def __init__(self, sample, sample_manager):
self.sample = sample
self.sample_manager = sample_manager
#lumi weights
self.lumiweighter = LumiWeight(sample, sample_manager)
#pu weights
if not sample.is_data:
self.puReweighting = getReweightingFunction(
sample.chain.year, 'central')
self.puReweightingUp = getReweightingFunction(
sample.chain.year, 'up')
self.puReweightingDown = getReweightingFunction(
sample.chain.year, 'down')
self.fakerate_collection = None
class Reweighter:
def __init__(self, sample, sample_manager):
self.sample = sample
self.sample_manager = sample_manager
#lumi weights
self.lumiweighter = LumiWeight(sample, sample_manager)
#pu weights
if not sample.is_data:
self.puReweighting = getReweightingFunction(
sample.chain.year, 'central')
self.puReweightingUp = getReweightingFunction(
sample.chain.year, 'up')
self.puReweightingDown = getReweightingFunction(
sample.chain.year, 'down')
self.fakerate_collection = None
def getLumiWeight(self):
return self.lumiweighter.getLumiWeight()
def getPUWeight(self):
if not self.sample.is_data:
return self.puReweighting(self.sample.chain._nTrueInt)
else:
return 1.
def getFakeRateWeight(self):
try:
return self.fakerate_collection.getFakeWeight()
except:
self.fakerate_collection = returnFakeRateCollection(
self.sample.chain)
return self.fakerate_collection.getFakeWeight()
def getTotalWeight(self, sideband=False):
tot_weight = 1.
tot_weight *= self.getLumiWeight()
tot_weight *= self.getPUWeight()
if sideband:
tot_weight *= self.getFakeRateWeight()
return tot_weight
#
# Set range of events to process
#
if args.isTest:
max_events = 20000
event_range = xrange(max_events) if max_events < len(
sample.getEventRange(args.subJob)) else sample.getEventRange(
args.subJob)
else:
event_range = sample.getEventRange(args.subJob)
#
# Get luminosity weight
#
from HNL.Weights.lumiweight import LumiWeight
lw = LumiWeight(sample, sample_manager)
from HNL.EventSelection.eventCategorization import EventCategory
try:
ec = EventCategory(chain)
except:
ec = None
#
# Define event selection
#
event = Event(chain,
chain,
is_reco_level=True,
selection=args.selection,
strategy='MVA',
#
if args.isTest:
if len(sample.getEventRange(0)) < 1000:
event_range = sample.getEventRange(0)
else:
event_range = xrange(1000)
elif args.runOnCream:
event_range = sample.getEventRange(args.subJob)
else:
event_range = xrange(chain.GetEntries())
chain.HNLmass = sample.getMass()
chain.year = int(args.year)
from HNL.Weights.lumiweight import LumiWeight
lw = LumiWeight(sample, sample_manager)
print sample.name
#
# Loop over all events
#
from HNL.Tools.helpers import progress, makeDirIfNeeded
from HNL.ObjectSelection.tauSelector import isGoodGenTau
from HNL.EventSelection.eventSelectionTools import select3GenLeptons
ec = EventCategory(chain)
for entry in event_range:
chain.GetEntry(entry)
progress(entry - event_range[0], len(event_range))
if not select3GenLeptons(chain, chain): continue
sample = sample_manager.getSample(args.sample)
chain = sample.initTree()
chain.year = int(args.year)
chain.is_signal = 'HNL' in sample.name
#
# Import and create cutter to provide cut flow
#
from HNL.EventSelection.cutter import Cutter
cutter = Cutter(chain = chain)
#
# Get lumiweight
#
from HNL.Weights.lumiweight import LumiWeight
lw = LumiWeight(sample, sample_manager)
#
# Create new reduced tree (except if it already exists and overwrite option is not used)
#
from HNL.Tools.helpers import isValidRootFile, makeDirIfNeeded
gen_name = 'Reco' if not args.genSkim else 'Gen'
if sample.is_data:
output_file_name = 'Data'
elif chain.is_signal:
output_file_name = sample.path.split('/')[-1].rsplit('.', 1)[0]
else:
output_file_name = sample.path.split('/')[-2]
output_base = os.path.expandvars(os.path.join('/user/$USER/public/ntuples/HNL')) if not args.isTest else os.path.expandvars(os.path.join('$CMSSW_BASE', 'src', 'HNL', 'SkimTuples', 'data', 'testArea'))
for channel in ['Ditau', 'SingleTau']:
list_of_hist[algo][iso_wp][ele_wp][mu_wp][
channel] = ROOT.TH1D(
'_'.join(
[channel, algo, iso_wp, ele_wp, mu_wp]),
'_'.join(
[channel, algo, iso_wp, ele_wp,
mu_wp]), 1, 0, 1)
list_of_hist[algo][iso_wp][ele_wp][mu_wp][
channel].Sumw2()
#
# Get luminosity weight
#
from HNL.Weights.lumiweight import LumiWeight
lw = LumiWeight(sample, sample_manager)
from HNL.EventSelection.eventSelectionTools import bVeto
def passCuts(chain, indices):
if len(indices) != 3: return False
if chain._lCharge[indices[0]] == chain._lCharge[
indices[1]] and chain._lCharge[indices[2]] == chain._lCharge[
indices[1]]:
return False
if bVeto(chain): return False
vectors = []
for lepton_index in indices:
vectors.append(
getFourVec(chain._lPt[lepton_index], chain._lEta[lepton_index],
chain._lPhi[lepton_index], chain._lE[lepton_index]))
if args.isTest:
max_events = 20000
event_range = xrange(max_events) if max_events < len(sample.getEventRange(args.subJob)) else sample.getEventRange(args.subJob)
else:
event_range = sample.getEventRange(args.subJob)
chain.HNLmass = sample.getMass()
chain.year = int(args.year)
chain.selection = args.selection
chain.strategy = args.strategy
#
# Get luminosity weight
#
from HNL.Weights.lumiweight import LumiWeight
lw = LumiWeight(sample, sample_manager)
#
# Import and create cutter to provide cut flow
#
from HNL.EventSelection.cutter import Cutter
cutter = Cutter(chain = chain)
#
# Loop over all events
#
from HNL.Tools.helpers import progress
from HNL.EventSelection.eventSelectionTools import selectGenLeptonsGeneral, passedCustomPtCuts
from HNL.EventSelection.signalLeptonMatcher import SignalLeptonMatcher
from HNL.ObjectSelection.leptonSelector import isGoodLepton
if args.isTest:
max_events = 2000
event_range = xrange(max_events) if max_events < len(
sample.getEventRange(args.subJob)) else sample.getEventRange(
args.subJob)
else:
event_range = sample.getEventRange(args.subJob)
chain.HNLmass = sample.getMass()
chain.year = int(args.year)
#
# Get luminosity weight
#
from HNL.Weights.lumiweight import LumiWeight
lw = LumiWeight(sample, sample_manager, skimmed=not args.noskim)
from HNL.EventSelection.eventCategorization import EventCategory
ec = EventCategory(chain)
#
# Object ID param
#
if args.selection == 'AN2017014':
object_selection_param = {
'no_tau': True,
'light_algo': 'cutbased',
'workingpoint': 'tight'
}
else:
object_selection_param = {
cutter = Cutter(chain = chain)
if args.isTest:
event_range = xrange(1000)
else:
event_range = sample.getEventRange(args.subJob)
chain.HNLmass = sample.getMass()
chain.year = int(args.year)
#
# Get luminosity weight
#
from HNL.Weights.lumiweight import LumiWeight
if args.noskim:
lw = LumiWeight(sample, sample_manager)
from HNL.EventSelection.eventCategorization import EventCategory
ec = EventCategory(chain)
list_of_numbers = {}
for c in listOfCategories():
list_of_numbers[c] = {}
for sr in xrange(1, srm.getNumberOfSearchRegions()+1):
list_of_numbers[c][sr] = Histogram('_'.join([str(c), str(sr)]), lambda c: 0.5, ('', 'Events'), np.arange(0., 2., 1.))
subjobAppendix = 'subJob' + args.subJob if args.subJob else ''
selection_str = 'OldSel' if args.oldAnalysisCuts else 'NewCuts'
mass_str = 'allMass' if args.massRegion is None else args.massRegion