sample = sample_manager.getSample(args.sample)
if not args.inData and 'Data' in sample.name: exit(0)
chain = sample.initTree(needhcount=False)
chain.HNLmass = sample.getMass()
chain.year = int(args.year)
#
# Initialize reweighter
#
reweighter = Reweighter(sample, sample_manager)
#
# Import and create cutter to provide cut flow
#
from HNL.EventSelection.cutter import Cutter
cutter = Cutter(chain=chain)
#
# 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
#
print "Submitted "+str(len(jobs))+" jobs to cream"
exit(0)
#
#Get specific sample for this subjob
#
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:
from HNL.EventSelection.eventSelector import EventSelector
from HNL.EventSelection.eventCategorization import EventCategory, filterSuperCategory
from HNL.EventSelection.signalLeptonMatcher import SignalLeptonMatcher
slm = SignalLeptonMatcher(chain)
ec = EventCategory(chain)
es = EventSelector('baseline',
chain,
chain,
is_reco_level=False,
event_categorization=ec)
#
# Create cutter to provide cut flow
#
from HNL.EventSelection.cutter import Cutter
cutter = Cutter(chain=chain)
#Loop over events
for entry in eventRange:
#print progress and load in entry
progress(entry - eventRange[0], len(eventRange))
chain.GetEntry(entry)
if not es.passedFilter(cutter, sample.output): continue
slm.saveNewOrder()
category = ec.returnCategory()
if not filterSuperCategory('SingleTau', category): continue
# print category, entry
# if chain._gen_nL < 3: continue
list_of_hist[sample.name] = {}
#
# Load in sample and chain
#
chain = sample.initTree(needhcount=False)
sample_names.append(sample.name)
for v in var:
list_of_hist[sample.name][v] = Histogram(sample.output + '-' + v,
var[v][0], var[v][2],
var[v][1])
from HNL.EventSelection.cutter import Cutter
cutter = Cutter(chain=chain)
#
# Get luminosity weight
#
from HNL.Weights.lumiweight import LumiWeight
lw = LumiWeight(sample, sample_manager)
#
# Set event range
#
if args.isTest:
max_events = 20000
event_range = xrange(max_events) if max_events < len(
sample.getEventRange(args.subJob)) else sample.getEventRange(
args.subJob)
#
#Get specific sample for this subjob
#
sample = sample_manager.getSample(args.sample)
chain = sample.initTree(needhcount=False)
chain.year = int(args.year)
chain.is_signal = 'HNL' in sample.name
chain.selection = args.selection
chain.strategy = args.strategy
reweighter = Reweighter(sample, sample_manager)
# Import and create cutter to provide cut flow
#
from HNL.EventSelection.cutter import Cutter
cutter = Cutter(chain=chain)
#
# Create new reduced tree (except if it already exists and overwrite option is not used)
#
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', 'TMVA', 'data', 'testArea'))
signal_str = 'Signal' if chain.is_signal else 'Background'
output_name = os.path.join(
output_base, 'TMVA', str(args.year),
args.region + '-' + args.selection, signal_str, 'tmp_' + sample.output,
sample.name + '_' + sample.output + '_' + str(args.subJob) + '.root')
makeDirIfNeeded(output_name)
exit(0)
#
# Load in sample and chain
#
if not args.includeData and args.sample == 'Data':
raise RuntimeError(
'Trying to run data while it is not allowed. Stopping the program')
sample = sample_manager.getSample(args.sample)
chain = sample.initTree(needhcount=False)
#
# Import and create cutter to provide cut flow
#
from HNL.EventSelection.cutter import Cutter
cutter = Cutter(chain=chain)
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
#
jobs,
argParser,
jobLabel='calcSignalEfficiency')
exit(0)
#
# Load in sample and chain
#
sample = getSampleFromList(sample_list, args.sample)
chain = sample.initTree(needhcount=False)
#
# Import and create cutter to provide cut flow
#
from HNL.EventSelection.cutter import Cutter
cutter = Cutter(chain=chain)
if args.isTest:
event_range = xrange(500)
else:
event_range = sample.getEventRange(args.subJob)
if 'HNL' in sample.name:
chain.HNLmass = float(sample.name.rsplit('-', 1)[1])
chain.year = int(args.year)
#
# Loop over all events
#
from HNL.Tools.helpers import progress
from HNL.ObjectSelection.tauSelector import tau_DMfinding, isCleanFromLightLeptons, passedMuonDiscr, passedElectronDiscr, tau_id_WP, isGoodGenTau
#
# Some basic variables about the sample to store in the chain
#
chain.HNLmass = sample.getMass()
chain.year = int(args.year)
#
# Skip HNL masses that were not defined
#
if args.masses is not None and chain.HNLmass not in args.masses: continue
#
# Create cutter to provide cut flow
#
cutter = Cutter(chain = chain)
#
# Loop over all events
#
ec = EventCategory(chain)
es = EventSelector(args.region, args.selection, object_selection_param, not args.genLevel, ec)
for entry in event_range:
chain.GetEntry(entry)
progress(entry - event_range[0], len(event_range))
cutter.cut(True, 'Total')
#
#Triggers
jobs += [(sample.name, str(njob))]
submitJobs(__file__, ('sample', 'subJob'), jobs, argParser, jobLabel = 'calcSignalEfficiency')
exit(0)
#
# Load in sample and chain
#
sample = sample_manager.getSample(args.sample)
chain = sample.initTree(needhcount = False)
#
# Import and create cutter to provide cut flow
#
from HNL.EventSelection.cutter import Cutter
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)
jobs,
argParser,
jobLabel='closureTest')
exit(0)
#
# Load in sample and chain
#
sample = sample_manager.getSample(args.sample)
chain = sample.initTree(needhcount=False)
#
# Import and create cutter to provide cut flow
#
from HNL.EventSelection.cutter import Cutter
cutter = Cutter(chain=chain)
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
#
# Get luminosity weight
#
# Some basic variables about the sample to store in the chain
#
chain.HNLmass = sample.getMass()
chain.year = int(args.year)
#
# Skip HNL masses that were not defined
#
if args.masses is not None and chain.HNLmass not in args.masses:
continue
#
# Create cutter to provide cut flow
#
cutter = Cutter(chain=chain)
#
# Initialize reweighter
#
reweighter = Reweighter(sample, sample_manager)
#
# Load in MVA reader if needed
#
if args.strategy == 'MVA':
tmva = {}
for sel in ['lowMassSR', 'highMassSR']:
tmva[sel] = {}
for n in listAvailableMVAs():
try:
print 'get sample'
sample = sample_manager.getSample(args.sample)
print 'init tree'
chain = sample.initTree(int(args.subJob))
# print sample.list_of_subjobclusters
print 'year'
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
if sample.is_data:
output_file_name = 'Data'
elif chain.is_signal or args.region is not None:
output_file_name = sample.path.split('/')[-1].rsplit('.', 1)[0]