsElElOutZBoostedJets,
dilepton=OsElEl[0],
suffix='hasOsdilep_OutZ_BoostedJets',
channel='ElEl')
plots += makeDileptonPlots(self,
sel=hasOsMuMuOutZBoostedJets,
dilepton=OsMuMu[0],
suffix='hasOsdilep_OutZ_BoostedJets',
channel='MuMu')
plots += makeDileptonPlots(self,
sel=hasOsElMuOutZBoostedJets,
dilepton=OsElMu[0],
suffix='hasOsdilep_OutZ_BoostedJets',
channel='ElMu')
plots += makeDileptonPlots(self,
sel=hasOsMuElOutZBoostedJets,
dilepton=OsMuEl[0],
suffix='hasOsdilep_OutZ_BoostedJets',
channel='MuEl')
# Plotting the fatjet for OS dilepton, Z peak and Boosted jets selections #
plots += makeFatJetPlots(self,
sel=hasOsElElOutZBoostedJets,
fatjet=bjetsBoosted[0],
suffix="hasOsdilep_OutZ_BoostedJets",
channel="ElEl")
plots += makeFatJetPlots(self,
sel=hasOsMuMuOutZBoostedJets,
fatjet=bjetsBoosted[0],
suffix="hasOsdilep_OutZ_BoostedJets",
channel="MuMu")
plots += makeFatJetPlots(self,
sel=hasOsElMuOutZBoostedJets,
fatjet=bjetsBoosted[0],
suffix="hasOsdilep_OutZ_BoostedJets",
channel="ElMu")
plots += makeFatJetPlots(self,
sel=hasOsMuElOutZBoostedJets,
fatjet=bjetsBoosted[0],
suffix="hasOsdilep_OutZ_BoostedJets",
channel="MuEl")
# Plotting the jets for OS dilepton, Z peak and Resolved jets selections #
plots += makeJetsPlots(self,
sel=hasOsElElOutZResolvedJets,
jets=bjetsResolved,
suffix="hasOsdilep_OutZ_ResolvedJets",
channel="ElEl")
plots += makeJetsPlots(self,
sel=hasOsMuMuOutZResolvedJets,
jets=bjetsResolved,
suffix="hasOsdilep_OutZ_ResolvedJets",
channel="MuMu")
plots += makeJetsPlots(self,
sel=hasOsElMuOutZResolvedJets,
jets=bjetsResolved,
suffix="hasOsdilep_OutZ_ResolvedJets",
channel="ElMu")
plots += makeJetsPlots(self,
sel=hasOsMuElOutZResolvedJets,
jets=bjetsResolved,
suffix="hasOsdilep_OutZ_ResolvedJets",
channel="MuEl")
## helper selection (OR) to make sure jet calculations are only done once
#hasOSLL = noSel.refine("hasOSLL", cut=op.OR(*( hasOSLL_cmbRng(rng) for rng in osLLRng.values())))
#forceDefine(t._Jet.calcProd, hasOSLL)
#for varNm in t._Jet.available:
# forceDefine(t._Jet[varNm], hasOSLL)
return plots
def definePlots(self, t, noSel, sample=None, sampleCfg=None):
noSel = super(PlotterNanoHHtobbWWDL,self).prepareObjects(t, noSel, sample, sampleCfg, 'DL')
#----- Machine Learning Model -----#
path_model = os.path.join(os.path.abspath(os.path.dirname(__file__)),'MachineLearning','model.pb')
if not os.path.exists(path_model):
raise RuntimeError('Could not find model file %s'%path_model)
try:
LBN = op.mvaEvaluator(path_model,mvaType='Tensorflow',otherArgs=(["input_1", "input_2"], "model/output/Softmax"))
except:
raise RuntimeError('Could not load model %s'%path_model)
#---- Parameters -----#
plots = []
cutFlowPlots = []
era = sampleCfg['era']
self.sample = sample
self.sampleCfg = sampleCfg
self.era = era
self.yieldPlots = makeYieldPlots(self.args.Synchronization)
#----- Ratio reweighting variables (before lepton and jet selection) -----#
if self.args.BtagReweightingOff or self.args.BtagReweightingOn:
plots.append(objectsNumberPlot(channel="NoChannel",suffix='NoSelection',sel=noSel,objCont=self.ak4Jets,objName='Ak4Jets',Nmax=15,xTitle='N(Ak4 jets)'))
plots.append(CutFlowReport("BtagReweightingCutFlowReport",noSel))
return plots
#----- Stitching study -----#
if self.args.DYStitchingPlots or self.args.WJetsStitchingPlots:
if self.args.DYStitchingPlots and sampleCfg['group'] != 'DY':
raise RuntimeError("Stitching is only done on DY MC samples")
if self.args.WJetsStitchingPlots and sampleCfg['group'] != 'Wjets':
raise RuntimeError("Stitching is only done on WJets MC samples")
plots.extend(makeLHEPlots(noSel,t.LHE))
plots.append(objectsNumberPlot(channel="NoChannel",suffix='NoSelection',sel=noSel,objCont=self.ak4Jets,objName='Ak4Jets',Nmax=15,xTitle='N(Ak4 jets)'))
plots.append(CutFlowReport("DYStitchingCutFlowReport",noSel))
return plots
#----- Dileptons -----#
selObjectDict = makeDoubleLeptonSelection(self,noSel,plot_yield=True)
# selObjectDict : keys -> level (str)
# values -> [ElEl,MuMu,ElMu] x Selection object
# Select the jets selections that will be done depending on user input #
jet_level = ["Ak4","Ak8","Resolved0Btag","Resolved1Btag","Resolved2Btag","Boosted"]
jetplot_level = [arg for (arg,boolean) in self.args.__dict__.items() if arg in jet_level and boolean]
if len(jetplot_level) == 0:
jetplot_level = jet_level # If nothing said, will do all
jetsel_level = copy(jetplot_level) # A plot level might need a previous selection that needs to be defined but not necessarily plotted
if "Resolved0Btag" in jetsel_level or "Resolved1Btag" in jetsel_level or "Resolved2Btag" in jetsel_level:
jetsel_level.append("Ak4") # Resolved needs the Ak4 selection
if "Boosted" in jetsel_level:
jetsel_level.append("Ak8") # Boosted needs the Ak8 selection
# Loop over lepton selection and start plotting #
for selectionType, selectionList in selObjectDict.items():
print ("... Processing %s lepton type"%selectionType)
#----- Select correct dilepton -----#
if selectionType == "Preselected":
OSElElDilepton = self.OSElElDileptonPreSel
OSMuMuDilepton = self.OSMuMuDileptonPreSel
OSElMuDilepton = self.OSElMuDileptonPreSel
elif selectionType == "Fakeable":
OSElElDilepton = self.ElElDileptonFakeSel
OSMuMuDilepton = self.MuMuDileptonFakeSel
OSElMuDilepton = self.ElMuDileptonFakeSel
elif selectionType == "Tight":
OSElElDilepton = switch_on_index([0],op.rng_len(self.ElElDileptonTightSel)>=1,self.ElElDileptonTightSel,self.ElElDileptonFakeExtrapolationSel)
OSMuMuDilepton = switch_on_index([0],op.rng_len(self.MuMuDileptonTightSel)>=1,self.MuMuDileptonTightSel,self.MuMuDileptonFakeExtrapolationSel)
OSElMuDilepton = switch_on_index([0],op.rng_len(self.ElMuDileptonTightSel)>=1,self.ElMuDileptonTightSel,self.ElMuDileptonFakeExtrapolationSel)
elif selectionType == "FakeExtrapolation":
OSElElDilepton = self.ElElDileptonFakeExtrapolationSel
OSMuMuDilepton = self.MuMuDileptonFakeExtrapolationSel
OSElMuDilepton = self.ElMuDileptonFakeExtrapolationSel
#----- Separate selections ------#
ElElSelObjectDilepton = selectionList[0]
MuMuSelObjectDilepton = selectionList[1]
ElMuSelObjectDilepton = selectionList[2]
#----- Channel and trigger plots -----#
if not self.args.OnlyYield:
ChannelDictList = []
ChannelDictList.append({'channel':'ElEl','sel':ElElSelObjectDilepton.sel,'suffix':ElElSelObjectDilepton.selName})
ChannelDictList.append({'channel':'MuMu','sel':MuMuSelObjectDilepton.sel,'suffix':MuMuSelObjectDilepton.selName})
ChannelDictList.append({'channel':'ElMu','sel':ElMuSelObjectDilepton.sel,'suffix':ElMuSelObjectDilepton.selName})
for channelDict in ChannelDictList:
#----- Trigger plots -----#
plots.extend(doubleLeptonTriggerPlots(**channelDict,triggerDict=self.triggersPerPrimaryDataset))
#----- Dilepton plots -----#
#plots.extend(doubleLeptonChannelPlot(**channelDict,DilepElEl=OSElElDilepton,DilepMuMu=OSMuMuDilepton,DilepElMu=OSElMuDilepton))
LeptonKeys = ['channel','sel','dilepton','suffix','is_MC']
JetKeys = ['channel','sel','leadjet','subleadjet','lead_is_b','sublead_is_b','suffix','is_MC']
commonItems = ['channel','sel','suffix']
#----- Ak4 jets selection -----#
if "Ak4" in jetsel_level:
print ("...... Processing Ak4 jet selection")
ElElSelObjectDileptonAk4Jets = makeAtLeastTwoAk4JetSelection(self,ElElSelObjectDilepton,copy_sel=True,plot_yield=True)
MuMuSelObjectDileptonAk4Jets = makeAtLeastTwoAk4JetSelection(self,MuMuSelObjectDilepton,copy_sel=True,plot_yield=True)
ElMuSelObjectDileptonAk4Jets = makeAtLeastTwoAk4JetSelection(self,ElMuSelObjectDilepton,copy_sel=True,plot_yield=True)
# Jet and lepton plots #
ChannelDictList = []
if "Ak4" in jetplot_level:
# Cut flow report #
cutFlowPlots.append(CutFlowReport(ElElSelObjectDileptonAk4Jets.selName,ElElSelObjectDileptonAk4Jets.sel))
cutFlowPlots.append(CutFlowReport(MuMuSelObjectDileptonAk4Jets.selName,MuMuSelObjectDileptonAk4Jets.sel))
cutFlowPlots.append(CutFlowReport(ElMuSelObjectDileptonAk4Jets.selName,ElMuSelObjectDileptonAk4Jets.sel))
if not self.args.OnlyYield:
ChannelDictList.append({'channel':'ElEl','sel':ElElSelObjectDileptonAk4Jets.sel,'dilepton':OSElElDilepton[0],'leadjet':self.ak4Jets[0],'subleadjet':self.ak4Jets[1],'lead_is_b':False,'sublead_is_b':False,'suffix':ElElSelObjectDileptonAk4Jets.selName,'is_MC':self.is_MC})
ChannelDictList.append({'channel':'MuMu','sel':MuMuSelObjectDileptonAk4Jets.sel,'dilepton':OSMuMuDilepton[0],'leadjet':self.ak4Jets[0],'subleadjet':self.ak4Jets[1],'lead_is_b':False,'sublead_is_b':False,'suffix':MuMuSelObjectDileptonAk4Jets.selName,'is_MC':self.is_MC})
ChannelDictList.append({'channel':'ElMu','sel':ElMuSelObjectDileptonAk4Jets.sel,'dilepton':OSElMuDilepton[0],'leadjet':self.ak4Jets[0],'subleadjet':self.ak4Jets[1],'lead_is_b':False,'sublead_is_b':False,'suffix':ElMuSelObjectDileptonAk4Jets.selName,'is_MC':self.is_MC})
JetsN = {'objName':'Ak4Jets','objCont':self.ak4Jets,'Nmax':15,'xTitle':'N(Ak4 jets)'}
for channelDict in ChannelDictList:
# Dilepton #
plots.extend(makeDileptonPlots(**{k:channelDict[k] for k in LeptonKeys}))
# Number of jets #
plots.append(objectsNumberPlot(**{k:channelDict[k] for k in commonItems},**JetsN))
# Ak4 Jets #
plots.extend(makeTwoAk4JetsPlots(**{k:channelDict[k] for k in JetKeys}))
# MET #
plots.extend(makeMETPlots(**{k:channelDict[k] for k in commonItems}, met=self.corrMET))
##### Ak8 jets selection #####
if "Ak8" in jetsel_level:
print ("...... Processing Ak8 jet selection")
ElElSelObjectDileptonAk8Jets = makeAtLeastOneAk8JetSelection(self,ElElSelObjectDilepton,copy_sel=True,plot_yield=True)
MuMuSelObjectDileptonAk8Jets = makeAtLeastOneAk8JetSelection(self,MuMuSelObjectDilepton,copy_sel=True,plot_yield=True)
ElMuSelObjectDileptonAk8Jets = makeAtLeastOneAk8JetSelection(self,ElMuSelObjectDilepton,copy_sel=True,plot_yield=True)
# Fatjets plots #
ChannelDictList = []
if "Ak8" in jetplot_level:
# Cut flow report #
cutFlowPlots.append(CutFlowReport(ElElSelObjectDileptonAk8Jets.selName,ElElSelObjectDileptonAk8Jets.sel))
cutFlowPlots.append(CutFlowReport(MuMuSelObjectDileptonAk8Jets.selName,MuMuSelObjectDileptonAk8Jets.sel))
cutFlowPlots.append(CutFlowReport(ElMuSelObjectDileptonAk8Jets.selName,ElMuSelObjectDileptonAk8Jets.sel))
if not self.args.OnlyYield:
ChannelDictList.append({'channel':'ElEl','sel':ElElSelObjectDileptonAk8Jets.sel,'dilepton':OSElElDilepton[0],'fatjet':self.ak8Jets[0],'suffix':ElElSelObjectDileptonAk8Jets.selName,'is_MC':self.is_MC})
ChannelDictList.append({'channel':'MuMu','sel':MuMuSelObjectDileptonAk8Jets.sel,'dilepton':OSMuMuDilepton[0],'fatjet':self.ak8Jets[0],'suffix':MuMuSelObjectDileptonAk8Jets.selName,'is_MC':self.is_MC})
ChannelDictList.append({'channel':'ElMu','sel':ElMuSelObjectDileptonAk8Jets.sel,'dilepton':OSElMuDilepton[0],'fatjet':self.ak8Jets[0],'suffix':ElMuSelObjectDileptonAk8Jets.selName,'is_MC':self.is_MC})
FatJetKeys = ['channel','sel','fatjet','suffix']
FatJetsN = {'objName':'Ak8Jets','objCont':self.ak8Jets,'Nmax':5,'xTitle':'N(Ak8 jets)'}
for channelDict in ChannelDictList:
# Dilepton #
plots.extend(makeDileptonPlots(**{k:channelDict[k] for k in LeptonKeys}))
# Number of jets #
plots.append(objectsNumberPlot(**{k:channelDict[k] for k in commonItems},**FatJetsN))
# Ak8 Jets #
plots.extend(makeDoubleLeptonAk8JetsPlots(**{k:channelDict[k] for k in FatJetKeys}))
# MET #
plots.extend(makeMETPlots(**{k:channelDict[k] for k in commonItems}, met=self.corrMET))
#----- Resolved selection -----#
if any(item in ["Resolved0Btag","Resolved1Btag","Resolved2Btag"] for item in jetsel_level): # If any of resolved category is asked
#----- select the jets -----#
aka4JetsByBtagScore = op.sort(self.ak4Jets, lambda jet : -jet.btagDeepFlavB)
container0b2j = [ t.Jet[self.ak4LightJetsByBtagScore[i].idx] for i in range(2) ]
container1b1j = [ t.Jet[op.switch(op.rng_len(self.ak4BJets) == 1, self.ak4BJets[0].idx, aka4JetsByBtagScore[0].idx)] ,
t.Jet[op.switch(op.rng_len(self.ak4BJets) == 1, self.ak4LightJetsByBtagScore[0].idx, aka4JetsByBtagScore[1].idx)]]
container2b0j = [ t.Jet[op.switch(op.rng_len(self.ak4BJets) >= 2, self.ak4BJets[i].idx, aka4JetsByBtagScore[i].idx)] for i in range(2) ]
ChannelDictList = []
#----- Resolved selection : 0 Btag -----#
if "Resolved0Btag" in jetsel_level:
print ("...... Processing Resolved jet (0 btag) selection")
ElElSelObjectDileptonAk4JetsExclusiveResolvedNoBtag = makeExclusiveResolvedNoBtagSelection(self,ElElSelObjectDileptonAk4Jets,copy_sel=True,plot_yield=True)
MuMuSelObjectDileptonAk4JetsExclusiveResolvedNoBtag = makeExclusiveResolvedNoBtagSelection(self,MuMuSelObjectDileptonAk4Jets,copy_sel=True,plot_yield=True)
ElMuSelObjectDileptonAk4JetsExclusiveResolvedNoBtag = makeExclusiveResolvedNoBtagSelection(self,ElMuSelObjectDileptonAk4Jets,copy_sel=True,plot_yield=True)
if "Resolved0Btag" in jetplot_level:
# Cut flow report #
cutFlowPlots.append(CutFlowReport(ElElSelObjectDileptonAk4JetsExclusiveResolvedNoBtag.selName,ElElSelObjectDileptonAk4JetsExclusiveResolvedNoBtag.sel))
cutFlowPlots.append(CutFlowReport(MuMuSelObjectDileptonAk4JetsExclusiveResolvedNoBtag.selName,MuMuSelObjectDileptonAk4JetsExclusiveResolvedNoBtag.sel))
cutFlowPlots.append(CutFlowReport(ElMuSelObjectDileptonAk4JetsExclusiveResolvedNoBtag.selName,ElMuSelObjectDileptonAk4JetsExclusiveResolvedNoBtag.sel))
if not self.args.OnlyYield:
ChannelDictList.append({'channel':'ElEl','sel':ElElSelObjectDileptonAk4JetsExclusiveResolvedNoBtag.sel,'dilepton':OSElElDilepton[0],'leadjet':container0b2j[0],'subleadjet':container0b2j[1],'lead_is_b':False,'sublead_is_b':False,'suffix':ElElSelObjectDileptonAk4JetsExclusiveResolvedNoBtag.selName,'is_MC':self.is_MC})
ChannelDictList.append({'channel':'MuMu','sel':MuMuSelObjectDileptonAk4JetsExclusiveResolvedNoBtag.sel,'dilepton':OSMuMuDilepton[0],'leadjet':container0b2j[0],'subleadjet':container0b2j[1],'lead_is_b':False,'sublead_is_b':False,'suffix':MuMuSelObjectDileptonAk4JetsExclusiveResolvedNoBtag.selName,'is_MC':self.is_MC})
ChannelDictList.append({'channel':'ElMu','sel':ElMuSelObjectDileptonAk4JetsExclusiveResolvedNoBtag.sel,'dilepton':OSElMuDilepton[0],'leadjet':container0b2j[0],'subleadjet':container0b2j[1],'lead_is_b':False,'sublead_is_b':False,'suffix':ElMuSelObjectDileptonAk4JetsExclusiveResolvedNoBtag.selName,'is_MC':self.is_MC})
#---- Resolved selection : 1 Btag -----#
if "Resolved1Btag" in jetsel_level:
print ("...... Processing Resolved jet (1 btag) selection")
ElElSelObjectDileptonAk4JetsExclusiveResolvedOneBtag = makeExclusiveResolvedOneBtagSelection(self,ElElSelObjectDileptonAk4Jets,copy_sel=True,plot_yield=True)
MuMuSelObjectDileptonAk4JetsExclusiveResolvedOneBtag = makeExclusiveResolvedOneBtagSelection(self,MuMuSelObjectDileptonAk4Jets,copy_sel=True,plot_yield=True)
ElMuSelObjectDileptonAk4JetsExclusiveResolvedOneBtag = makeExclusiveResolvedOneBtagSelection(self,ElMuSelObjectDileptonAk4Jets,copy_sel=True,plot_yield=True)
if "Resolved1Btag" in jetplot_level:
# Cut flow report #
cutFlowPlots.append(CutFlowReport(ElElSelObjectDileptonAk4JetsExclusiveResolvedOneBtag.selName,ElElSelObjectDileptonAk4JetsExclusiveResolvedOneBtag.sel))
cutFlowPlots.append(CutFlowReport(MuMuSelObjectDileptonAk4JetsExclusiveResolvedOneBtag.selName,MuMuSelObjectDileptonAk4JetsExclusiveResolvedOneBtag.sel))
cutFlowPlots.append(CutFlowReport(ElMuSelObjectDileptonAk4JetsExclusiveResolvedOneBtag.selName,ElMuSelObjectDileptonAk4JetsExclusiveResolvedOneBtag.sel))
if not self.args.OnlyYield:
ChannelDictList.append({'channel':'ElEl','sel':ElElSelObjectDileptonAk4JetsExclusiveResolvedOneBtag.sel,'dilepton':OSElElDilepton[0],'leadjet':container1b1j[0],'subleadjet':container1b1j[1],'lead_is_b':True,'sublead_is_b':False,'suffix':ElElSelObjectDileptonAk4JetsExclusiveResolvedOneBtag.selName,'is_MC':self.is_MC})
ChannelDictList.append({'channel':'MuMu','sel':MuMuSelObjectDileptonAk4JetsExclusiveResolvedOneBtag.sel,'dilepton':OSMuMuDilepton[0],'leadjet':container1b1j[0],'subleadjet':container1b1j[1],'lead_is_b':True,'sublead_is_b':False,'suffix':MuMuSelObjectDileptonAk4JetsExclusiveResolvedOneBtag.selName,'is_MC':self.is_MC})
ChannelDictList.append({'channel':'ElMu','sel':ElMuSelObjectDileptonAk4JetsExclusiveResolvedOneBtag.sel,'dilepton':OSElMuDilepton[0],'leadjet':container1b1j[0],'subleadjet':container1b1j[1],'lead_is_b':True,'sublead_is_b':False,'suffix':ElMuSelObjectDileptonAk4JetsExclusiveResolvedOneBtag.selName,'is_MC':self.is_MC})
#----- Resolved selection : 2 Btags -----#
if "Resolved2Btag" in jetsel_level:
print ("...... Processing Resolved jet (2 btags) selection")
ElElSelObjectDileptonAk4JetsExclusiveResolvedTwoBtags = makeExclusiveResolvedTwoBtagsSelection(self,ElElSelObjectDileptonAk4Jets,copy_sel=True,plot_yield=True)
MuMuSelObjectDileptonAk4JetsExclusiveResolvedTwoBtags = makeExclusiveResolvedTwoBtagsSelection(self,MuMuSelObjectDileptonAk4Jets,copy_sel=True,plot_yield=True)
ElMuSelObjectDileptonAk4JetsExclusiveResolvedTwoBtags = makeExclusiveResolvedTwoBtagsSelection(self,ElMuSelObjectDileptonAk4Jets,copy_sel=True,plot_yield=True)
if "Resolved2Btag" in jetplot_level:
# Cut flow report #
cutFlowPlots.append(CutFlowReport(ElElSelObjectDileptonAk4JetsExclusiveResolvedTwoBtags.selName,ElElSelObjectDileptonAk4JetsExclusiveResolvedTwoBtags.sel))
cutFlowPlots.append(CutFlowReport(MuMuSelObjectDileptonAk4JetsExclusiveResolvedTwoBtags.selName,MuMuSelObjectDileptonAk4JetsExclusiveResolvedTwoBtags.sel))
cutFlowPlots.append(CutFlowReport(ElMuSelObjectDileptonAk4JetsExclusiveResolvedTwoBtags.selName,ElMuSelObjectDileptonAk4JetsExclusiveResolvedTwoBtags.sel))
if not self.args.OnlyYield:
ChannelDictList.append({'channel':'ElEl','sel':ElElSelObjectDileptonAk4JetsExclusiveResolvedTwoBtags.sel,'dilepton':OSElElDilepton[0],'leadjet':container2b0j[0],'subleadjet':container2b0j[1],'lead_is_b':True,'sublead_is_b':True,'suffix':ElElSelObjectDileptonAk4JetsExclusiveResolvedTwoBtags.selName,'is_MC':self.is_MC})
ChannelDictList.append({'channel':'MuMu','sel':MuMuSelObjectDileptonAk4JetsExclusiveResolvedTwoBtags.sel,'dilepton':OSMuMuDilepton[0],'leadjet':container2b0j[0],'subleadjet':container2b0j[1],'lead_is_b':True,'sublead_is_b':True,'suffix':MuMuSelObjectDileptonAk4JetsExclusiveResolvedTwoBtags.selName,'is_MC':self.is_MC})
ChannelDictList.append({'channel':'ElMu','sel':ElMuSelObjectDileptonAk4JetsExclusiveResolvedTwoBtags.sel,'dilepton':OSElMuDilepton[0],'leadjet':container2b0j[0],'subleadjet':container2b0j[1],'lead_is_b':True,'sublead_is_b':True,'suffix':ElMuSelObjectDileptonAk4JetsExclusiveResolvedTwoBtags.selName,'is_MC':self.is_MC})
# Lepton + jet Plots #
ResolvedJetsN = {'objName':'Ak4BJets','objCont':self.ak4BJets,'Nmax':5,'xTitle':'N(Ak4 Bjets)'}
for channelDict in ChannelDictList:
# Dilepton #
plots.extend(makeDileptonPlots(**{k:channelDict[k] for k in LeptonKeys}))
# Number of jets #
plots.append(objectsNumberPlot(**{k:channelDict[k] for k in commonItems},**ResolvedJetsN))
plots.append(objectsNumberPlot(**{k:channelDict[k] for k in commonItems},**JetsN))
# Ak4 Jets #
plots.extend(makeTwoAk4JetsPlots(**{k:channelDict[k] for k in JetKeys}))
# MET #
plots.extend(makeMETPlots(**{k:channelDict[k] for k in commonItems}, met=self.corrMET))
#----- Boosted selection -----#
if "Boosted" in jetsel_level:
print ("...... Processing Boosted jet selection")
ElElSelObjectDileptonAk8JetsInclusiveBoosted = makeInclusiveBoostedSelection(self,ElElSelObjectDileptonAk8Jets,copy_sel=True,plot_yield=True)
MuMuSelObjectDileptonAk8JetsInclusiveBoosted = makeInclusiveBoostedSelection(self,MuMuSelObjectDileptonAk8Jets,copy_sel=True,plot_yield=True)
ElMuSelObjectDileptonAk8JetsInclusiveBoosted = makeInclusiveBoostedSelection(self,ElMuSelObjectDileptonAk8Jets,copy_sel=True,plot_yield=True)
# Lepton + jet Plots #
ChannelDictList = []
if "Boosted" in jetplot_level:
# Cut flow report #
cutFlowPlots.append(CutFlowReport(ElElSelObjectDileptonAk8JetsInclusiveBoosted.selName,ElElSelObjectDileptonAk8JetsInclusiveBoosted.sel))
cutFlowPlots.append(CutFlowReport(MuMuSelObjectDileptonAk8JetsInclusiveBoosted.selName,MuMuSelObjectDileptonAk8JetsInclusiveBoosted.sel))
cutFlowPlots.append(CutFlowReport(ElMuSelObjectDileptonAk8JetsInclusiveBoosted.selName,ElMuSelObjectDileptonAk8JetsInclusiveBoosted.sel))
if not self.args.OnlyYield:
ChannelDictList.append({'channel':'ElEl','sel':ElElSelObjectDileptonAk8JetsInclusiveBoosted.sel,'dilepton':OSElElDilepton[0],'fatjet':self.ak8BJets[0],'suffix':ElElSelObjectDileptonAk8JetsInclusiveBoosted.selName,'is_MC':self.is_MC})
ChannelDictList.append({'channel':'MuMu','sel':MuMuSelObjectDileptonAk8JetsInclusiveBoosted.sel,'dilepton':OSMuMuDilepton[0],'fatjet':self.ak8BJets[0],'suffix':MuMuSelObjectDileptonAk8JetsInclusiveBoosted.selName,'is_MC':self.is_MC})
ChannelDictList.append({'channel':'ElMu','sel':ElMuSelObjectDileptonAk8JetsInclusiveBoosted.sel,'dilepton':OSElMuDilepton[0],'fatjet':self.ak8BJets[0],'suffix':ElMuSelObjectDileptonAk8JetsInclusiveBoosted.selName,'is_MC':self.is_MC})
BoostedJetsN = {'objName':'Ak8BJets','objCont':self.ak8BJets,'Nmax':5,'xTitle':'N(Ak8 Bjets)'}
for channelDict in ChannelDictList:
# Dilepton #
plots.extend(makeDileptonPlots(**{k:channelDict[k] for k in LeptonKeys}))
# Number of jets #
plots.append(objectsNumberPlot(**{k:channelDict[k] for k in commonItems},**BoostedJetsN))
plots.append(objectsNumberPlot(**{k:channelDict[k] for k in commonItems},**FatJetsN))
# Ak8 Jets #
plots.extend(makeDoubleLeptonAk8JetsPlots(**{k:channelDict[k] for k in FatJetKeys}))
# MET #
plots.extend(makeMETPlots(**{k:channelDict[k] for k in commonItems}, met=self.corrMET))
#----- High-level combinations -----#
# NOTE : very time consuming
ChannelDictList = []
if not self.args.OnlyYield:
# Resolved No Btag #
if "Resolved0Btag" in jetplot_level:
ChannelDictList.append({'channel': 'ElEl','met': self.corrMET,'l1':OSElElDilepton[0][0],'l2':OSElElDilepton[0][1],'j1':container0b2j[0],'j2':container0b2j[1],'sel':ElElSelObjectDileptonAk4JetsExclusiveResolvedNoBtag.sel,'suffix':ElElSelObjectDileptonAk4JetsExclusiveResolvedNoBtag.selName})
ChannelDictList.append({'channel': 'MuMu','met': self.corrMET,'l1':OSMuMuDilepton[0][0],'l2':OSMuMuDilepton[0][1],'j1':container0b2j[0],'j2':container0b2j[1],'sel':MuMuSelObjectDileptonAk4JetsExclusiveResolvedNoBtag.sel,'suffix':MuMuSelObjectDileptonAk4JetsExclusiveResolvedNoBtag.selName})
ChannelDictList.append({'channel': 'ElMu','met': self.corrMET,'l1':OSElMuDilepton[0][0],'l2':OSElMuDilepton[0][1],'j1':container0b2j[0],'j2':container0b2j[1],'sel':ElMuSelObjectDileptonAk4JetsExclusiveResolvedNoBtag.sel,'suffix':ElMuSelObjectDileptonAk4JetsExclusiveResolvedNoBtag.selName})
# Resolved One Btag #
if "Resolved1Btag" in jetplot_level:
ChannelDictList.append({'channel': 'ElEl','met': self.corrMET,'l1':OSElElDilepton[0][0],'l2':OSElElDilepton[0][1],'j1':container1b1j[0],'j2':container1b1j[1],'sel':ElElSelObjectDileptonAk4JetsExclusiveResolvedOneBtag.sel,'suffix':ElElSelObjectDileptonAk4JetsExclusiveResolvedOneBtag.selName})
ChannelDictList.append({'channel': 'MuMu','met': self.corrMET,'l1':OSMuMuDilepton[0][0],'l2':OSMuMuDilepton[0][1],'j1':container1b1j[0],'j2':container1b1j[1],'sel':MuMuSelObjectDileptonAk4JetsExclusiveResolvedOneBtag.sel,'suffix':MuMuSelObjectDileptonAk4JetsExclusiveResolvedOneBtag.selName})
ChannelDictList.append({'channel': 'ElMu','met': self.corrMET,'l1':OSElMuDilepton[0][0],'l2':OSElMuDilepton[0][1],'j1':container1b1j[0],'j2':container1b1j[1],'sel':ElMuSelObjectDileptonAk4JetsExclusiveResolvedOneBtag.sel,'suffix':ElMuSelObjectDileptonAk4JetsExclusiveResolvedOneBtag.selName})
# Resolved Two Btags #
if "Resolved2Btag" in jetplot_level:
ChannelDictList.append({'channel': 'ElEl','met': self.corrMET,'l1':OSElElDilepton[0][0],'l2':OSElElDilepton[0][1],'j1':container2b0j[0],'j2':container2b0j[1],'sel':ElElSelObjectDileptonAk4JetsExclusiveResolvedTwoBtags.sel,'suffix':ElElSelObjectDileptonAk4JetsExclusiveResolvedTwoBtags.selName})
ChannelDictList.append({'channel': 'MuMu','met': self.corrMET,'l1':OSMuMuDilepton[0][0],'l2':OSMuMuDilepton[0][1],'j1':container2b0j[0],'j2':container2b0j[1],'sel':MuMuSelObjectDileptonAk4JetsExclusiveResolvedTwoBtags.sel,'suffix':MuMuSelObjectDileptonAk4JetsExclusiveResolvedTwoBtags.selName})
ChannelDictList.append({'channel': 'ElMu','met': self.corrMET,'l1':OSElMuDilepton[0][0],'l2':OSElMuDilepton[0][1],'j1':container2b0j[0],'j2':container2b0j[1],'sel':ElMuSelObjectDileptonAk4JetsExclusiveResolvedTwoBtags.sel,'suffix':ElMuSelObjectDileptonAk4JetsExclusiveResolvedTwoBtags.selName})
# Boosted #
if "Boosted" in jetplot_level:
ChannelDictList.append({'channel': 'ElEl','met': self.corrMET,'l1':OSElElDilepton[0][0],'l2':OSElElDilepton[0][1],'j1':self.ak8BJets[0].subJet1,'j2':self.ak8BJets[0].subJet2,'sel':ElElSelObjectDileptonAk8JetsInclusiveBoosted.sel,'suffix':ElElSelObjectDileptonAk8JetsInclusiveBoosted.selName})
ChannelDictList.append({'channel': 'MuMu','met': self.corrMET,'l1':OSMuMuDilepton[0][0],'l2':OSMuMuDilepton[0][1],'j1':self.ak8BJets[0].subJet1,'j2':self.ak8BJets[0].subJet2,'sel':MuMuSelObjectDileptonAk8JetsInclusiveBoosted.sel,'suffix':MuMuSelObjectDileptonAk8JetsInclusiveBoosted.selName})
ChannelDictList.append({'channel': 'ElMu','met': self.corrMET,'l1':OSElMuDilepton[0][0],'l2':OSElMuDilepton[0][1],'j1':self.ak8BJets[0].subJet1,'j2':self.ak8BJets[0].subJet2,'sel':ElMuSelObjectDileptonAk8JetsInclusiveBoosted.sel,'suffix':ElMuSelObjectDileptonAk8JetsInclusiveBoosted.selName})
for channelDict in ChannelDictList:
plots.extend(makeDoubleLeptonHighLevelQuantities(**channelDict,HLL=self.HLL))
#----- Machine Learning plots -----#
selObjectDictList = []
if not self.args.OnlyYield:
if "Ak4" in jetplot_level:
selObjectDictList.append({'channel':'ElEl','selObject':ElElSelObjectDileptonAk4Jets})
selObjectDictList.append({'channel':'MuMu','selObject':MuMuSelObjectDileptonAk4Jets})
selObjectDictList.append({'channel':'ElMu','selObject':ElMuSelObjectDileptonAk4Jets})
# if "Ak8" in jetplot_level:
# selObjectDictList.append({'channel':'ElEl','selObject':ElElSelObjectDileptonAk8Jets})
# selObjectDictList.append({'channel':'MuMu','selObject':MuMuSelObjectDileptonAk8Jets})
# selObjectDictList.append({'channel':'ElMu','selObject':ElMuSelObjectDileptonAk8Jets})
if "Resolved0Btag" in jetplot_level:
selObjectDictList.append({'channel':'ElEl','selObject':ElElSelObjectDileptonAk4JetsExclusiveResolvedNoBtag})
selObjectDictList.append({'channel':'MuMu','selObject':MuMuSelObjectDileptonAk4JetsExclusiveResolvedNoBtag})
selObjectDictList.append({'channel':'ElMu','selObject':ElMuSelObjectDileptonAk4JetsExclusiveResolvedNoBtag})
if "Resolved1Btag" in jetplot_level:
selObjectDictList.append({'channel':'ElEl','selObject':ElElSelObjectDileptonAk4JetsExclusiveResolvedOneBtag})
selObjectDictList.append({'channel':'MuMu','selObject':MuMuSelObjectDileptonAk4JetsExclusiveResolvedOneBtag})
selObjectDictList.append({'channel':'ElMu','selObject':ElMuSelObjectDileptonAk4JetsExclusiveResolvedOneBtag})
if "Resolved2Btag" in jetplot_level:
selObjectDictList.append({'channel':'ElEl','selObject':ElElSelObjectDileptonAk4JetsExclusiveResolvedTwoBtags})
selObjectDictList.append({'channel':'MuMu','selObject':MuMuSelObjectDileptonAk4JetsExclusiveResolvedTwoBtags})
selObjectDictList.append({'channel':'ElMu','selObject':ElMuSelObjectDileptonAk4JetsExclusiveResolvedTwoBtags})
# if "Boosted" in jetplot_level:
# selObjectDictList.append({'channel':'ElEl','selObject':ElElSelObjectDileptonAk8JetsInclusiveBoosted})
# selObjectDictList.append({'channel':'MuMu','selObject':MuMuSelObjectDileptonAk8JetsInclusiveBoosted})
# selObjectDictList.append({'channel':'ElMu','selObject':ElMuSelObjectDileptonAk8JetsInclusiveBoosted})
dileptons = {'ElEl':OSElElDilepton[0],'MuMu':OSMuMuDilepton[0],'ElMu':OSElMuDilepton[0]}
for selObjectDict in selObjectDictList:
dilepton = dileptons[selObjectDict['channel']]
plots.extend(makeDoubleLeptonMachineLearningPlots(channel=selObjectDict['channel'],l1=dilepton[0],l2=dilepton[1],jets=self.ak4Jets,sel=selObjectDict['selObject'].sel,suffix=selObjectDict['selObject'].selName,model=LBN))
#----- Add the Yield plots -----#
plots.extend(self.yieldPlots.returnPlots())
#plots.extend(cutFlowPlots)
#----- Return -----#
return plots
def returnJetsMVAInputs(self,jets):
return {('j1_E', 'Lead jet E [GeV]', (50,0.,500.)) : op.switch(op.rng_len(jets)>0,jets[0].p4.E(),op.c_float(0.)),
('j1_Px', 'Lead jet P_x [GeV]', (40,-200.,200.)) : op.switch(op.rng_len(jets)>0,jets[0].p4.Px(),op.c_float(0.)),
('j1_Py', 'Lead jet P_y [GeV]', (40,-200.,200.)) : op.switch(op.rng_len(jets)>0,jets[0].p4.Py(),op.c_float(0.)),
('j1_Pz', 'Lead jet P_z [GeV]', (40,-200.,200.)) : op.switch(op.rng_len(jets)>0,jets[0].p4.Pz(),op.c_float(0.)),
('j1_btag', 'Lead jet btag score', (50,0.,1.) ) : op.switch(op.rng_len(jets)>0,jets[0].btagDeepFlavB,op.c_float(0.)),
('j2_E', 'Sublead jet E [GeV]', (50,0.,500.)) : op.switch(op.rng_len(jets)>1,jets[1].p4.E(),op.c_float(0.)),
('j2_Px', 'Sublead jet P_x [GeV]', (40,-200.,200.)) : op.switch(op.rng_len(jets)>1,jets[1].p4.Px(),op.c_float(0.)),
('j2_Py', 'Sublead jet P_y [GeV]', (40,-200.,200.)) : op.switch(op.rng_len(jets)>1,jets[1].p4.Py(),op.c_float(0.)),
('j2_Pz', 'Sublead jet P_z [GeV]', (40,-200.,200.)) : op.switch(op.rng_len(jets)>1,jets[1].p4.Pz(),op.c_float(0.)),
('j2_btag', 'Sublead jet btag score', (50,0.,1.) ) : op.switch(op.rng_len(jets)>1,jets[1].btagDeepFlavB,op.c_float(0.)),
('j3_E', 'Subsublead jet E [GeV]', (50,0.,500.)) : op.switch(op.rng_len(jets)>2,jets[2].p4.E(),op.c_float(0.)),
('j3_Px', 'Subsublead jet P_x [GeV]', (40,-200.,200.)) : op.switch(op.rng_len(jets)>2,jets[2].p4.Px(),op.c_float(0.)),
('j3_Py', 'Subsublead jet P_y [GeV]', (40,-200.,200.)) : op.switch(op.rng_len(jets)>2,jets[2].p4.Py(),op.c_float(0.)),
('j3_Pz', 'Subsublead jet P_z [GeV]', (40,-200.,200.)) : op.switch(op.rng_len(jets)>2,jets[2].p4.Pz(),op.c_float(0.)),
('j3_btag', 'Subsublead jet btag score', (50,0.,1.) ) : op.switch(op.rng_len(jets)>2,jets[2].btagDeepFlavB,op.c_float(0.)),
('j4_E', 'Subsubsublead jet E [GeV]', (50,0.,500.)) : op.switch(op.rng_len(jets)>3,jets[3].p4.E(),op.c_float(0.)),
('j4_Px', 'Subsubsublead jet P_x [GeV]', (40,-200.,200.)) : op.switch(op.rng_len(jets)>3,jets[3].p4.Px(),op.c_float(0.)),
('j4_Py', 'Subsubsublead jet P_y [GeV]', (40,-200.,200.)) : op.switch(op.rng_len(jets)>3,jets[3].p4.Py(),op.c_float(0.)),
('j4_Pz', 'Subsubsublead jet P_z [GeV]', (40,-200.,200.)) : op.switch(op.rng_len(jets)>3,jets[3].p4.Pz(),op.c_float(0.)),
('j4_btag', 'Subsubsublead jet btag score', (50,0.,1.) ) : op.switch(op.rng_len(jets)>3,jets[3].btagDeepFlavB,op.c_float(0.))}
def returnResonantMVAInputs(self, l1, l2, channel, jets, bjets, fatjets, met,
electrons, muons):
if channel == "ElEl":
l1conept = lambda l1: self.electron_conept[l1.idx]
l2conept = lambda l2: self.electron_conept[l2.idx]
elif channel == "MuMu":
l1conept = lambda l1: self.muon_conept[l1.idx]
l2conept = lambda l2: self.muon_conept[l2.idx]
elif channel == "ElMu":
l1conept = lambda l1: self.electron_conept[l1.idx]
l2conept = lambda l2: self.muon_conept[l2.idx]
else:
raise RuntimeError("Wrong channel")
dijets = op.combine(jets, N=2)
import bamboo.treeoperations as _to
def rng_min(rng, fun=(lambda x: x), typeName="float"):
return op._to.Reduce.fromRngFun(
rng, op.c_float(float("+inf"), typeName),
(lambda fn:
(lambda res, elm: op.extMethod("std::min", returnType="Float_t")
(res, fn(elm))))(fun))
if self.args.era is None:
era = op.c_int(int(self.era))
else:
era = op.c_int(int(self.args.era))
print(f'Using {self.args.era} as DNN input')
return {
('eventnr', 'Event number', (100, 0., 1e6)):
self.tree.event,
('era', 'Era', (3, 2016., 2019.)):
era,
('l1_E', 'Lead lepton E [GeV]', (50, 0., 500.)):
op.switch(l1conept(l1) >= l2conept(l2), l1.p4.E(), l2.p4.E()),
('l1_Px', 'Lead lepton P_x [GeV]', (40, -200., 200.)):
op.switch(l1conept(l1) >= l2conept(l2), l1.p4.Px(), l2.p4.Px()),
('l1_Py', 'Lead lepton P_y [GeV]', (40, -200., 200.)):
op.switch(l1conept(l1) >= l2conept(l2), l1.p4.Py(), l2.p4.Py()),
('l1_Pz', 'Lead lepton P_z [GeV]', (40, -200., 200.)):
op.switch(l1conept(l1) >= l2conept(l2), l1.p4.Pz(), l2.p4.Pz()),
('l1_charge', 'Lead lepton charge', (2, 0., 2.)):
op.switch(l1conept(l1) >= l2conept(l2), l1.charge, l2.charge),
('l1_pdgId', 'Lead lepton pdg ID', (45, -22., 22.)):
op.switch(l1conept(l1) >= l2conept(l2), l1.pdgId, l2.pdgId),
('l2_E', 'Sublead lepton E [GeV]', (50, 0., 500.)):
op.switch(l1conept(l1) >= l2conept(l2), l2.p4.E(), l1.p4.E()),
('l2_Px', 'Sublead lepton P_x [GeV]', (40, -200., 200.)):
op.switch(l1conept(l1) >= l2conept(l2), l2.p4.Px(), l1.p4.Px()),
('l2_Py', 'Sublead lepton P_y [GeV]', (40, -200., 200.)):
op.switch(l1conept(l1) >= l2conept(l2), l2.p4.Py(), l1.p4.Py()),
('l2_Pz', 'Sublead lepton P_z [GeV]', (40, -200., 200.)):
op.switch(l1conept(l1) >= l2conept(l2), l2.p4.Pz(), l1.p4.Pz()),
('l2_charge', 'Sublead lepton charge', (2, 0., 2.)):
op.switch(l1conept(l1) >= l2conept(l2), l2.charge, l1.charge),
('l2_pdgId', 'Sublead lepton pdg ID', (45, -22., 22.)):
op.switch(l1conept(l1) >= l2conept(l2), l2.pdgId, l1.pdgId),
('j1_E', 'Lead jet E [GeV]', (50, 0., 500.)):
op.switch(op.rng_len(jets) > 0, jets[0].p4.E(), op.c_float(0.)),
('j1_Px', 'Lead jet P_x [GeV]', (40, -200., 200.)):
op.switch(op.rng_len(jets) > 0, jets[0].p4.Px(), op.c_float(0.)),
('j1_Py', 'Lead jet P_y [GeV]', (40, -200., 200.)):
op.switch(op.rng_len(jets) > 0, jets[0].p4.Py(), op.c_float(0.)),
('j1_Pz', 'Lead jet P_z [GeV]', (40, -200., 200.)):
op.switch(op.rng_len(jets) > 0, jets[0].p4.Pz(), op.c_float(0.)),
('j2_E', 'Sublead jet E [GeV]', (50, 0., 500.)):
op.switch(op.rng_len(jets) > 1, jets[1].p4.E(), op.c_float(0.)),
('j2_Px', 'Sublead jet P_x [GeV]', (40, -200., 200.)):
op.switch(op.rng_len(jets) > 1, jets[1].p4.Px(), op.c_float(0.)),
('j2_Py', 'Sublead jet P_y [GeV]', (40, -200., 200.)):
op.switch(op.rng_len(jets) > 1, jets[1].p4.Py(), op.c_float(0.)),
('j2_Pz', 'Sublead jet P_z [GeV]', (40, -200., 200.)):
op.switch(op.rng_len(jets) > 1, jets[1].p4.Pz(), op.c_float(0.)),
('j3_E', 'Subsublead jet E [GeV]', (50, 0., 500.)):
op.switch(op.rng_len(jets) > 2, jets[2].p4.E(), op.c_float(0.)),
('j3_Px', 'Subsublead jet P_x [GeV]', (40, -200., 200.)):
op.switch(op.rng_len(jets) > 2, jets[2].p4.Px(), op.c_float(0.)),
('j3_Py', 'Subsublead jet P_y [GeV]', (40, -200., 200.)):
op.switch(op.rng_len(jets) > 2, jets[2].p4.Py(), op.c_float(0.)),
('j3_Pz', 'Subsublead jet P_z [GeV]', (40, -200., 200.)):
op.switch(op.rng_len(jets) > 2, jets[2].p4.Pz(), op.c_float(0.)),
('j4_E', 'Subsubsublead jet E [GeV]', (50, 0., 500.)):
op.switch(op.rng_len(jets) > 3, jets[3].p4.E(), op.c_float(0.)),
('j4_Px', 'Subsubsublead jet P_x [GeV]', (40, -200., 200.)):
op.switch(op.rng_len(jets) > 3, jets[3].p4.Px(), op.c_float(0.)),
('j4_Py', 'Subsubsublead jet P_y [GeV]', (40, -200., 200.)):
op.switch(op.rng_len(jets) > 3, jets[3].p4.Py(), op.c_float(0.)),
('j4_Pz', 'Subsubsublead jet P_z [GeV]', (40, -200., 200.)):
op.switch(op.rng_len(jets) > 3, jets[3].p4.Pz(), op.c_float(0.)),
('fatjet_E', 'Fatjet E [GeV]', (50, 0., 500.)):
op.switch(op.rng_len(fatjets) > 0, fatjets[0].p4.E(), op.c_float(0.)),
('fatjet_Px', 'Fatjet P_x [GeV]', (40, -200., 200.)):
op.switch(op.rng_len(fatjets) > 0, fatjets[0].p4.Px(), op.c_float(0.)),
('fatjet_Py', 'Fatjet P_y [GeV]', (40, -200., 200.)):
op.switch(op.rng_len(fatjets) > 0, fatjets[0].p4.Py(), op.c_float(0.)),
('fatjet_Pz', 'Fatjet P_z [GeV]', (40, -200., 200.)):
op.switch(op.rng_len(fatjets) > 0, fatjets[0].p4.Pz(), op.c_float(0.)),
('fatjet_tau1', 'Fatjet #tau_1', (50, 0., 1.)):
op.switch(op.rng_len(fatjets) > 0, fatjets[0].tau1, op.c_float(0.)),
('fatjet_tau2', 'Fatjet #tau_2', (50, 0., 1.)):
op.switch(op.rng_len(fatjets) > 0, fatjets[0].tau2, op.c_float(0.)),
('fatjet_tau3', 'Fatjet #tau_3', (50, 0., 1.)):
op.switch(op.rng_len(fatjets) > 0, fatjets[0].tau3, op.c_float(0.)),
('fatjet_tau4', 'Fatjet #tau_4', (50, 0., 1.)):
op.switch(op.rng_len(fatjets) > 0, fatjets[0].tau4, op.c_float(0.)),
('fatjet_softdrop', 'Fatjet softdrop mass [GeV]', (50, 0., 1000.)):
op.switch(
op.rng_len(fatjets) > 0, fatjets[0].msoftdrop, op.c_float(0.)),
('met_E', 'MET Energy', (50, 0., 500.)):
met.p4.E(),
('met_Px', 'MET P_x', (40, -200., 200.)):
met.p4.Px(),
('met_Py', 'MET P_y', (40, -200., 200.)):
met.p4.Py(),
('met_Pz', 'MET P_z', (40, -200., 200.)):
met.p4.Pz(),
('m_bb_bregcorr', 'Di-bjet invariant mass (regcorr) [GeV]', (100, 0., 1000.)):
op.multiSwitch(
(op.rng_len(bjets) == 0, op.c_float(0.)),
(op.rng_len(bjets) == 1, self.HLL.getCorrBp4(bjets[0]).M()),
op.invariant_mass(self.HLL.getCorrBp4(bjets[0]),
self.HLL.getCorrBp4(bjets[1]))),
('ht', 'HT(jets) [GeV]', (100, 0., 1000.)):
op.rng_sum(jets, lambda j: j.pt),
('min_dr_jets_lep1', 'Min(#Delta R(lead lepton,jets))', (25, 0., 5.)):
op.switch(
op.rng_len(jets) > 0,
op.switch(
l1conept(l1) >= l2conept(l2),
self.HLL.MinDR_part1_partCont(l1.p4, jets),
self.HLL.MinDR_part1_partCont(l2.p4, jets)), op.c_float(0.)),
('min_dr_jets_lep2', 'Min(#Delta R(sublead lepton,jets))', (25, 0., 5.)):
op.switch(
op.rng_len(jets) > 0,
op.switch(
l1conept(l1) >= l2conept(l2),
self.HLL.MinDR_part1_partCont(l2.p4, jets),
self.HLL.MinDR_part1_partCont(l1.p4, jets)), op.c_float(0.)),
('m_ll', 'Dilepton invariant mass [GeV]', (100, 0., 1000.)):
op.invariant_mass(l1.p4, l2.p4),
('dr_ll', 'Dilepton #Delta R', (25, 0., 5.)):
op.deltaR(l1.p4, l2.p4),
('min_dr_jet', 'Min(#Delta R(jets))', (25, 0., 5.)):
op.switch(
op.rng_len(dijets) > 0,
op.rng_min(dijets,
lambda dijet: op.deltaR(dijet[0].p4, dijet[1].p4)),
op.c_float(0.)),
('min_dphi_jet', 'Min(#Delta #Phi(jets))', (16, 0., 3.2)):
op.switch(
op.rng_len(dijets) > 0,
rng_min(
dijets,
lambda dijet: op.abs(op.deltaPhi(dijet[0].p4, dijet[1].p4)),
typeName='double'), op.c_float(0.)),
('m_hh_simplemet_bregcorr', 'M_{HH} (simple MET) (regcorr) [GeV]', (100, 0., 1000.)):
op.invariant_mass(
op.rng_sum(bjets,
lambda bjet: self.HLL.getCorrBp4(bjet),
start=self.HLL.empty_p4), l1.p4, l2.p4, met.p4),
('met_ld', 'MET_{LD}', (100, 0., 1000.)):
self.HLL.MET_LD_DL(met, jets, electrons, muons),
('dr_bb', 'Di-bjet #Delta R', (25, 0., 5.)):
op.switch(
op.rng_len(bjets) >= 2, op.deltaR(bjets[0].p4, bjets[1].p4),
op.c_float(0.)),
('min_dr_leps_b1', 'Min(#Delta R(lead bjet,dilepton))', (25, 0., 5.)):
op.switch(
op.rng_len(bjets) >= 1,
self.HLL.MinDR_part1_dipart(bjets[0].p4, [l1.p4, l2.p4]),
op.c_float(0.)),
('min_dr_leps_b2', 'Min(#Delta R(sublead bjet,dilepton))', (25, 0., 5.)):
op.switch(
op.rng_len(bjets) >= 2,
self.HLL.MinDR_part1_dipart(bjets[1].p4, [l1.p4, l2.p4]),
op.c_float(0.)),
('lep1_conept', 'Lead lepton cone-P_T [GeV]', (40, 0., 200.)):
op.switch(l1conept(l1) >= l2conept(l2), l1conept(l1), l2conept(l2)),
('lep2_conept', 'Sublead lepton cone-P_T [GeV]', (40, 0., 200.)):
op.switch(l1conept(l1) >= l2conept(l2), l2conept(l2), l1conept(l1)),
('mww_simplemet', 'M_{WW} (simple MET) [GeV]', (100, 0., 1000.)):
op.invariant_mass(l1.p4, l2.p4, met.p4),
('boosted_tag', 'Boosted tag', (2, 0., 2.)):
op.c_int(
op.OR(
op.rng_len(self.ak8BJets) > 0, # Boosted 1B
op.AND(
op.rng_len(self.ak8BJets) == 0, # Boosted 0B
op.rng_len(self.ak8Jets) > 0,
op.rng_len(self.ak4BJets) == 0))),
('dphi_met_dilep', 'Dilepton-MET #Delta #Phi', (32, -3.2, 3.2)):
op.abs(op.deltaPhi(met.p4, (l1.p4 + l2.p4))),
('dphi_met_dibjet', 'Dibjet-MET #Delta #Phi', (32, -3.2, 3.2)):
op.multiSwitch(
(op.rng_len(bjets) == 0, op.c_float(0.)),
(op.rng_len(bjets) == 1, op.abs(op.deltaPhi(met.p4, bjets[0].p4))),
op.abs(op.deltaPhi(met.p4, (bjets[0].p4 + bjets[1].p4)))),
('dr_dilep_dijet', 'Dilepton-dijet #Delta R', (25, 0., 5.)):
op.multiSwitch(
(op.rng_len(jets) == 0, op.c_float(0.)),
(op.rng_len(jets) == 1, op.deltaR((l1.p4 + l2.p4), jets[0].p4)),
op.deltaR((l1.p4 + l2.p4), (jets[0].p4 + jets[1].p4))),
('dr_dilep_dibjet', 'Dilepton-dibjet #Delta R', (25, 0., 5.)):
op.multiSwitch(
(op.rng_len(bjets) == 0, op.c_float(0.)),
(op.rng_len(bjets) == 1, op.deltaR((l1.p4 + l2.p4), bjets[0].p4)),
op.deltaR((l1.p4 + l2.p4), (bjets[0].p4 + bjets[1].p4))),
('m_T', 'Transverse mass', (100, 0., 1000.)):
op.sqrt(2 * (l1.p4 + l2.p4).Pt() * met.p4.E() *
(1 - op.cos((l1.p4 + l2.p4).Phi() - met.p4.Phi()))),
('cosThetaS_Hbb', 'Helicity angle between Hbb and bjet', (20, 0., 1.)):
op.switch(
op.rng_len(bjets) == 2,
op.extMethod("HHbbWWJPA::cosThetaS",
returnType="float")(bjets[0].p4, bjets[1].p4),
op.c_float(0.)),
('LBN_inputs', 'LBN inputs', None): [
op.switch(l1conept(l1) >= l2conept(l2), l1.p4.E(), l2.p4.E()),
op.switch(l1conept(l1) >= l2conept(l2), l1.p4.Px(), l2.p4.Px()),
op.switch(l1conept(l1) >= l2conept(l2), l1.p4.Py(), l2.p4.Py()),
op.switch(l1conept(l1) >= l2conept(l2), l1.p4.Pz(), l2.p4.Pz()),
op.switch(l1conept(l1) >= l2conept(l2), l2.p4.E(), l1.p4.E()),
op.switch(l1conept(l1) >= l2conept(l2), l2.p4.Px(), l1.p4.Px()),
op.switch(l1conept(l1) >= l2conept(l2), l2.p4.Py(), l1.p4.Py()),
op.switch(l1conept(l1) >= l2conept(l2), l2.p4.Pz(), l1.p4.Pz()),
op.switch(op.rng_len(jets) > 0, jets[0].p4.E(), op.c_float(0.)),
op.switch(op.rng_len(jets) > 0, jets[0].p4.Px(), op.c_float(0.)),
op.switch(op.rng_len(jets) > 0, jets[0].p4.Py(), op.c_float(0.)),
op.switch(op.rng_len(jets) > 0, jets[0].p4.Pz(), op.c_float(0.)),
op.switch(op.rng_len(jets) > 1, jets[1].p4.E(), op.c_float(0.)),
op.switch(op.rng_len(jets) > 1, jets[1].p4.Px(), op.c_float(0.)),
op.switch(op.rng_len(jets) > 1, jets[1].p4.Py(), op.c_float(0.)),
op.switch(op.rng_len(jets) > 1, jets[1].p4.Pz(), op.c_float(0.)),
op.switch(op.rng_len(jets) > 2, jets[2].p4.E(), op.c_float(0.)),
op.switch(op.rng_len(jets) > 2, jets[2].p4.Px(), op.c_float(0.)),
op.switch(op.rng_len(jets) > 2, jets[2].p4.Py(), op.c_float(0.)),
op.switch(op.rng_len(jets) > 2, jets[2].p4.Pz(), op.c_float(0.)),
op.switch(op.rng_len(jets) > 3, jets[3].p4.E(), op.c_float(0.)),
op.switch(op.rng_len(jets) > 3, jets[3].p4.Px(), op.c_float(0.)),
op.switch(op.rng_len(jets) > 3, jets[3].p4.Py(), op.c_float(0.)),
op.switch(op.rng_len(jets) > 3, jets[3].p4.Pz(), op.c_float(0.)),
op.switch(
op.rng_len(fatjets) > 0, fatjets[0].p4.E(), op.c_float(0.)),
op.switch(
op.rng_len(fatjets) > 0, fatjets[0].p4.Px(), op.c_float(0.)),
op.switch(
op.rng_len(fatjets) > 0, fatjets[0].p4.Py(), op.c_float(0.)),
op.switch(
op.rng_len(fatjets) > 0, fatjets[0].p4.Pz(), op.c_float(0.))
]
}
def defineSkimSelection(self, t, noSel, sample=None, sampleCfg=None):
noSel, PUWeight, corrMET, muons, electrons, AK4jets, AK8jets, bjets_resolved, bjets_boosted, categories, TwoLeptonsTwoJets_Resolved, TwoLeptonsTwoJets_Boosted, TwoLeptonsTwoBjets_Res, TwoLeptonsTwoBjets_Boo, TwoLeptonsTwoBjets_NoMETCut_Res, TwoLeptonsTwoBjets_NoMETCut_Boo, WorkingPoints = self.defineObjects(
t, noSel, sample, sampleCfg)
era = sampleCfg["era"]
isMC = self.isMC(sample)
if self.SetSel not in ["noSel", "catSel", "2Lep2Jets", "2Lep2bJets"]:
print('[Skimedtree_NanoHtoZA]: %s Unkown selection ' % self.SetSel)
sys.exit(0)
if self.SetRegion not in ["boosted", "resolved"]:
print(' Region of studies should be : boosted or resolved ! ')
sys.exit(0)
if self.SetRegion == "boosted":
self.SetTagger = "DeepCSV" # FIXME add later DeepDoubleB
else:
if self.SetTagger not in ["DeepFlavour", "DeepCSV"]:
print(
'[Skimedtree_NanoHtoZA]: %s Unknown tagger for resolved region'
% self.SetTagger)
sys.exit(0)
if self.SetCat not in categories.keys():
print('[Skimedtree_NanoHtoZA] channel %s not found in categories' %
self.SetCat)
print('Available channel are :')
print(categories.keys())
sys.exit(0)
if self.SetWP is None:
print(
'[Skimedtree_NanoHtoZA]: WP is MANDATORY, this is the working point as defined in the ZAtollbb_PreSelection.py'
)
sys.exit(0)
if self.SetWP not in WorkingPoints:
print(
'[Skimedtree_NanoHtoZA] WP %s not found in working points definitions'
% self.SetWP)
print(' --> define in settings first')
print(' In settings I found WPs: ')
print(WorkingPoints)
sys.exit(1)
key = self.SetTagger + self.SetWP
if self.SetRegion == "resolved":
jets = AK4jets
bjets = bjets_resolved
suffix = "AK4Jets"
elif self.SetRegion == "boosted":
jets = AK8jets
bjets = bjets_boosted
suffix = "AK8Jets"
else:
raise RuntimeError('ERROR : %s Unkown args' % self.SetRegion)
#variables to keep from the input tree
varsToKeep = {"run": None, "luminosityBlock": None, "event": None}
if isMC:
varsToKeep["MC_weight"] = t.genWeight
varsToKeep["PU_weight"] = PUWeight
if self.SetSel == "noSel":
FinalSel = noSel
# Muons && Electrons selections
for obj, flav in zip([muons, electrons], ["Muons", "Electrons"]):
varsToKeep["n%s" % flav] = op.static_cast(
"UInt_t", op.rng_len(obj))
varsToKeep["%s_pt" % flav] = op.map(obj, lambda lep: lep.pt)
varsToKeep["%s_eta" % flav] = op.map(obj, lambda lep: lep.eta)
varsToKeep["%s_phi" % flav] = op.map(obj, lambda lep: lep.phi)
# resolved or boosted
### Jets selections
varsToKeep["%s_pt" % suffix] = op.map(jets, lambda j: j.pt)
varsToKeep["%s_eta" % suffix] = op.map(jets, lambda j: j.eta)
varsToKeep["%s_phi" % suffix] = op.map(jets, lambda j: j.phi)
varsToKeep["n%s" % suffix] = op.static_cast(
"UInt_t", op.rng_len(jets))
# MET selections
varsToKeep["CorrMET_pt"] = corrMET.pt
varsToKeep["CorrMET_phi"] = corrMET.phi
for channel, (dilepton, catSel) in categories.items():
### Opposite sign leptons , Same Flavour selection
if self.SetSel == "catSel":
FinalSel = catSel
for i in range(2):
varsToKeep["lep{0}_pt_{1}".format(
i, self.SetCat)] = dilepton[i].p4.pt
varsToKeep["lep{0}_eta_{1}".format(
i, self.SetCat)] = dilepton[i].p4.eta
varsToKeep["lep{0}_phi_{1}".format(
i, self.SetCat)] = dilepton[i].p4.phi
ll_M = op.invariant_mass(dilepton[0].p4, dilepton[1].p4)
varsToKeep["ll_M_{0}".format(channel)] = ll_M
# boosted or resolved
### Two OS SF Leptons _ Two Jets selection
elif self.SetSel == "2Lep2Jets":
if self.SetRegion == "resolved":
FinalSel = TwoLeptonsTwoJets_Resolved.get(key)
elif self.SetRegion == "boosted":
FinaSel = TwoLeptonsTwoJets_Boosted.get(key)
lljj_M = (dilepton[0].p4 + dilepton[1].p4 + jets[0].p4 +
jets[1].p4).M()
jj_M = op.invariant_mass(jets[0].p4, jets[1].p4)
varsToKeep["lljj_M_{0}_{1}{2}_{3}".format(
self.SetRegion, self.SetTagger, self.SetWP,
self.SetCat)] = lljj_M
varsToKeep["jj_M_{0}_{1}{2}_{3}".format(
self.SetRegion, self.SetTagger, self.SetWP,
self.SetCat)] = jj_M
varsToKeep["nB_{0}_{1}{2}_{3}".format(
suffix, self.SetTagger, self.SetWP,
self.SetCat)] = op.static_cast("UInt_t", op.rng_len(bJets))
### Two OS SF Leptons _ Two bJets selection +MET cut (xy corr applied too )
elif self.SetSel == "2Lep2bJets":
bJets = safeget(bjets, self.SetTagger, self.SetWP)
if self.SetRegion == "resolved":
FinalSel = TwoLeptonsTwoBjets_Res.get(key)
elif self.SetRegion == "boosted":
FinalSel = TwoLeptonsTwoBjets_Boo.get(key)
llbb_M = (dilepton[0].p4 + dilepton[1].p4 + bJets[0].p4 +
bJets[1].p4).M()
bb_M = op.invariant_mass(bJets[0].p4 + bJets[1].p4)
varsToKeep["llbb_M_{0}_{1}{2}_{3}".format(
self.SetRegion, self.SetTagger, self.SetWP,
self.SetCat)] = llbb_M
varsToKeep["bb_M_{0}_{1}{2}_{3}".format(
self.SetRegion, self.SetTagger, self.SetWP,
self.SetCat)] = bb_M
varsToKeep["nB_{0}_{1}{2}_{3}".format(
suffix, self.SetTagger, self.SetWP,
self.SetCat)] = op.static_cast("UInt_t", op.rng_len(bJets))
else:
raise RuntimeError('ERROR : %s in selection args' %
self.SetSel)
#sample_weight=
#event_weight=
#total_weight=
#cross_section=
return FinalSel, varsToKeep
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 defineSkimSelection(self, t, noSel, sample=None, sampleCfg=None):
noSel = super(SkimmerNanoHHtobbWWSL,
self).prepareObjects(t,
noSel,
sample,
sampleCfg,
"SL",
forSkimmer=True)
# For the Skimmer, SF must not use defineOnFirstUse -> segmentation fault
era = sampleCfg['era']
# Initialize varsToKeep dict #
varsToKeep = dict()
#---------------------------------------------------------------------------------------#
# Selections #
#---------------------------------------------------------------------------------------#
# keep the exact same order of nodes as mentioned in respective JPA model xml files
ResolvedJPANodeList = [
'2b2Wj', '2b1Wj', '1b2Wj', '2b0Wj', '1b1Wj', '1b0Wj', '0b'
]
BoostedJPANodeList = ['Hbb2Wj', 'Hbb1Wj', 'Hbb0Wj']
# JPA Models
basepath = os.path.join(os.path.abspath(os.path.dirname(__file__)),
'MachineLearning', 'ml-models',
'JPA_Loose_ttH')
resolvedModelDict = getResolvedJpaModelDict(basepath,
ResolvedJPANodeList, era)
boostedModelDict = getBoostedJpaModelDict(basepath, BoostedJPANodeList,
era)
if not self.inclusive_sel:
#----- Check arguments -----#
jet_level = [
"Ak4", "Ak8", "Res2b2Wj", "Res2b1Wj", "Res2b0Wj", "Res1b2Wj",
"Res1b1Wj", "Res1b0Wj", "Res0b", "Hbb2Wj", "Hbb1Wj", "Hbb0Wj"
]
if [
boolean for (level, boolean) in self.args.__dict__.items()
if level in jet_level
].count(True) != 1:
raise RuntimeError(
"Only one of the jet arguments must be used, check --help")
if self.args.Channel not in ["El", "Mu"]:
raise RuntimeError("Channel must be either 'El' or 'Mu'")
#----- Lepton selection -----#
ElSelObj, MuSelObj = makeSingleLeptonSelection(
self, noSel, use_dd=False, fake_selection=self.args.FakeCR)
if self.args.Channel is None:
raise RuntimeError("You need to specify --Channel")
if self.args.Channel == "El":
selObj = ElSelObj
lep = self.electronsTightSel[0]
if self.args.Channel == "Mu":
selObj = MuSelObj
lep = self.muonsTightSel[0]
#----- Apply jet corrections -----#
ElSelObject.sel = self.beforeJetselection(ElSelObj.sel, 'El')
MuSelObject.sel = self.beforeJetselection(MuSelObj.sel, 'Mu')
#----- Jet selection -----#
if any([
self.args.__dict__[item] for item in [
"Ak4", "Res2b2Wj", "Res2b1Wj", "Res2b0Wj", "Res1b2Wj",
"Res1b1Wj", "Res1b0Wj", "Res0b"
]
]):
makeResolvedSelection(self, selObj)
if self.args.Channel == "El":
print('... Resolved :: El Channel')
L1out, L2out, selObjAndJetsPerJpaCatDict = findJPACategoryResolved(
self,
selObj,
lep,
self.muonsPreSel,
self.electronsPreSel,
self.ak4Jets,
self.ak4BJetsLoose,
self.ak4BJets,
self.corrMET,
resolvedModelDict,
t.event,
self.HLL,
ResolvedJPANodeList,
plot_yield=False)
if self.args.Channel == "Mu":
print('... Resolved :: Mu Channel')
L1out, L2out, selObjAndJetsPerJpaCatDict = findJPACategoryResolved(
self,
selObj,
lep,
self.muonsPreSel,
self.electronsPreSel,
self.ak4Jets,
self.ak4BJetsLoose,
self.ak4BJets,
self.corrMET,
resolvedModelDict,
t.event,
self.HLL,
ResolvedJPANodeList,
plot_yield=False)
if any([
self.args.__dict__[item]
for item in ["Ak8", "Hbb2Wj", "Hbb1Wj", "Hbb0Wj"]
]):
makeBoostedSelection(self, selObj)
if self.args.Channel == "El":
print('... Boosted :: El Channel')
L1out, L2out, selObjAndJetsPerJpaCatDict = findJPACategoryBoosted(
self,
selObj,
lep,
self.muonsPreSel,
self.electronsPreSel,
self.ak8BJets,
self.ak4JetsCleanedFromAk8b,
self.ak4BJetsLoose,
self.ak4BJets,
self.corrMET,
boostedModelDict,
t.event,
self.HLL,
BoostedJPANodeList,
plot_yield=False)
if self.args.Channel == "Mu":
print('... Boosted :: Mu Channel')
L1out, L2out, selObjAndJetsPerJpaCatDict = findJPACategoryBoosted(
self,
selObj,
lep,
self.muonsPreSel,
self.electronsPreSel,
self.ak8BJets,
self.ak4JetsCleanedFromAk8b,
self.ak4BJetsLoose,
self.ak4BJets,
self.corrMET,
boostedModelDict,
t.event,
self.HLL,
BoostedJPANodeList,
plot_yield=False)
if self.args.Res2b2Wj:
print("...... 2b2Wj")
selObj = selObjAndJetsPerJpaCatDict.get('2b2Wj')[0]
jpaJets = selObjAndJetsPerJpaCatDict.get('2b2Wj')[1]
jpaarg = "Res2b2Wj"
if self.args.Res2b1Wj:
print("...... 2b1Wj")
selObj = selObjAndJetsPerJpaCatDict.get('2b1Wj')[0]
jpaJets = selObjAndJetsPerJpaCatDict.get('2b1Wj')[1]
jpaarg = "Res2b1Wj"
if self.args.Res1b2Wj:
print("...... 1b2Wj")
selObj = selObjAndJetsPerJpaCatDict.get('1b2Wj')[0]
jpaJets = selObjAndJetsPerJpaCatDict.get('1b2Wj')[1]
jpaarg = "Res1b2Wj"
if self.args.Res2b0Wj:
print("...... 2b0Wj")
selObj = selObjAndJetsPerJpaCatDict.get('2b0Wj')[0]
jpaJets = selObjAndJetsPerJpaCatDict.get('2b0Wj')[1]
jpaarg = "Res2b0Wj"
if self.args.Res1b1Wj:
print("...... 1b1Wj")
selObj = selObjAndJetsPerJpaCatDict.get('1b1Wj')[0]
jpaJets = selObjAndJetsPerJpaCatDict.get('1b1Wj')[1]
jpaarg = "Res1b1Wj"
if self.args.Res1b0Wj:
print("...... 1b0Wj")
selObj = selObjAndJetsPerJpaCatDict.get('1b0Wj')[0]
jpaJets = selObjAndJetsPerJpaCatDict.get('1b0Wj')[1]
jpaarg = "Res1b0Wj"
if self.args.Res0b:
print("...... 0b")
selObj = selObjAndJetsPerJpaCatDict.get('0b')[0]
jpaJets = None
jpaarg = "Res0b"
#######################################
# Hbb2Wj : jet1 jet2 jet3 jet4
# Hbb1Wj : jet1 jet2 jet3 jet4=0
# Hbb0Wj : jet1 jet2 jet3=0 jet4=0
#######################################
if self.args.Hbb2Wj:
print("...... Hbb2Wj")
selObj = selObjAndJetsPerJpaCatDict.get('Hbb2Wj')[0]
jpaJets = selObjAndJetsPerJpaCatDict.get('Hbb2Wj')[1]
jpaarg = "Hbb2Wj"
if self.args.Hbb1Wj:
print("...... Hbb1Wj")
selObj = selObjAndJetsPerJpaCatDict.get('Hbb1Wj')[0]
jpaJets = selObjAndJetsPerJpaCatDict.get('Hbb1Wj')[1]
jpaarg = "Hbb1Wj"
if self.args.Hbb0Wj:
print("...... Hbb0Wj")
selObj = selObjAndJetsPerJpaCatDict.get('Hbb0Wj')[0]
jpaJets = None
jpaarg = "Hbb0Wj"
else:
noSel = self.beforeJetselection(noSel)
#---------------------------------------------------------------------------------------#
# Synchronization tree #
#---------------------------------------------------------------------------------------#
if self.args.Synchronization:
# Event variables #
varsToKeep["event"] = None # Already in tree
varsToKeep["run"] = None # Already in tree
varsToKeep["ls"] = t.luminosityBlock
varsToKeep["n_presel_mu"] = op.static_cast(
"UInt_t", op.rng_len(self.muonsPreSel))
varsToKeep["n_fakeablesel_mu"] = op.static_cast(
"UInt_t", op.rng_len(self.muonsFakeSel))
varsToKeep["n_mvasel_mu"] = op.static_cast(
"UInt_t", op.rng_len(self.muonsTightSel))
varsToKeep["n_presel_ele"] = op.static_cast(
"UInt_t", op.rng_len(self.electronsPreSel))
varsToKeep["n_fakeablesel_ele"] = op.static_cast(
"UInt_t", op.rng_len(self.electronsFakeSel))
varsToKeep["n_mvasel_ele"] = op.static_cast(
"UInt_t", op.rng_len(self.electronsTightSel))
varsToKeep["n_presel_ak4Jet"] = op.static_cast(
"UInt_t", op.rng_len(self.ak4Jets))
varsToKeep["n_presel_ak8Jet"] = op.static_cast(
"UInt_t", op.rng_len(self.ak8Jets))
varsToKeep["n_presel_ak8BJet"] = op.static_cast(
"UInt_t", op.rng_len(self.ak8BJets))
varsToKeep["n_loose_ak4BJet"] = op.static_cast(
"UInt_t", op.rng_len(self.ak4BJetsLoose))
varsToKeep["n_medium_ak4BJet"] = op.static_cast(
"UInt_t", op.rng_len(self.ak4BJets))
varsToKeep["n_ak4JetsCleanAk8b"] = op.static_cast(
"UInt_t", op.rng_len(self.ak4JetsCleanedFromAk8b))
varsToKeep["n_presel_ak4JetVBF"] = op.static_cast(
"UInt_t", op.rng_len(self.VBFJetsPreSel))
varsToKeep["is_SR"] = op.static_cast(
"UInt_t",
op.OR(
op.rng_len(self.electronsTightSel) == 1,
op.rng_len(self.muonsTightSel) == 1))
varsToKeep["is_e"] = op.c_float(
True) if self.args.Channel == 'El' else op.c_float(False)
varsToKeep["is_m"] = op.c_float(
False) if self.args.Channel == 'El' else op.c_float(True)
varsToKeep["is_resolved"] = op.switch(
op.AND(
op.rng_len(self.ak4Jets) >= 3,
op.rng_len(self.ak4BJets) >= 1,
op.rng_len(self.ak8BJets) == 0), op.c_bool(True),
op.c_bool(False))
varsToKeep["is_boosted"] = op.switch(
op.AND(
op.rng_len(self.ak8BJets) >= 1,
op.rng_len(self.ak4JetsCleanedFromAk8b) >= 1),
op.c_bool(True), op.c_bool(False))
varsToKeep["n_tau"] = op.static_cast("UInt_t",
op.rng_len(self.tauCleanSel))
varsToKeep['resolved_tag'] = op.static_cast(
"UInt_t",
op.AND(
op.rng_len(self.ak4Jets) >= 3,
op.rng_len(self.ak4BJets) >= 1,
op.rng_len(self.ak8BJets) == 0))
varsToKeep['boosted_tag'] = op.static_cast(
"UInt_t",
op.AND(
op.rng_len(self.ak8BJets) >= 1,
op.rng_len(self.ak4JetsCleanedFromAk8b) >= 1))
# Triggers #
'''
varsToKeep["triggers"] = self.triggers
varsToKeep["triggers_SingleElectron"] = op.OR(*self.triggersPerPrimaryDataset['SingleElectron'])
varsToKeep["triggers_SingleMuon"] = op.OR(*self.triggersPerPrimaryDataset['SingleMuon'])
varsToKeep["triggers_DoubleElectron"] = op.OR(*self.triggersPerPrimaryDataset['DoubleEGamma'])
varsToKeep["triggers_DoubleMuon"] = op.OR(*self.triggersPerPrimaryDataset['DoubleMuon'])
varsToKeep["triggers_MuonElectron"] = op.OR(*self.triggersPerPrimaryDataset['MuonEG'])
'''
# Muons #
for i in range(1, 3): # 2 leading muons
varsToKeep["mu{}_pt".format(i)] = op.switch(
op.rng_len(self.muonsPreSel) >= i,
self.muonsPreSel[i - 1].pt, op.c_float(-9999., "float"))
varsToKeep["mu{}_eta".format(i)] = op.switch(
op.rng_len(self.muonsPreSel) >= i,
self.muonsPreSel[i - 1].eta, op.c_float(-9999.))
varsToKeep["mu{}_phi".format(i)] = op.switch(
op.rng_len(self.muonsPreSel) >= i,
self.muonsPreSel[i - 1].phi, op.c_float(-9999.))
varsToKeep["mu{}_E".format(i)] = op.switch(
op.rng_len(self.muonsPreSel) >= i,
self.muonsPreSel[i - 1].p4.E(),
op.c_float(-9999., "float"))
varsToKeep["mu{}_charge".format(i)] = op.switch(
op.rng_len(self.muonsPreSel) >= i,
self.muonsPreSel[i - 1].charge, op.c_int(-9999.))
varsToKeep["mu{}_conept".format(i)] = op.switch(
op.rng_len(self.muonsPreSel) >= i,
self.muon_conept[self.muonsPreSel[i - 1].idx],
op.c_float(-9999.))
varsToKeep["mu{}_miniRelIso".format(i)] = op.switch(
op.rng_len(self.muonsPreSel) >= i,
self.muonsPreSel[i - 1].miniPFRelIso_all,
op.c_float(-9999.))
varsToKeep["mu{}_PFRelIso04".format(i)] = op.switch(
op.rng_len(self.muonsPreSel) >= i,
self.muonsPreSel[i - 1].pfRelIso04_all, op.c_float(-9999.))
varsToKeep["mu{}_jetNDauChargedMVASel".format(i)] = op.c_float(
-9999.)
varsToKeep["mu{}_jetPtRel".format(i)] = op.switch(
op.rng_len(self.muonsPreSel) >= i,
self.muonsPreSel[i - 1].jetPtRelv2, op.c_float(-9999.))
varsToKeep["mu{}_jetRelIso".format(i)] = op.switch(
op.rng_len(self.muonsPreSel) >= i,
self.muonsPreSel[i - 1].jetRelIso, op.c_float(-9999.))
varsToKeep["mu{}_jetDeepJet".format(i)] = op.switch(
op.rng_len(self.muonsPreSel) >= i,
self.muonsPreSel[i - 1].jet.btagDeepFlavB,
op.c_float(-9999.))
varsToKeep["mu{}_sip3D".format(i)] = op.switch(
op.rng_len(self.muonsPreSel) >= i,
self.muonsPreSel[i - 1].sip3d, op.c_float(-9999.))
varsToKeep["mu{}_dxy".format(i)] = op.switch(
op.rng_len(self.muonsPreSel) >= i,
self.muonsPreSel[i - 1].dxy, op.c_float(-9999.))
varsToKeep["mu{}_dxyAbs".format(i)] = op.switch(
op.rng_len(self.muonsPreSel) >= i,
op.abs(self.muonsPreSel[i - 1].dxy), op.c_float(-9999.))
varsToKeep["mu{}_dz".format(i)] = op.switch(
op.rng_len(self.muonsPreSel) >= i,
self.muonsPreSel[i - 1].dz, op.c_float(-9999.))
varsToKeep["mu{}_segmentCompatibility".format(i)] = op.switch(
op.rng_len(self.muonsPreSel) >= i,
self.muonsPreSel[i - 1].segmentComp, op.c_float(-9999.))
varsToKeep["mu{}_leptonMVA".format(i)] = op.switch(
op.rng_len(self.muonsPreSel) >= i,
self.muonsPreSel[i - 1].mvaTTH, op.c_float(-9999.))
varsToKeep["mu{}_mediumID".format(i)] = op.switch(
op.rng_len(self.muonsPreSel) >= i,
self.muonsPreSel[i - 1].mediumId,
op.c_float(-9999., "Bool_t"))
varsToKeep["mu{}_dpt_div_pt".format(i)] = op.switch(
op.rng_len(self.muonsPreSel) >= i,
self.muonsPreSel[i - 1].tunepRelPt,
op.c_float(-9999.)) # Not sure
varsToKeep["mu{}_isfakeablesel".format(i)] = op.switch(
op.rng_len(self.muonsPreSel) >= i,
op.switch(self.lambda_muonFakeSel(self.muonsPreSel[i - 1]),
op.c_int(1), op.c_int(0)), op.c_int(-9999))
varsToKeep["mu{}_ismvasel".format(i)] = op.switch(
op.rng_len(self.muonsPreSel) >= i,
op.switch(
op.AND(
self.lambda_muonTightSel(self.muonsPreSel[i - 1]),
self.lambda_muonFakeSel(self.muonsPreSel[i - 1])),
op.c_int(1), op.c_int(0)),
op.c_int(-9999)) # mvasel encompasses fakeablesel
varsToKeep["mu{}_isGenMatched".format(i)] = op.switch(
op.rng_len(self.muonsPreSel) >= i,
op.switch(self.lambda_is_matched(self.muonsPreSel[i - 1]),
op.c_int(1), op.c_int(0)), op.c_int(-9999))
varsToKeep["mu{}_genPartFlav".format(i)] = op.switch(
op.rng_len(self.muonsPreSel) >= i,
self.muonsPreSel[i - 1].genPartFlav, op.c_int(-9999))
varsToKeep["mu{}_FR".format(i)] = op.switch(
op.rng_len(self.muonsPreSel) >= i,
self.lambda_FR_mu(self.muonsPreSel[i - 1]),
op.c_int(-9999))
varsToKeep["mu{}_FRcorr".format(i)] = op.switch(
op.rng_len(self.muonsPreSel) >= i,
self.lambda_FRcorr_mu(self.muonsPreSel[i - 1]),
op.c_int(-9999))
varsToKeep["mu{}_FF".format(i)] = op.switch(
op.rng_len(self.muonsPreSel) >= i,
self.lambda_FF_mu(self.muonsPreSel[i - 1]),
op.c_int(-9999))
varsToKeep["mu{}_looseSF".format(i)] = op.switch(
op.rng_len(self.muonsPreSel) >= i,
reduce(mul,
self.lambda_MuonLooseSF(self.muonsPreSel[i - 1])),
op.c_int(-9999))
varsToKeep["mu{}_tightSF".format(i)] = op.switch(
op.rng_len(self.muonsPreSel) >= i,
reduce(mul,
self.lambda_MuonTightSF(self.muonsPreSel[i - 1])),
op.c_int(-9999))
# Electrons #
for i in range(1, 3): # 2 leading electrons
varsToKeep["ele{}_pt".format(i)] = op.switch(
op.rng_len(self.electronsPreSel) >= i,
self.electronsPreSel[i - 1].pt, op.c_float(-9999.))
varsToKeep["ele{}_eta".format(i)] = op.switch(
op.rng_len(self.electronsPreSel) >= i,
self.electronsPreSel[i - 1].eta, op.c_float(-9999.))
varsToKeep["ele{}_phi".format(i)] = op.switch(
op.rng_len(self.electronsPreSel) >= i,
self.electronsPreSel[i - 1].phi, op.c_float(-9999.))
varsToKeep["ele{}_E".format(i)] = op.switch(
op.rng_len(self.electronsPreSel) >= i,
self.electronsPreSel[i - 1].p4.E(), op.c_float(-9999., ))
varsToKeep["ele{}_charge".format(i)] = op.switch(
op.rng_len(self.electronsPreSel) >= i,
self.electronsPreSel[i - 1].charge, op.c_int(-9999.))
varsToKeep["ele{}_conept".format(i)] = op.switch(
op.rng_len(self.electronsPreSel) >= i,
self.electron_conept[self.electronsPreSel[i - 1].idx],
op.c_float(-9999.))
varsToKeep["ele{}_miniRelIso".format(i)] = op.switch(
op.rng_len(self.electronsPreSel) >= i,
self.electronsPreSel[i - 1].miniPFRelIso_all,
op.c_float(-9999.))
varsToKeep["ele{}_PFRelIso03".format(i)] = op.switch(
op.rng_len(self.electronsPreSel) >= i,
self.electronsPreSel[i - 1].pfRelIso03_all,
op.c_float(-9999.)) # Iso03, Iso04 not in NanoAOD
varsToKeep["ele{}_jetNDauChargedMVASel".format(
i)] = op.c_float(-9999.)
varsToKeep["ele{}_jetPtRel".format(i)] = op.switch(
op.rng_len(self.electronsPreSel) >= i,
self.electronsPreSel[i - 1].jetPtRelv2, op.c_float(-9999.))
varsToKeep["ele{}_jetRelIso".format(i)] = op.switch(
op.rng_len(self.electronsPreSel) >= i,
self.electronsPreSel[i - 1].jetRelIso, op.c_float(-9999.))
varsToKeep["ele{}_jetDeepJet".format(i)] = op.switch(
op.rng_len(self.electronsPreSel) >= i,
self.electronsPreSel[i - 1].jet.btagDeepFlavB,
op.c_float(-9999.))
varsToKeep["ele{}_sip3D".format(i)] = op.switch(
op.rng_len(self.electronsPreSel) >= i,
self.electronsPreSel[i - 1].sip3d, op.c_float(-9999.))
varsToKeep["ele{}_dxy".format(i)] = op.switch(
op.rng_len(self.electronsPreSel) >= i,
self.electronsPreSel[i - 1].dxy, op.c_float(-9999.))
varsToKeep["ele{}_dxyAbs".format(i)] = op.switch(
op.rng_len(self.electronsPreSel) >= i,
op.abs(self.electronsPreSel[i - 1].dxy),
op.c_float(-9999.))
varsToKeep["ele{}_dz".format(i)] = op.switch(
op.rng_len(self.electronsPreSel) >= i,
self.electronsPreSel[i - 1].dz, op.c_float(-9999.))
varsToKeep["ele{}_ntMVAeleID".format(i)] = op.switch(
op.rng_len(self.electronsPreSel) >= i,
self.electronsPreSel[i - 1].mvaFall17V2noIso,
op.c_float(-9999.))
varsToKeep["ele{}_leptonMVA".format(i)] = op.switch(
op.rng_len(self.electronsPreSel) >= i,
self.electronsPreSel[i - 1].mvaTTH, op.c_float(-9999.))
varsToKeep["ele{}_passesConversionVeto".format(i)] = op.switch(
op.rng_len(self.electronsPreSel) >= i,
self.electronsPreSel[i - 1].convVeto,
op.c_float(-9999., "Bool_t"))
varsToKeep["ele{}_nMissingHits".format(i)] = op.switch(
op.rng_len(self.electronsPreSel) >= i,
self.electronsPreSel[i - 1].lostHits,
op.c_float(-9999., "UChar_t"))
varsToKeep["ele{}_sigmaEtaEta".format(i)] = op.switch(
op.rng_len(self.electronsPreSel) >= i,
self.electronsPreSel[i - 1].sieie, op.c_float(-9999.))
varsToKeep["ele{}_HoE".format(i)] = op.switch(
op.rng_len(self.electronsPreSel) >= i,
self.electronsPreSel[i - 1].hoe, op.c_float(-9999.))
varsToKeep["ele{}_OoEminusOoP".format(i)] = op.switch(
op.rng_len(self.electronsPreSel) >= i,
self.electronsPreSel[i - 1].eInvMinusPInv,
op.c_float(-9999.))
varsToKeep["ele{}_isfakeablesel".format(i)] = op.switch(
op.rng_len(self.electronsPreSel) >= i,
op.switch(
self.lambda_electronFakeSel(self.electronsPreSel[i -
1]),
op.c_int(1), op.c_int(0)), op.c_int(-9999))
varsToKeep["ele{}_ismvasel".format(i)] = op.switch(
op.rng_len(self.electronsPreSel) >= i,
op.switch(
op.AND(
self.lambda_electronTightSel(
self.electronsPreSel[i - 1]),
self.lambda_electronFakeSel(
self.electronsPreSel[i - 1])), op.c_int(1),
op.c_int(0)),
op.c_int(-9999)) # mvasel encompasses fakeablesel
varsToKeep["ele{}_isGenMatched".format(i)] = op.switch(
op.rng_len(self.electronsPreSel) >= i,
op.switch(
self.lambda_is_matched(self.electronsPreSel[i - 1]),
op.c_int(1), op.c_int(0)), op.c_int(-9999))
varsToKeep["ele{}_genPartFlav".format(i)] = op.switch(
op.rng_len(self.electronsPreSel) >= i,
self.electronsPreSel[i - 1].genPartFlav, op.c_int(-9999))
varsToKeep["ele{}_deltaEtaSC".format(i)] = op.switch(
op.rng_len(self.electronsPreSel) >= i,
self.electronsPreSel[i - 1].deltaEtaSC, op.c_int(-9999))
varsToKeep["ele{}_FR".format(i)] = op.switch(
op.rng_len(self.electronsPreSel) >= i,
self.lambda_FR_el(self.electronsPreSel[i - 1]),
op.c_int(-9999))
varsToKeep["ele{}_FRcorr".format(i)] = op.switch(
op.rng_len(self.electronsPreSel) >= i,
self.lambda_FRcorr_el(self.electronsPreSel[i - 1]),
op.c_int(-9999))
varsToKeep["ele{}_FF".format(i)] = op.switch(
op.rng_len(self.electronsPreSel) >= i,
self.lambda_FF_el(self.electronsPreSel[i - 1]),
op.c_int(-9999))
varsToKeep["ele{}_looseSF".format(i)] = op.switch(
op.rng_len(self.electronsPreSel) >= i,
reduce(
mul,
self.lambda_ElectronLooseSF(self.electronsPreSel[i -
1])),
op.c_int(-9999))
varsToKeep["ele{}_tightSF".format(i)] = op.switch(
op.rng_len(self.electronsPreSel) >= i,
reduce(
mul,
self.lambda_ElectronTightSF(self.electronsPreSel[i -
1])),
op.c_int(-9999))
# AK4 Jets #
for i in range(1, 5): # 4 leading jets
varsToKeep["ak4Jet{}_pt".format(i)] = op.switch(
op.rng_len(self.ak4Jets) >= i, self.ak4Jets[i - 1].pt,
op.c_float(-9999.))
varsToKeep["ak4Jet{}_eta".format(i)] = op.switch(
op.rng_len(self.ak4Jets) >= i, self.ak4Jets[i - 1].eta,
op.c_float(-9999.))
varsToKeep["ak4Jet{}_phi".format(i)] = op.switch(
op.rng_len(self.ak4Jets) >= i, self.ak4Jets[i - 1].phi,
op.c_float(-9999.))
varsToKeep["ak4Jet{}_E".format(i)] = op.switch(
op.rng_len(self.ak4Jets) >= i, self.ak4Jets[i - 1].p4.E(),
op.c_float(-9999.))
varsToKeep["ak4Jet{}_CSV".format(i)] = op.switch(
op.rng_len(self.ak4Jets) >= i,
self.ak4Jets[i - 1].btagDeepFlavB, op.c_float(-9999.))
varsToKeep["ak4Jet{}_hadronFlavour".format(i)] = op.switch(
op.rng_len(self.ak4Jets) >= i,
self.ak4Jets[i - 1].hadronFlavour, op.c_float(-9999.))
varsToKeep["ak4Jet{}_btagSF".format(i)] = op.switch(
op.rng_len(self.ak4Jets) >= i,
self.DeepJetDiscReshapingSF(self.ak4Jets[i - 1]),
op.c_float(-9999.))
varsToKeep["ak4Jet{}_puid_eff".format(i)] = op.switch(
op.rng_len(self.ak4Jets) >= i,
self.jetpuid_mc_eff(self.ak4Jets[i - 1]),
op.c_float(-9999.))
varsToKeep["ak4Jet{}_puid_sfeff".format(i)] = op.switch(
op.rng_len(self.ak4Jets) >= i,
self.jetpuid_sf_eff(self.ak4Jets[i - 1]),
op.c_float(-9999.))
varsToKeep["ak4Jet{}_puid_mis".format(i)] = op.switch(
op.rng_len(self.ak4Jets) >= i,
self.jetpuid_mc_mis(self.ak4Jets[i - 1]),
op.c_float(-9999.))
varsToKeep["ak4Jet{}_puid_sfmis".format(i)] = op.switch(
op.rng_len(self.ak4Jets) >= i,
self.jetpuid_sf_mis(self.ak4Jets[i - 1]),
op.c_float(-9999.))
# VBF Jets #
for i in range(1, 6): # 5 leading jets
varsToKeep["ak4JetVBF{}_pt".format(i)] = op.switch(
op.rng_len(self.VBFJetsPreSel) >= i,
self.VBFJetsPreSel[i - 1].pt, op.c_float(-9999.))
varsToKeep["ak4JetVBF{}_eta".format(i)] = op.switch(
op.rng_len(self.VBFJetsPreSel) >= i,
self.VBFJetsPreSel[i - 1].eta, op.c_float(-9999.))
varsToKeep["ak4JetVBF{}_phi".format(i)] = op.switch(
op.rng_len(self.VBFJetsPreSel) >= i,
self.VBFJetsPreSel[i - 1].phi, op.c_float(-9999.))
varsToKeep["ak4JetVBF{}_E".format(i)] = op.switch(
op.rng_len(self.VBFJetsPreSel) >= i,
self.VBFJetsPreSel[i - 1].p4.E(), op.c_float(-9999.))
varsToKeep["ak4JetVBF{}_CSV".format(i)] = op.switch(
op.rng_len(self.VBFJetsPreSel) >= i,
self.VBFJetsPreSel[i - 1].btagDeepFlavB,
op.c_float(-9999.))
varsToKeep["ak4JetVBF{}_btagSF".format(i)] = op.switch(
op.rng_len(self.VBFJetsPreSel) >= i,
self.DeepJetDiscReshapingSF(self.VBFJetsPreSel[i - 1]),
op.c_float(-9999.))
if not self.inclusive_sel:
if not any([self.args.Res0b, self.args.Ak4, self.args.Ak8]):
varsToKeep["ak4JetVBFPair1_pt"] = op.switch(
op.rng_len(VBFJetPairsJPA) >= 1,
VBFJetPairsJPA[0][0].pt, op.c_float(-9999.))
varsToKeep["ak4JetVBFPair1_eta"] = op.switch(
op.rng_len(VBFJetPairsJPA) >= 1,
VBFJetPairsJPA[0][0].eta, op.c_float(-9999.))
varsToKeep["ak4JetVBFPair1_phi"] = op.switch(
op.rng_len(VBFJetPairsJPA) >= 1,
VBFJetPairsJPA[0][0].phi, op.c_float(-9999.))
varsToKeep["ak4JetVBFPair1_E"] = op.switch(
op.rng_len(VBFJetPairsJPA) >= 1,
VBFJetPairsJPA[0][0].p4.E(), op.c_float(-9999.))
varsToKeep["ak4JetVBFPair1_CSV"] = op.switch(
op.rng_len(VBFJetPairsJPA) >= 1,
VBFJetPairsJPA[0][0].btagDeepFlavB, op.c_float(-9999.))
varsToKeep["ak4JetVBFPair1_btagSF"] = op.switch(
op.rng_len(VBFJetPairsJPA) >= 1,
self.DeepJetDiscReshapingSF(VBFJetPairsJPA[0][0]),
op.c_float(-9999.))
varsToKeep["ak4JetVBFPair2_pt"] = op.switch(
op.rng_len(VBFJetPairsJPA) >= 1,
VBFJetPairsJPA[0][1].pt, op.c_float(-9999.))
varsToKeep["ak4JetVBFPair2_eta"] = op.switch(
op.rng_len(VBFJetPairsJPA) >= 1,
VBFJetPairsJPA[0][1].eta, op.c_float(-9999.))
varsToKeep["ak4JetVBFPair2_phi"] = op.switch(
op.rng_len(VBFJetPairsJPA) >= 1,
VBFJetPairsJPA[0][1].phi, op.c_float(-9999.))
varsToKeep["ak4JetVBFPair2_E"] = op.switch(
op.rng_len(VBFJetPairsJPA) >= 1,
VBFJetPairsJPA[0][1].p4.E(), op.c_float(-9999.))
varsToKeep["ak4JetVBFPair2_CSV"] = op.switch(
op.rng_len(VBFJetPairsJPA) >= 1,
VBFJetPairsJPA[0][1].btagDeepFlavB, op.c_float(-9999.))
varsToKeep["ak4JetVBFPair2_btagSF"] = op.switch(
op.rng_len(VBFJetPairsJPA) >= 1,
self.DeepJetDiscReshapingSF(VBFJetPairsJPA[0][1]),
op.c_float(-9999.))
else:
varsToKeep["ak4JetVBFPair1_pt"] = op.c_float(-9999.)
varsToKeep["ak4JetVBFPair1_eta"] = op.c_float(-9999.)
varsToKeep["ak4JetVBFPair1_phi"] = op.c_float(-9999.)
varsToKeep["ak4JetVBFPair1_E"] = op.c_float(-9999.)
varsToKeep["ak4JetVBFPair1_CSV"] = op.c_float(-9999.)
varsToKeep["ak4JetVBFPair1_btagSF"] = op.c_float(-9999.)
varsToKeep["ak4JetVBFPair2_pt"] = op.c_float(-9999.)
varsToKeep["ak4JetVBFPair2_eta"] = op.c_float(-9999.)
varsToKeep["ak4JetVBFPair2_phi"] = op.c_float(-9999.)
varsToKeep["ak4JetVBFPair2_E"] = op.c_float(-9999.)
varsToKeep["ak4JetVBFPair2_CSV"] = op.c_float(-9999.)
varsToKeep["ak4JetVBFPair2_btagSF"] = op.c_float(-9999.)
# AK8 Jets #
for i in range(1, 3): # 2 leading fatjets
varsToKeep["ak8Jet{}_pt".format(i)] = op.switch(
op.rng_len(self.ak8BJets) >= i, self.ak8BJets[i - 1].pt,
op.c_float(-9999.))
varsToKeep["ak8Jet{}_eta".format(i)] = op.switch(
op.rng_len(self.ak8BJets) >= i, self.ak8BJets[i - 1].eta,
op.c_float(-9999.))
varsToKeep["ak8Jet{}_phi".format(i)] = op.switch(
op.rng_len(self.ak8BJets) >= i, self.ak8BJets[i - 1].phi,
op.c_float(-9999.))
varsToKeep["ak8Jet{}_E".format(i)] = op.switch(
op.rng_len(self.ak8BJets) >= i,
self.ak8BJets[i - 1].p4.E(), op.c_float(-9999.))
varsToKeep["ak8Jet{}_msoftdrop".format(i)] = op.switch(
op.rng_len(self.ak8BJets) >= i,
self.ak8BJets[i - 1].msoftdrop, op.c_float(-9999.))
varsToKeep["ak8Jet{}_tau1".format(i)] = op.switch(
op.rng_len(self.ak8BJets) >= i, self.ak8BJets[i - 1].tau1,
op.c_float(-9999.))
varsToKeep["ak8Jet{}_tau2".format(i)] = op.switch(
op.rng_len(self.ak8BJets) >= i, self.ak8BJets[i - 1].tau2,
op.c_float(-9999.))
varsToKeep["ak8Jet{}_subjet0_pt".format(i)] = op.switch(
op.rng_len(self.ak8BJets) >= i,
self.ak8BJets[i - 1].subJet1.pt, op.c_float(-9999.))
varsToKeep["ak8Jet{}_subjet0_eta".format(i)] = op.switch(
op.rng_len(self.ak8BJets) >= i,
self.ak8BJets[i - 1].subJet1.eta, op.c_float(-9999.))
varsToKeep["ak8Jet{}_subjet0_phi".format(i)] = op.switch(
op.rng_len(self.ak8BJets) >= i,
self.ak8BJets[i - 1].subJet1.phi, op.c_float(-9999.))
varsToKeep["ak8Jet{}_subjet0_CSV".format(i)] = op.switch(
op.rng_len(self.ak8BJets) >= i,
self.ak8BJets[i - 1].subJet1.btagDeepB, op.c_float(-9999.))
varsToKeep["ak8Jet{}_subjet1_pt".format(i)] = op.switch(
op.rng_len(self.ak8BJets) >= i,
self.ak8BJets[i - 1].subJet2.pt, op.c_float(-9999.))
varsToKeep["ak8Jet{}_subjet1_eta".format(i)] = op.switch(
op.rng_len(self.ak8BJets) >= i,
self.ak8BJets[i - 1].subJet2.eta, op.c_float(-9999.))
varsToKeep["ak8Jet{}_subjet1_phi".format(i)] = op.switch(
op.rng_len(self.ak8BJets) >= i,
self.ak8BJets[i - 1].subJet2.phi, op.c_float(-9999.))
varsToKeep["ak8Jet{}_subjet1_CSV".format(i)] = op.switch(
op.rng_len(self.ak8BJets) >= i,
self.ak8BJets[i - 1].subJet2.btagDeepB, op.c_float(-9999.))
varsToKeep["PFMET"] = self.corrMET.pt
varsToKeep["PFMETphi"] = self.corrMET.phi
varsToKeep["met1_E"] = self.corrMET.p4.E()
varsToKeep["met1_pt"] = self.corrMET.pt
varsToKeep["met1_eta"] = self.corrMET.eta
varsToKeep["met1_phi"] = self.corrMET.phi
# SF #
electronMuon_cont = op.combine(
(self.electronsFakeSel, self.muonsFakeSel))
varsToKeep["trigger_SF"] = op.multiSwitch(
(op.AND(
op.rng_len(self.electronsTightSel) == 1,
op.rng_len(self.muonsTightSel) == 0),
self.ttH_singleElectron_trigSF(self.electronsTightSel[0])),
(op.AND(
op.rng_len(self.electronsTightSel) == 0,
op.rng_len(self.muonsTightSel)
== 1), self.ttH_singleMuon_trigSF(self.muonsTightSel[0])),
(op.AND(
op.rng_len(self.electronsTightSel) >= 2,
op.rng_len(self.muonsTightSel) == 0),
self.lambda_ttH_doubleElectron_trigSF(
self.electronsTightSel)),
(op.AND(
op.rng_len(self.electronsTightSel) == 0,
op.rng_len(self.muonsTightSel) >= 2),
self.lambda_ttH_doubleMuon_trigSF(self.muonsTightSel)),
(op.AND(
op.rng_len(self.electronsTightSel) >= 1,
op.rng_len(self.muonsTightSel) >= 1),
self.lambda_ttH_electronMuon_trigSF(electronMuon_cont[0])),
op.c_float(1.))
if not self.inclusive_sel:
varsToKeep["weight_trigger_el_sf"] = op.switch(
op.rng_len(self.electronsTightSel) > 0,
self.ttH_singleElectron_trigSF(lep), op.c_float(1.))
varsToKeep["weight_trigger_mu_sf"] = op.switch(
op.rng_len(self.muonsTightSel) > 0,
self.ttH_singleMuon_trigSF(lep), op.c_float(1.))
varsToKeep["lepton_IDSF"] = op.rng_product(self.electronsFakeSel, lambda el : reduce(mul,self.lambda_ElectronLooseSF(el)+self.lambda_ElectronTightSF(el))) * \
op.rng_product(self.muonsFakeSel, lambda mu : reduce(mul,self.lambda_MuonLooseSF(mu)+self.lambda_MuonTightSF(mu)))
varsToKeep["lepton_IDSF_recoToLoose"] = op.rng_product(self.electronsFakeSel, lambda el : reduce(mul,self.lambda_ElectronLooseSF(el))) * \
op.rng_product(self.muonsFakeSel, lambda mu : reduce(mul,self.lambda_MuonLooseSF(mu)))
varsToKeep["lepton_IDSF_looseToTight"] = op.rng_product(self.electronsFakeSel, lambda el : reduce(mul,self.lambda_ElectronTightSF(el))) * \
op.rng_product(self.muonsFakeSel, lambda mu : reduce(mul,self.lambda_MuonTightSF(mu)))
if era == "2016" or era == "2017":
if self.args.Channel == "El":
varsToKeep["weight_electron_reco_low"] = op.switch(
op.AND(self.lambda_is_matched(lep), lep.pt <= 20.),
self.elLooseRecoPtLt20(lep), op.c_float(1.))
varsToKeep["weight_electron_reco_high"] = op.switch(
op.AND(self.lambda_is_matched(lep), lep.pt > 20.),
self.elLooseRecoPtGt20(lep), op.c_float(1.))
varsToKeep["weight_muon_idiso_loose"] = op.c_float(1.)
varsToKeep["weight_electron_id_loose_01"] = op.switch(
self.lambda_is_matched(lep), self.elLooseEff(lep),
op.c_float(1.))
varsToKeep["weight_electron_id_loose_02"] = op.switch(
self.lambda_is_matched(lep), self.elLooseId(lep),
op.c_float(1.))
varsToKeep[
"weight_electron_tth_loose"] = self.lambda_ElectronTightSF(
lep)[0]
varsToKeep["weight_muon_tth_loose"] = op.c_float(1.)
if self.args.Channel == "Mu":
varsToKeep["weight_muon_idiso_loose"] = op.switch(
self.lambda_is_matched(lep), self.muLooseId(lep),
op.c_float(1.))
varsToKeep["weight_electron_reco_low"] = op.c_float(1.)
varsToKeep["weight_electron_reco_high"] = op.c_float(
1.)
varsToKeep["weight_electron_id_loose_01"] = op.c_float(
1.)
varsToKeep["weight_electron_id_loose_02"] = op.c_float(
1.)
varsToKeep["weight_electron_tth_loose"] = op.c_float(
1.)
varsToKeep[
"weight_muon_tth_loose"] = self.lambda_MuonTightSF(
lep)[0]
else:
raise NotImplementedError
# L1 Prefire #
if era in ["2016", "2017"]:
varsToKeep["L1prefire"] = self.L1Prefiring
varsToKeep["weight_l1_ecal_prefiring"] = self.L1Prefiring
else:
varsToKeep["L1prefire"] = op.c_float(-9999.)
varsToKeep["weight_l1_ecal_prefiring"] = op.c_float(-9999.)
# Fake rate #
if self.args.Channel == "El":
varsToKeep["fakeRate"] = op.switch(
self.lambda_electronTightSel(self.electronsFakeSel[0]),
self.ElFakeFactor(self.electronsFakeSel[0]),
op.c_float(1.))
varsToKeep["weight_fake_electrons"] = op.switch(
self.lambda_electronTightSel(self.electronsFakeSel[0]),
op.abs(self.ElFakeFactor(self.electronsFakeSel[0])),
op.c_float(1.))
varsToKeep["weight_fake_muons"] = op.c_float(1.)
varsToKeep["weight_fake_two_non_tight"] = op.c_float(999.0)
if self.args.Channel == "Mu":
varsToKeep["fakeRate"] = op.switch(
self.lambda_muonTightSel(self.muonsFakeSel[0]),
self.MuFakeFactor(self.muonsFakeSel[0]), op.c_float(1.))
varsToKeep["weight_fake_electrons"] = op.c_float(1.)
varsToKeep["weight_fake_muons"] = op.switch(
self.lambda_muonTightSel(self.muonsFakeSel[0]),
op.abs(self.MuFakeFactor(self.muonsFakeSel[0])),
op.c_float(1.))
varsToKeep["weight_fake_two_non_tight"] = op.c_float(999.0)
if self.is_MC:
varsToKeep["weight_fake_is_mc"] = op.c_float(-1.)
else:
varsToKeep["weight_fake_is_mc"] = op.c_float(1.)
# PU ID SF #
varsToKeep["PU_jetID_SF"] = self.puid_reweighting
varsToKeep[
"weight_jet_PUid_efficiency"] = self.puid_reweighting_efficiency
varsToKeep["weight_jet_PUid_mistag"] = self.puid_reweighting_mistag
# Btagging SF #
varsToKeep["btag_SF"] = self.btagAk4SF
varsToKeep["weight_btagWeight"] = self.btagAk4SF
if "BtagRatioWeight" in self.__dict__.keys():
varsToKeep["btag_ratio_SF"] = self.BtagRatioWeight
varsToKeep["weight_btagNorm"] = self.BtagRatioWeight
# PS weights #
varsToKeep["weight_PSWeight_ISR"] = self.psISRSyst
varsToKeep["weight_PSWeight_FSR"] = self.psFSRSyst
# ttbar PT reweighting #
if "group" in sampleCfg and sampleCfg["group"] == 'ttbar':
varsToKeep["topPt_wgt"] = self.ttbar_weight(
self.genTop[0], self.genAntitop[0])
# Event Weight #
if self.is_MC:
varsToKeep["MC_weight"] = t.genWeight
puWeightsFile = os.path.join(os.path.dirname(__file__), "data",
"pileup",
sample + '_%s.json' % era)
#puWeightsFile = os.path.join(os.path.dirname(__file__), "data" , "pileup", sampleCfg["pufile"])
varsToKeep["PU_weight"] = makePileupWeight(
puWeightsFile,
t.Pileup_nTrueInt,
nameHint=f"puweightFromFile{sample}".replace('-', '_'))
varsToKeep[
"eventWeight"] = noSel.weight if self.inclusive_sel else selObj.sel.weight
if self.inclusive_sel:
return noSel, varsToKeep
else:
return selObj.sel, varsToKeep
#---------------------------------------------------------------------------------------#
# Selection tree #
#---------------------------------------------------------------------------------------#
#----- EVT variables -----#
varsToKeep["event"] = None # Already in tree
varsToKeep["run"] = None # Already in tree
varsToKeep["ls"] = t.luminosityBlock
genVarsList = self.HLL.comp_cosThetaSbetBeamAndHiggs(t.GenPart)
varsToKeep['mHH_gen'] = genVarsList[0]
varsToKeep['consTheta1_gen'] = genVarsList[1]
varsToKeep['consTheta2_gen'] = genVarsList[2]
if any([
self.args.__dict__[item] for item in [
"Ak4", "Res2b2Wj", "Res2b1Wj", "Res2b0Wj", "Res1b2Wj",
"Res1b1Wj", "Res1b0Wj", "Res0b"
]
]):
commonInputs_Resolved = returnCommonInputs_Resolved(self=self)
classicInputs_Resolved = returnClassicInputs_Resolved(
self=self,
lepton=lep,
jpaSelectedJets=jpaJets,
L1out=L1out,
L2out=L2out,
jpaArg=jpaarg)
inputs_resolved = {
**commonInputs_Resolved,
**classicInputs_Resolved
}
for (varname, _, _), var in inputs_resolved.items():
varsToKeep[varname] = var
#----- Fatjet variables -----#
if any([
self.args.__dict__[item]
for item in ["Ak8", "Hbb2Wj", "Hbb1Wj", "Hbb0Wj"]
]):
commonInputs_Boosted = returnCommonInputs_Boosted(self=self)
classicInputs_Boosted = returnClassicInputs_Boosted(
self=self,
lepton=lep,
jpaSelectedJets=jpaJets,
L1out=L1out,
L2out=L2out,
jpaArg=jpaarg)
inputs_boosted = {**commonInputs_Boosted, **classicInputs_Boosted}
for (varname, _, _), var in inputs_boosted.items():
varsToKeep[varname] = var
#----- Additional variables -----#
varsToKeep["MC_weight"] = t.genWeight
varsToKeep['total_weight'] = selObj.sel.weight
#return leptonSel.sel, varsToKeep
return selObj.sel, varsToKeep
def definePlots(self, tree, noSel, sample=None, sampleCfg=None):
from bamboo.plots import Plot, SummedPlot
from bamboo.plots import EquidistantBinning as EqBin
from bamboo import treefunctions as op
if self.args.examples == "all":
examples = list(i+1 for i in range(self.nExamples)) # 1-4 are fine, so is 7
else:
examples = list(set(int(tk) for tk in self.args.examples.split(",")))
logger.info("Running the following examples: {0}".format(",".join(str(i) for i in examples)))
plots = []
if 1 in examples:
## Example 1: Plot the missing ET of all events.
plots.append(Plot.make1D("Ex1_MET",
tree.MET.pt, noSel,
EqBin(100, 0., 2000.), title="MET (GeV)"))
if 2 in examples:
## Example 2: Plot pT of all jets in all events.
plots.append(Plot.make1D("Ex2_jetPt",
op.map(tree.Jet, lambda j : j.pt), noSel,
EqBin(100, 15., 60.), title="Jet p_{T} (GeV/c)"))
if 3 in examples:
## Example 3: Plot pT of jets with |η| < 1.
centralJets1 = op.select(tree.Jet, lambda j : op.abs(j.eta) < 1.)
plots.append(Plot.make1D("Ex3_central1_jetPt",
op.map(centralJets1, lambda j : j.pt), noSel,
EqBin(100, 15., 60.), title="Jet p_{T} (GeV/c)"))
if 4 in examples:
## Example 4: Plot the missing ET of events that have at least two jets with pT > 40 GeV.
jets40 = op.select(tree.Jet, lambda j : j.pt > 40)
hasTwoJets40 = noSel.refine("twoJets40", cut=(op.rng_len(jets40) >= 2))
plots.append(Plot.make1D("Ex4_twoJets40_MET",
tree.MET.pt, hasTwoJets40,
EqBin(100, 0., 2000.), title="MET (GeV)"))
if 5 in examples:
## Example 5: Plot the missing ET of events that have an opposite-sign muon pair with an invariant mass between 60 and 120 GeV.
dimu_Z = op.combine(tree.Muon, N=2, pred=(lambda mu1, mu2 : op.AND(
mu1.charge != mu2.charge,
op.in_range(60., op.invariant_mass(mu1.p4, mu2.p4), 120.)
)))
hasDiMuZ = noSel.refine("hasDiMuZ", cut=(op.rng_len(dimu_Z) > 0))
plots.append(Plot.make1D("Ex5_dimuZ_MET",
tree.MET.pt, hasDiMuZ,
EqBin(100, 0., 2000.), title="MET (GeV)"))
if 6 in examples:
## Example 6: Plot pT of the trijet system with the mass closest to 172.5 GeV in each event and plot the maximum b-tagging discriminant value among the jets in the triplet.
trijets = op.combine(tree.Jet, N=3)
hadTop = op.rng_min_element_by(trijets,
fun=lambda comb: op.abs((comb[0].p4+comb[1].p4+comb[2].p4).M()-172.5))
hadTop_p4 = (hadTop[0].p4 + hadTop[1].p4 + hadTop[2].p4)
hasTriJet = noSel.refine("hasTriJet", cut=(op.rng_len(trijets) > 0))
plots.append(Plot.make1D("Ex6_trijet_topPt",
hadTop_p4.Pt(), hasTriJet,
EqBin(100, 15., 40.), title="Trijet p_{T} (GeV/c)"))
plots.append(Plot.make1D("Ex6_trijet_maxbtag",
op.max(op.max(hadTop[0].btag, hadTop[1].btag), hadTop[2].btag), hasTriJet,
EqBin(100, 0., 1.), title="Trijet maximum b-tag"))
if verbose:
plots.append(Plot.make1D("Ex6_njets",
op.rng_len(tree.Jet), noSel,
EqBin(20, 0., 20.), title="Number of jets"))
plots.append(Plot.make1D("Ex6_ntrijets",
op.rng_len(trijets), noSel,
EqBin(100, 0., 1000.), title="Number of 3-jet combinations"))
plots.append(Plot.make1D("Ex6_trijet_mass",
hadTop_p4.M(), hasTriJet,
EqBin(100, 0., 250.), title="Trijet mass (GeV/c^{2})"))
if 7 in examples:
## Example 7: Plot the sum of pT of jets with pT > 30 GeV that are not within 0.4 in ΔR of any lepton with pT > 10 GeV.
el10 = op.select(tree.Electron, lambda el : el.pt > 10.)
mu10 = op.select(tree.Muon , lambda mu : mu.pt > 10.)
cleanedJets30 = op.select(tree.Jet, lambda j : op.AND(
j.pt > 30.,
op.NOT(op.rng_any(el10, lambda el : op.deltaR(j.p4, el.p4) < 0.4 )),
op.NOT(op.rng_any(mu10, lambda mu : op.deltaR(j.p4, mu.p4) < 0.4 ))
))
plots.append(Plot.make1D("Ex7_sumCleanedJetPt",
op.rng_sum(cleanedJets30, lambda j : j.pt), noSel,
EqBin(100, 15., 200.), title="Sum p_{T} (GeV/c)"))
if 8 in examples:
## Example 8: For events with at least three leptons and a same-flavor opposite-sign lepton pair, find the same-flavor opposite-sign lepton pair with the mass closest to 91.2 GeV and plot the transverse mass of the missing energy and the leading other lepton.
# The plot is made for each of the different flavour categories (l+/- l-/+ l') and then summed,
# because concatenation of containers is not (yet) supported.
lepColl = { "El" : tree.Electron, "Mu" : tree.Muon }
mt3lPlots = []
for dlNm,dlCol in lepColl.items():
dilep = op.combine(dlCol, N=2, pred=(lambda l1,l2 : op.AND(l1.charge != l2.charge)))
hasDiLep = noSel.refine("hasDilep{0}{0}".format(dlNm), cut=(op.rng_len(dilep) > 0))
dilepZ = op.rng_min_element_by(dilep, fun=lambda ll : op.abs(op.invariant_mass(ll[0].p4, ll[1].p4)-91.2))
for tlNm,tlCol in lepColl.items():
if tlCol == dlCol:
hasTriLep = hasDiLep.refine("hasTrilep{0}{0}{1}".format(dlNm,tlNm),
cut=(op.rng_len(tlCol) > 2))
residLep = op.select(tlCol, lambda l : op.AND(l.idx != dilepZ[0].idx, l.idx != dilepZ[1].idx))
l3 = op.rng_max_element_by(residLep, lambda l : l.pt)
else:
hasTriLep = hasDiLep.refine("hasTriLep{0}{0}{1}".format(dlNm,tlNm),
cut=(op.rng_len(tlCol) > 0))
l3 = op.rng_max_element_by(tlCol, lambda l : l.pt)
mtPlot = Plot.make1D("Ex8_3lMT_{0}{0}{1}".format(dlNm,tlNm),
op.sqrt(2*l3.pt*tree.MET.pt*(1-op.cos(l3.phi-tree.MET.phi))), hasTriLep,
EqBin(100, 15., 250.), title="M_{T} (GeV/c^2)")
mt3lPlots.append(mtPlot)
plots.append(mtPlot)
plots.append(SummedPlot("Ex8_3lMT", mt3lPlots))
return plots
