or sname.endswith('Down')):
samples.pop(sname)
try:
signals.remove(sname)
except ValueError:
pass
cuts = {}
with open('cuts.py') as cutsfile:
exec(cutsfile)
nuisances = {}
with open('nuisances.py') as nuisancesfile:
exec(nuisancesfile)
subsamplemap = dict(utils.flatten_samples(samples))
for sname in signals:
for sub in list(subsamplemap[sname]):
if obsname not in sub:
samples.pop(sub)
subsamplemap[sname].remove(sub)
for cut in cuts.keys():
if obsname not in cut:
cuts.pop(cut)
categorymap = dict(utils.flatten_cuts(cuts))
nuisances_original = copy.deepcopy(nuisances)
utils.update_nuisances_with_subsamples(nuisances, subsamplemap.items())
utils.update_nuisances_with_categories(nuisances, categorymap.items())
if os.path.exists(opt.variablesFile):
handle = open(opt.variablesFile, 'r')
exec(handle)
handle.close()
nuisances = {}
if opt.nuisancesFile == None:
print " Please provide the nuisances structure if you want to add nuisances "
elif os.path.exists(opt.nuisancesFile):
handle = open(opt.nuisancesFile, 'r')
exec(handle)
handle.close()
import LatinoAnalysis.ShapeAnalysis.utils as utils
subsamplesmap = utils.flatten_samples(samples)
categoriesmap = utils.flatten_cuts(cuts)
utils.update_variables_with_categories(variables, categoriesmap)
utils.update_nuisances_with_subsamples(nuisances, subsamplesmap)
utils.update_nuisances_with_categories(nuisances, categoriesmap)
# check if only one cut or only one variable
# is requested, and filter th elist of cuts and variables
# using this piece of information
if opt.onlyVariable != None:
list_to_remove = []
for variableName, variable in variables.iteritems():
if variableName != opt.onlyVariable:
list_to_remove.append(variableName)
