def get_pileup_reweighting_tool(year, use_defaults=True, systematic=None):
# https://twiki.cern.ch/twiki/bin/viewauth/AtlasProtected/ExtendedPileupReweighting
# Initialize the pileup reweighting tool
pileup_tool = Root.TPileupReweighting()
if year == 2011:
if use_defaults:
pileup_tool.AddConfigFile(
PileupReweighting.get_resource(
'mc11b_defaults.prw.root'))
else:
pileup_tool.AddConfigFile(
'lumi/2011/'
'TPileupReweighting.mc11.prw.root')
lumicalc_file = 'lumi/2011/ilumicDDalc_histograms_None_178044-191933.root'
elif year == 2012:
if use_defaults:
pileup_tool.AddConfigFile(
PileupReweighting.get_resource(
'mc12ab_defaults.prw.root'))
else:
pileup_tool.AddConfigFile(
'lumi/2012/'
'TPileupReweighting.mc12.prw.root')
lumicalc_file = 'lumi/2012/ilumicalc_histograms_None_200842-215643.root'
else:
raise ValueError(
'No pileup reweighting defined for year %d' % year)
rescale, rescale_error = PU_RESCALE[year]
if systematic is None:
pileup_tool.SetDataScaleFactors(1. / rescale)
elif systematic == 'high':
pileup_tool.SetDataScaleFactors(1. / (rescale + rescale_error))
elif systematic == 'low':
pileup_tool.SetDataScaleFactors(1. / (rescale - rescale_error))
else:
raise ValueError(
"pileup systematic '{0}' not understood".format(systematic))
pileup_tool.AddLumiCalcFile(lumicalc_file)
# discard unrepresented data (with mu not simulated in MC)
pileup_tool.SetUnrepresentedDataAction(2)
pileup_tool.Initialize()
# set the random seed used by the GetRandomRunNumber and
# GetRandomPeriodNumber methods
pileup_tool.SetRandomSeed(1777)
# register
PILEUP_TOOLS.append(pileup_tool)
return pileup_tool
def work(self):
# trigger config tool to read trigger info in the ntuples
trigger_config = get_trigger_config()
OutputModel = (RecoTauBlock + EventVariables + SkimExtraModel +
TrueTauBlock)
onfilechange = []
# update the trigger config maps on every file change
onfilechange.append((update_trigger_config, (trigger_config,)))
cutflow = Hist(2, 0, 2, name='cutflow', type='D')
# initialize the TreeChain of all input files (each containing one tree named self.metadata.treename)
chain = TreeChain(self.metadata.treename,
files=self.files,
events=self.events,
cache=True,
cache_size=10000000,
learn_entries=30,
onfilechange=onfilechange)
# create output tree
self.output.cd()
tree = Tree(name='higgstautauhh', model=OutputModel)
copied_variables = ['actualIntPerXing',
'averageIntPerXing',
'RunNumber',
'EventNumber',
'lbn']
tree.set_buffer(
chain.buffer,
branches=copied_variables,
create_branches=True,
visible=False)
chain.always_read(copied_variables)
# set the event filters
event_filters = EventFilterList([
#Triggers(
# datatype=self.metadata.datatype,
# year=YEAR,
# skim=False),
PriVertex(),
LArError(),
LArHole(datatype=self.metadata.datatype),
JetCleaning(
datatype=self.metadata.datatype,
year=YEAR),
TauAuthor(1),
TauHasTrack(1),
TauPT(1, thresh=25 * GeV),
TauEta(1),
TauCrack(1),
TauLArHole(1),
#TauTriggerMatch(
# config=trigger_config,
# year=YEAR,
# datatype=self.metadata.datatype,
# skim=False,
# tree=tree,
# min_taus=1),
])
self.filters['event'] = event_filters
chain.filters += event_filters
# define tree collections
chain.define_collection(name="taus", prefix="tau_", size="tau_n", mix=TauFourMomentum)
chain.define_collection(name="taus_EF", prefix="trig_EF_tau_",
size="trig_EF_tau_n", mix=TauFourMomentum)
# jet_* etc. is AntiKt4LCTopo_* in tau-perf D3PDs
chain.define_collection(name="jets", prefix="jet_", size="jet_n", mix=FourMomentum)
chain.define_collection(name="truetaus", prefix="trueTau_", size="trueTau_n", mix=MCTauFourMomentum)
chain.define_collection(name="mc", prefix="mc_", size="mc_n", mix=MCParticle)
chain.define_collection(name="muons", prefix="mu_staco_", size="mu_staco_n")
chain.define_collection(name="electrons", prefix="el_", size="el_n")
chain.define_collection(name="vertices", prefix="vxp_", size="vxp_n")
from externaltools import PileupReweighting
from ROOT import Root
# Initialize the pileup reweighting tool
pileup_tool = Root.TPileupReweighting()
if YEAR == 2011:
pileup_tool.AddConfigFile(PileupReweighting.get_resource('mc11b_defaults.prw.root'))
pileup_tool.AddLumiCalcFile('lumi/2011/hadhad/ilumicalc_histograms_None_178044-191933.root')
elif YEAR == 2012:
pileup_tool.AddConfigFile(PileupReweighting.get_resource('mc12a_defaults.prw.root'))
pileup_tool.SetDataScaleFactors(1./1.11)
pileup_tool.AddLumiCalcFile('lumi/2012/hadhad/ilumicalc_histograms_None_200841-205113.root')
else:
raise ValueError('No pileup reweighting defined for year %d' %
YEAR)
# discard unrepresented data (with mu not simulated in MC)
pileup_tool.SetUnrepresentedDataAction(2)
pileup_tool.Initialize()
# entering the main event loop...
for event in chain:
tree.reset()
event.vertices.select(vertex_selection)
tree.number_of_good_vertices = len(event.vertices)
# match only with visible true taus
event.truetaus.select(lambda tau: tau.vis_Et > 10 * GeV and abs(tau.vis_eta) < 2.5)
if len(event.truetaus) == 1:
true_tau = event.truetaus[0]
TrueTauBlock.set(tree, 1, true_tau)
else:
continue
# Truth-matching
matched_reco = None
reco_index = true_tau.tauAssoc_index
tau = event.taus.getitem(reco_index)
if tau in event.taus:
matched_reco = tau
else:
continue
tree.MET = event.MET_RefFinal_BDTMedium_et
# fill tau block
RecoTauBlock.set(event, tree, matched_reco, None)
# set the event weight
tree.pileup_weight = pileup_tool.GetCombinedWeight(event.RunNumber,
event.mc_channel_number,
event.averageIntPerXing)
tree.mc_weight = event.mc_event_weight
tree.Fill(reset=True)
self.output.cd()
tree.FlushBaskets()
tree.Write()
total_events = event_filters[0].total
cutflow[0] = total_events
cutflow[1] = total_events
cutflow.Write()
