def ggTauTau_inclusive_preselection(events, photons, electrons, muons, taus, options, debug):
cut_diagnostics = utils.CutDiagnostics(events = events, debug = debug, cut_set = "[analysis_selections.py : ggTauTau_inclusive_preselection]")
# Get number of electrons, muons, taus
selected_electrons = electrons[lepton_selections.select_electrons(events, photons, electrons, options, debug)]
selected_muons = muons[lepton_selections.select_muons(events, photons, muons, options, debug)]
selected_taus = taus[tau_selections.select_taus(events, photons, selected_muons, selected_electrons, taus, options, debug)]
n_electrons = awkward.num(selected_electrons)
n_muons = awkward.num(selected_muons)
n_taus = awkward.num(selected_taus)
# Require >= 1 lep/tau
n_leptons_and_taus = n_electrons + n_muons + n_taus
lep_tau_cut = n_leptons_and_taus >= options["n_leptons_and_taus"]
# Require OS leptons/taus for events with 2 leptons/taus
sum_charge = awkward.sum(selected_electrons.charge, axis=1) + awkward.sum(selected_muons.charge, axis=1) + awkward.sum(selected_taus.charge, axis=1)
charge_cut = sum_charge == 0
two_leptons = n_leptons_and_taus == 2
not_two_leptons = n_leptons_and_taus != 2
os_cut = (two_leptons & charge_cut) | not_two_leptons # only require 2 OS leptons if there are ==2 leptons in the event
all_cuts = lep_tau_cut & os_cut
cut_diagnostics.add_cuts([lep_tau_cut, os_cut, all_cuts], ["N_leptons + N_taus >= 1", "OS dileptons", "all"])
return events[all_cuts], photons[all_cuts], selected_electrons[all_cuts], selected_muons[all_cuts], selected_taus[all_cuts]
def diphoton_preselection_full(events, photons, options, debug):
cut_diagnostics = utils.CutDiagnostics(
events=events,
debug=debug,
cut_set="[photon_selections.py : diphoton_preselection]")
selected_photons = photons[photon_selections.select_photons(
events, photons, options, debug)]
def tth_hadronic_preselection(events, photons, electrons, muons, jets, options,
debug):
cut_diagnostics = utils.CutDiagnostics(
events=events,
debug=debug,
cut_set="[analysis_selections.py : tth_hadronic_preselection]")
# Get number of electrons, muons
selected_electrons = electrons[lepton_selections.select_electrons(
events, photons, electrons, options, debug)]
selected_muons = muons[lepton_selections.select_muons(
events, photons, muons, options, debug)]
n_electrons = awkward.num(selected_electrons)
n_muons = awkward.num(selected_muons)
n_leptons = n_electrons + n_muons
# Get number of jets
selected_jets = jets[jet_selections.select_jets(events, photons,
selected_electrons,
selected_muons, None, jets,
options, debug)]
n_jets = awkward.num(selected_jets)
# Get number of b-jets
selected_bjets = selected_jets[jet_selections.select_bjets(
selected_jets, options, debug)]
n_bjets = awkward.num(selected_bjets)
lep_cut = n_leptons == 0
jet_cut = n_jets >= 3
bjet_cut = n_bjets >= 1
all_cuts = lep_cut & jet_cut & bjet_cut
cut_diagnostics.add_cuts(
[lep_cut, jet_cut, bjet_cut, all_cuts],
["N_leptons == 0", "N_jets >= 3", "N_bjets >= 1", "all"])
# Keep only selected events
selected_events = events[all_cuts]
selected_photons = photons[all_cuts]
selected_electrons = selected_electrons[all_cuts]
selected_muons = selected_muons[all_cuts]
selected_jets = selected_jets[all_cuts]
# Calculate event-level variables
selected_events = lepton_selections.set_electrons(selected_events,
selected_electrons,
debug)
selected_events = lepton_selections.set_muons(selected_events,
selected_muons, debug)
selected_events = jet_selections.set_jets(selected_events, selected_jets,
options, debug)
return selected_events
def tth_leptonic_preselection(events, photons, electrons, muons, jets, options,
debug):
"""
Performs tth leptonic preselection, requiring >= 1 lepton and >= 1 jet
Assumes diphoton preselection has already been applied.
Also calculates relevant event-level variables.
"""
cut_diagnostics = utils.CutDiagnostics(
events=events,
debug=debug,
cut_set="[analysis_selections.py : tth_leptonic_preselection]")
# Get number of electrons, muons
selected_electrons = electrons[lepton_selections.select_electrons(
events, photons, electrons, options, debug)]
selected_muons = muons[lepton_selections.select_muons(
events, photons, muons, options, debug)]
n_electrons = awkward.num(selected_electrons)
n_muons = awkward.num(selected_muons)
n_leptons = n_electrons + n_muons
# Get number of jets
selected_jets = jets[jet_selections.select_jets(events, photons,
selected_electrons,
selected_muons, None, jets,
options, debug)]
n_jets = awkward.num(selected_jets)
lep_cut = n_leptons >= 1
jet_cut = n_jets >= 1
all_cuts = lep_cut & jet_cut
cut_diagnostics.add_cuts([lep_cut, jet_cut, all_cuts],
["N_leptons >= 1", "N_jets >= 1", "all"])
# Keep only selected events
selected_events = events[all_cuts]
selected_photons = photons[all_cuts]
selected_electrons = selected_electrons[all_cuts]
selected_muons = selected_muons[all_cuts]
selected_jets = selected_jets[all_cuts]
# Calculate event-level variables
selected_events = lepton_selections.set_electrons(selected_events,
selected_electrons,
debug)
selected_events = lepton_selections.set_muons(selected_events,
selected_muons, debug)
selected_events = jet_selections.set_jets(selected_events, selected_jets,
options, debug)
return selected_events
def diphoton_preselection(events, photons, options, debug):
# Initialize cut diagnostics tool for debugging
cut_diagnostics = utils.CutDiagnostics(
events=events,
debug=debug,
cut_set="[photon_selections.py : diphoton_preselection]")
selected_photons = photons[photon_selections.select_photons(
events, photons, options, debug)]
### mgg cut ###
resonant = options["resonant"]
if resonant:
mgg_mask = numpy.array(
events.ggMass > options["diphotons"]["mgg_lower"]) & numpy.array(
events.ggMass < options["diphotons"]["mgg_upper"])
else:
sideband_low = numpy.array(
events.ggMass > options["diphotons"]["mgg_lower"]) & numpy.array(
events.ggMass < options["diphotons"]["mgg_sideband_lower"])
sideband_high = numpy.array(
events.ggMass > options["diphotons"]["mgg_sideband_upper"]
) & numpy.array(events.ggMass < options["diphotons"]["mgg_upper"])
mgg_mask = sideband_low | sideband_high
### pt/mgg cuts ###
lead_pt_mgg_requirement = (selected_photons.pt / events.ggMass
) > options["photons"]["lead_pt_mgg_cut"]
sublead_pt_mgg_requirement = (selected_photons.pt / events.ggMass
) > options["photons"]["sublead_pt_mgg_cut"]
lead_pt_mgg_cut = awkward.num(
selected_photons[lead_pt_mgg_requirement]
) >= 1 # at least 1 photon passing lead requirement
sublead_pt_mgg_cut = awkward.num(
selected_photons[sublead_pt_mgg_requirement]
) >= 2 # at least 2 photon passing sublead requirement
pt_mgg_cut = lead_pt_mgg_cut & sublead_pt_mgg_cut
### 2 good selected_photons ###
n_photon_cut = awkward.num(
selected_photons
) == 2 # can regain a few % of signal if we set to >= 2 (probably e's that are reconstructed as selected_photons)
all_cuts = mgg_mask & pt_mgg_cut & n_photon_cut
cut_diagnostics.add_cuts([mgg_mask, pt_mgg_cut, n_photon_cut, all_cuts], [
"mgg in [100, 180]" if resonant else "mgg in [100, 120] or [130, 180]",
"lead (sublead) pt/mgg > 0.33 (0.25)", "2 good photons", "all"
])
return events[all_cuts], selected_photons[all_cuts]
def diphoton_preselection(events, debug):
cut_diagnostics = utils.CutDiagnostics(
n_events_initial=len(events),
debug=debug,
cut_set="[photon_selections.py : diphoton_preselection]")
# mgg cut
mgg_mask = numpy.array(events.ggMass > 100) & numpy.array(
events.ggMass < 180)
events = events[mgg_mask]
cut_diagnostics.add_cut(len(events), cut_name="mgg cut")
# pt/mgg cuts
pt_mgg_cut1 = (events.Photon_pt / events.ggMass) > 0.33
pt_mgg_cut2 = (events.Photon_pt / events.ggMass) > 0.25
n_pho1 = awkward.num(events.Photon_pt[pt_mgg_cut1])
n_pho2 = awkward.num(events.Photon_pt[pt_mgg_cut2])
pt_mgg_mask = numpy.array(n_pho1 >= 1) & numpy.array(n_pho2 >= 2)
events = events[pt_mgg_mask]
cut_diagnostics.add_cut(len(events), cut_name="pt/mgg cut")
# pho id mva cuts
pho_idmva_cut = events.Photon_mvaID > -0.7
n_pho = awkward.num(events.Photon_pt[pho_idmva_cut])
pho_idmva_mask = numpy.array(n_pho >= 2)
events = events[pho_idmva_mask]
cut_diagnostics.add_cut(len(events), cut_name="photon id mva cut")
# electron veto cuts
eveto_cut = events.Photon_electronVeto == 1
n_pho = awkward.num(events.Photon_pt[eveto_cut])
eveto_mask = numpy.array(n_pho >= 2)
events = events[eveto_mask]
cut_diagnostics.add_cut(len(events), cut_name="electron veto cut")
return events
def tth_leptonic_preselection(events, photons, electrons, muons, jets, options, debug):
cut_diagnostics = utils.CutDiagnostics(events = events, debug = debug, cut_set = "[analysis_selections.py : tth_leptonic_preselection]")
# Get number of electrons, muons
selected_electrons = electrons[lepton_selections.select_electrons(events, photons, electrons, options, debug)]
selected_muons = muons[lepton_selections.select_muons(events, photons, muons, options, debug)]
n_electrons = awkward.num(selected_electrons)
n_muons = awkward.num(selected_muons)
n_leptons = n_electrons + n_muons
# Get number of jets
selected_jets = jets[jet_selections.select_jets(events, photons, selected_electrons, selected_muons, None, jets, options, debug)]
n_jets = awkward.num(selected_jets)
lep_cut = n_leptons >= 1
jet_cut = n_jets >= 1
all_cuts = lep_cut & jet_cut
cut_diagnostics.add_cuts([lep_cut, jet_cut, all_cuts], ["N_leptons >= 1", "N_jets >= 1", "all"])
return events[all_cuts], photons[all_cuts], selected_electrons[all_cuts], selected_muons[all_cuts], selected_jets[all_cuts]
def diphoton_preselection(events, selected_photons, options, debug):
# Initialize cut diagnostics tool for debugging
cut_diagnostics = utils.CutDiagnostics(
events=events,
debug=debug,
cut_set="[photon_selections.py : diphoton_preselection]")
### mgg cut ###
resonant = options["resonant"]
if resonant:
mgg_mask = numpy.array(
events.gg_mass > options["diphotons"]["mgg_lower"]) & numpy.array(
events.gg_mass < options["diphotons"]["mgg_upper"])
else:
sideband_low = numpy.array(
events.gg_mass > options["diphotons"]["mgg_lower"]) & numpy.array(
events.gg_mass < options["diphotons"]["mgg_sideband_lower"])
sideband_high = numpy.array(
events.gg_mass > options["diphotons"]["mgg_sideband_upper"]
) & numpy.array(events.gg_mass < options["diphotons"]["mgg_upper"])
mgg_mask = sideband_low | sideband_high
lead_pt_mgg_cut = selected_photons.pt[:, 0] / events.gg_mass > options[
"photons"]["lead_pt_mgg_cut"]
sublead_pt_mgg_cut = selected_photons.pt[:, 1] / events.gg_mass > options[
"photons"]["sublead_pt_mgg_cut"]
pt_mgg_cut = lead_pt_mgg_cut & sublead_pt_mgg_cut
lead_idmva_cut = selected_photons.mvaID[:, 0] > options["photons"][
"idmva_cut"]
sublead_idmva_cut = selected_photons.mvaID[:, 1] > options["photons"][
"idmva_cut"]
idmva_cut = lead_idmva_cut & sublead_idmva_cut
lead_eveto_cut = selected_photons.electronVeto[:, 0] > options["photons"][
"eveto_cut"]
sublead_eveto_cut = selected_photons.electronVeto[:, 1] > options[
"photons"]["eveto_cut"]
eveto_cut = lead_eveto_cut & sublead_eveto_cut
lead_eta_cut1 = abs(selected_photons.eta[:, 0]) < options["photons"]["eta"]
lead_eta_cut2 = abs(selected_photons.eta[:, 0]
) < options["photons"]["transition_region_eta"][0]
lead_eta_cut3 = abs(selected_photons.eta[:, 0]
) > options["photons"]["transition_region_eta"][1]
lead_eta_cut = lead_eta_cut1 & (lead_eta_cut2 | lead_eta_cut3)
sublead_eta_cut1 = abs(selected_photons.eta[:,
1]) < options["photons"]["eta"]
sublead_eta_cut2 = abs(selected_photons.eta[:, 1]
) < options["photons"]["transition_region_eta"][0]
sublead_eta_cut3 = abs(selected_photons.eta[:, 1]
) > options["photons"]["transition_region_eta"][1]
sublead_eta_cut = sublead_eta_cut1 & (sublead_eta_cut2 | sublead_eta_cut3)
eta_cut = lead_eta_cut & sublead_eta_cut
if options["data"]:
if options["year"] == 2016:
trigger_cut = events.HLT_Diphoton30_18_R9Id_OR_IsoCaloId_AND_HE_R9Id_Mass90 == True
elif options["year"] == 2017 or options["year"] == 2018:
trigger_cut = events.HLT_Diphoton30_22_R9Id_OR_IsoCaloId_AND_HE_R9Id_Mass90 == True
else:
trigger_cut = events.gg_mass > 0
all_cuts = mgg_mask & pt_mgg_cut & idmva_cut & eveto_cut & eta_cut & trigger_cut
cut_diagnostics.add_cuts([
mgg_mask, pt_mgg_cut, idmva_cut, eveto_cut, eta_cut, trigger_cut,
all_cuts
], [
"mgg in [100, 180]" if resonant else "mgg in [100, 120] or [130, 180]",
"lead (sublead) pt/mgg > 0.33 (0.25)", "pho idmva > -0.7", "eveto cut",
"eta cut", "trigger", "all"
])
selected_events = events[all_cuts]
selected_photons = selected_photons[all_cuts]
# Calculate event-level photon/diphoton variables
selected_events = photon_selections.set_photons(selected_events,
selected_photons, debug)
selected_events = set_diphotons(selected_events, selected_photons, debug)
return selected_events, selected_photons
def ggbb_preselection(events, photons, electrons, muons, jets, fatjets,
options, debug):
cut_diagnostics = utils.CutDiagnostics(
events=events,
debug=debug,
cut_set="[analysis_selections.py : ggbb_preselection]")
# Get number of electrons, muons
selected_electrons = electrons[lepton_selections.select_electrons(
events, photons, electrons, options, debug)]
selected_muons = muons[lepton_selections.select_muons(
events, photons, muons, options, debug)]
n_electrons = awkward.num(selected_electrons)
n_muons = awkward.num(selected_muons)
n_leptons = n_electrons + n_muons
# Get number of jets
selected_jets = jets[jet_selections.select_jets(events, photons,
selected_electrons,
selected_muons, None, jets,
options, debug)]
n_jets = awkward.num(selected_jets)
# Get number of b-jets
selected_bjets = selected_jets[jet_selections.select_bjets(
selected_jets, options, debug)]
n_bjets = awkward.num(selected_bjets)
# Get fat jets
selected_fatjets = fatjets[jet_selections.select_fatjets(
events, photons, fatjets, options, debug)]
n_fatjets = awkward.num(selected_fatjets)
lep_cut = n_leptons == 0
if options["boosted"]:
jet_cut = n_bjets < 2
fatjet_cut = n_fatjets == 1
all_cuts = lep_cut & jet_cut & fatjet_cut
cut_diagnostics.add_cuts(
[lep_cut, jet_cut, fatjet_cut, all_cuts],
["N_leptons == 0", "N_b-jets < 2", "N_fatjets == 1", "all"])
else:
jet_cut = n_bjets == 2
all_cuts = lep_cut & jet_cut
cut_diagnostics.add_cuts([lep_cut, jet_cut, all_cuts],
["N_leptons == 0", "N_b-jets == 2", "all"])
# Keep only selected events
selected_events = events[all_cuts]
selected_photons = photons[all_cuts]
selected_jets = selected_jets[all_cuts]
selected_fatjets = selected_fatjets[all_cuts]
# Calculate event-level variables
selected_events = jet_selections.set_jets(selected_events, selected_jets,
options, debug)
selected_events = jet_selections.set_fatjets(selected_events,
selected_fatjets, options,
debug)
return selected_events
def ggTauTau_inclusive_preselection(events, photons, electrons, muons, taus,
jets, dR, genPart, Category_pairsLoose,
options, debug):
"""
Performs inclusive ggTauTau preselection, requiring >=1 (leptons + tau_h).
Assumes diphoton preselection has already been applied.
Also calculates relevant event-level variables.
"""
cut_diagnostics = utils.CutDiagnostics(
events=events,
debug=debug,
cut_set="[analysis_selections.py : ggTauTau_inclusive_preselection]")
# Get number of electrons, muons, taus
selected_electrons = electrons[lepton_selections.select_electrons(
events, photons, electrons, options, debug)]
selected_muons = muons[lepton_selections.select_muons(
events, photons, muons, options, debug)]
selected_taus = taus[tau_selections.select_taus(events, photons,
selected_muons,
selected_electrons, taus,
options, debug)]
n_electrons = awkward.num(selected_electrons)
n_muons = awkward.num(selected_muons)
n_taus = awkward.num(selected_taus)
# Require >= 1 lep/tau
n_leptons_and_taus = n_electrons + n_muons + n_taus
# only events with hadronic taus (no leptonic taus!!!!!!!!!!)
atleast_one_had_tau_cut = (n_taus >= 1)
# Require OS leptons/taus for events with 2 leptons/taus
sum_charge = awkward.sum(selected_electrons.charge, axis=1) + awkward.sum(
selected_muons.charge, axis=1) + awkward.sum(selected_taus.charge,
axis=1)
charge_cut = sum_charge == 0
two_leptons = n_leptons_and_taus == 2
not_two_leptons = n_leptons_and_taus != 2
os_cut = (
two_leptons & charge_cut
) | not_two_leptons # only require 2 OS leptons if there are ==2 leptons in the event
# Select jets (don't cut on jet quantities for selection, but they will be useful for BDT training)
selected_jets = jets[jet_selections.select_jets(events, photons,
selected_electrons,
selected_muons,
selected_taus, jets,
options, debug)]
all_cuts = os_cut & atleast_one_had_tau_cut
cut_diagnostics.add_cuts([atleast_one_had_tau_cut, os_cut, all_cuts],
["N_taus >= 1", "OS dileptons", "all"])
# Keep only selected events
selected_events = events[all_cuts]
selected_photons = photons[all_cuts]
selected_electrons = selected_electrons[all_cuts]
selected_muons = selected_muons[all_cuts]
selected_taus = selected_taus[all_cuts]
selected_jets = selected_jets[all_cuts]
dR = dR[all_cuts]
# Calculate event-level variables
selected_events = lepton_selections.set_electrons(selected_events,
selected_electrons,
debug)
selected_events = lepton_selections.set_muons(selected_events,
selected_muons, debug)
selected_events = tau_selections.set_taus(selected_events, selected_taus,
debug)
selected_events = jet_selections.set_jets(selected_events, selected_jets,
options, debug)
if genPart is not None:
genPart = genPart[all_cuts]
selected_events = gen_selections.set_genZ(selected_events, genPart,
options, debug)
else:
selected_events["genZ_decayMode"] = awkward.from_numpy(
numpy.ones(len(selected_events)) * -1)
selected_events["tau_motherID"] = awkward.from_numpy(
numpy.ones(len(selected_events)) * -1)
selected_events = compound_selections.compound_selections(
selected_events, options, debug)
return selected_events
def ggTauTau_inclusive_preselection(events, photons, electrons, muons, taus,
jets, options, debug):
"""
Performs inclusive ggTauTau preselection, requiring >=1 (leptons + tau_h).
Assumes diphoton preselection has already been applied.
Also calculates relevant event-level variables.
"""
cut_diagnostics = utils.CutDiagnostics(
events=events,
debug=debug,
cut_set="[analysis_selections.py : ggTauTau_inclusive_preselection]")
# Get number of electrons, muons, taus
selected_electrons = electrons[lepton_selections.select_electrons(
events, photons, electrons, options, debug)]
selected_muons = muons[lepton_selections.select_muons(
events, photons, muons, options, debug)]
selected_taus = taus[tau_selections.select_taus(events, photons,
selected_muons,
selected_electrons, taus,
options, debug)]
n_electrons = awkward.num(selected_electrons)
n_muons = awkward.num(selected_muons)
n_taus = awkward.num(selected_taus)
# Require >= 1 lep/tau
n_leptons_and_taus = n_electrons + n_muons + n_taus
lep_tau_cut = n_leptons_and_taus >= options["n_leptons_and_taus"]
# Require OS leptons/taus for events with 2 leptons/taus
sum_charge = awkward.sum(selected_electrons.charge, axis=1) + awkward.sum(
selected_muons.charge, axis=1) + awkward.sum(selected_taus.charge,
axis=1)
charge_cut = sum_charge == 0
two_leptons = n_leptons_and_taus == 2
not_two_leptons = n_leptons_and_taus != 2
os_cut = (
two_leptons & charge_cut
) | not_two_leptons # only require 2 OS leptons if there are ==2 leptons in the event
# Select jets (don't cut on jet quantities for selection, but they will be useful for BDT training)
selected_jets = jets[jet_selections.select_jets(events, photons,
selected_electrons,
selected_muons,
selected_taus, jets,
options, debug)]
all_cuts = lep_tau_cut & os_cut
cut_diagnostics.add_cuts(
[lep_tau_cut, os_cut, all_cuts],
["N_leptons + N_taus >= 1", "OS dileptons", "all"])
# Keep only selected events
selected_events = events[all_cuts]
selected_photons = photons[all_cuts]
selected_electrons = selected_electrons[all_cuts]
selected_muons = selected_muons[all_cuts]
selected_taus = selected_taus[all_cuts]
selected_jets = selected_jets[all_cuts]
# Calculate event-level variables
selected_events = lepton_selections.set_electrons(selected_events,
selected_electrons,
debug)
selected_events = lepton_selections.set_muons(selected_events,
selected_muons, debug)
selected_events = tau_selections.set_taus(selected_events, selected_taus,
debug)
selected_events = jet_selections.set_jets(selected_events, selected_jets,
options, debug)
# TODO: add calculation HH->ggTauTau specific variables (e.g. H->TauTau kinematics) here
return selected_events
def ggbb_preselection(events, photons, electrons, muons, jets, fatjets,
genparts, options, debug):
cut_diagnostics = utils.CutDiagnostics(
events=events,
debug=debug,
cut_set="[analysis_selections.py : ggbb_preselection]")
# Get number of electrons, muons
selected_electrons = electrons[lepton_selections.select_electrons(
events, photons, electrons, options, debug)]
selected_muons = muons[lepton_selections.select_muons(
events, photons, muons, options, debug)]
n_electrons = awkward.num(selected_electrons)
n_muons = awkward.num(selected_muons)
n_leptons = n_electrons + n_muons
# Get number of jets
selected_jets = jets[jet_selections.select_jets(events, photons,
selected_electrons,
selected_muons, None, jets,
options, debug)]
n_jets = awkward.num(selected_jets)
# Get number of b-jets
selected_bjets = selected_jets[jet_selections.select_bjets(
selected_jets, options, debug)]
n_bjets = awkward.num(selected_bjets)
# Get fat jets
selected_fatjets = fatjets[jet_selections.select_fatjets(
events, photons, fatjets, options, debug)]
n_fatjets = awkward.num(selected_fatjets)
lep_cut = n_leptons == 0
if options["boosted"]:
# jet_cut = n_bjets < 2 # This is not wanted
fatjet_cut = n_fatjets >= 1
all_cuts = lep_cut & fatjet_cut
cut_diagnostics.add_cuts([lep_cut, fatjet_cut, all_cuts],
["N_leptons == 0", "N_fatjets >= 1", "all"])
else:
jet_cut = n_bjets == 2
all_cuts = lep_cut & jet_cut
cut_diagnostics.add_cuts([lep_cut, jet_cut, all_cuts],
["N_leptons == 0", "N_b-jets == 2", "all"])
# Keep only selected events
selected_events = events[all_cuts]
selected_photons = photons[all_cuts]
selected_jets = selected_jets[all_cuts]
selected_bjets = selected_bjets[all_cuts]
selected_fatjets = selected_fatjets[all_cuts]
# # Lead FatJet pt cut
fatjet_pt_cut = selected_fatjets.pt[:, 0] >= 350
# # Keep only selected events II
# selected_events = selected_events[fatjet_pt_cut]
# selected_photons = selected_photons[fatjet_pt_cut]
# selected_jets = selected_jets[fatjet_pt_cut]
# selected_bjets = selected_bjets[fatjet_pt_cut]
# selected_fatjets = selected_fatjets[fatjet_pt_cut]
# cut_diagnostics.add_cuts([fatjet_pt_cut], ["Lead FatJet pt > 350 GeV"])
# Filter mjj #TODO Fix the "nearest" function
# mjj_cut = mjj_selections.mjj_filter(events,selected_fatjets,selected_jets,[120,130],debug)
# selected_events = events[mjj_cut]
# selected_photons = photons[mjj_cut]
# selected_jets = selected_jets[mjj_cut]
# selected_bjets = selected_fatjets[mjj_cut]
# selected_fatjets = selected_fatjets[mjj_cut]
# Calculate event-level variables
if genparts is not None:
selected_genparts = genparts[all_cuts]
# selected_genparts = selected_genparts[mjj_cut]
# selected_genparts = selected_genparts[fatjet_pt_cut]
# selected_events = selected_events[gen_selections.filter_genHbb(selected_events,selected_genparts,options,debug)]
selected_events = gen_selections.set_genInfo(selected_events,
selected_genparts,
options, debug)
selected_events = jet_selections.set_fatjets(selected_events,
selected_fatjets,
selected_genparts,
options, debug)
else:
selected_events = jet_selections.set_fatjets(
selected_events, selected_fatjets, genparts, options,
debug) #FIXME genparts is None here
selected_events = jet_selections.set_jets(selected_events, selected_jets,
options, debug)
selected_events = helicity_selections.set_helicity(selected_events,
selected_photons,
selected_fatjets,
selected_bjets, options,
debug)
return selected_events
