loadedSamples, 'fwlite_Zgamma_LO_order2_15weights_%s' % args.detector)
ttgammaSample = getattr(
loadedSamples,
'fwlite_ttgamma_bg_LO_order2_15weights_%s' % args.detector)
signal = [ttZSample, ttgamma1lSample, ttgamma2lSample]
ttZBg = [WZSample, tWZSample, tZqSample, ttgammaSample]
ttgammaBg = [ttSample, tWSample, tWZSample, tZqSample, ZgammaSample]
def checkReferencePoint(sample):
''' check if sample is simulated with a reference point
'''
return pickle.load(file(sample.reweight_pkl))['ref_point'] != {}
# set selection string
ttZSelectionString = cutInterpreter.cutString(
'lepSel3-onZ-njet3p-nbjet1p-Zpt0-leptonIso3')
ttgamma1lSelectionString = cutInterpreter.cutString(
'lepSel1-gammapt40-njet3p-nbjet1p-relIso0to0.12-met40-leptonIso1')
ttgamma2lSelectionString = cutInterpreter.cutString(
'lepSel2-gammapt40-njet2p-nbjet1p-relIso0to0.12-met40-leptonIso2')
ttZSample.setSelectionString(ttZSelectionString)
ttgamma1lSample.setSelectionString(ttgamma1lSelectionString)
ttgamma2lSample.setSelectionString(ttgamma2lSelectionString)
# somehow has to be separate from the next loop
if args.small:
for s in signal + ttZBg + ttgammaBg:
s.reduceFiles(to=20)
# configure samples
import TTXPheno.Tools.logger as logger
import RootTools.core.logger as logger_rt
logger = logger.get_logger( 'INFO', logFile = None)
logger_rt = logger_rt.get_logger('INFO', logFile = None)
# TTXPheno
from TTXPheno.Tools.cutInterpreterGen import cutInterpreter
from TTXPheno.samples.benchmarks import *
# Sample
sample = fwlite_ttZ_ll_LO_order2_15weights_ref
# Debug 1 event
sample.reduceFiles( to = 1 )
w = WeightInfo(sample.reweight_pkl)
w.set_order( 2 )
selection_string = cutInterpreter.cutString('lepSel3-onZ-njet3p-nbjet1p-Zpt0')
#selection_string = "evt==955001&&run==1&&lumi==9551"
# return [ histo_to_list(histo.ProjectionX("%i_px"%i, i+1, i+1)) for i in range( histo.GetNbinsY() ) ]
# # return histo_to_list( histo )
# Fisher information in ptZ histo
coeff_Z_pt = w.getCoeffPlotFromDraw( sample, 'genZ_pt', [ 20, 0, 500 ], selection_string, weightString='150*ref_lumiweight1fb')
# Fisher information in x-sec
#coeff_tot = getCoeffListFromDraw( sample, selection_string, weightString='150*lumiweight1fb')
coeff_tot = w.getCoeffListFromDraw( sample, selection_string, weightString='150*ref_lumiweight1fb' )
print w.get_weight_yield(coeff_tot, ctZ=0.), w.get_weight_yield(coeff_tot, ctZ=5)
#print(len(coeff_Z_pt))
ttgammaSample = getattr( loadedSamples, 'fwlite_ttgamma_bg_LO_order2_15weights_%s' %args.detector )
bg = [ WZSample, tZqSample, tWZSample, ttgammaSample ]
nonInfo = []
if args.nonInfoSignal:
ttZISRSample = copy.deepcopy( ttXSample ) #select ttgamma events with isolated gamma from ISR (cat a2)
ttZISRSample.name = 'fwlite_nonInfo_LO_order2_15weights_ref'
nonInfo.append( ttZISRSample)
def checkReferencePoint( sample ):
''' check if sample is simulated with a reference point
'''
return pickle.load(file(sample.reweight_pkl))['ref_point'] != {}
# set selection string
selectionString = cutInterpreter.cutString(args.selection)
selectionString_up = selectionString.replace('nBTag','nBTag_JEC_up').replace('nrecoJet','nrecoJets_JEC_up')
selectionString_down = selectionString.replace('nBTag','nBTag_JEC_down').replace('nrecoJet','nrecoJets_JEC_down')
# somehow has to be separate from the next loop
if args.small:
for s in [ttXSample] + bg + nonInfo:
s.reduceFiles( to = 30 )
# configure samples
for i, s in enumerate([ttXSample] + bg + nonInfo):
s.shortname = s.name.split('_')[1]
s.event_factor = s.nEvents / float( s.chain.GetEntries() )
s.xsecScaleFactor = s.xsec14 / s.xsec if args.scale14TeV else 1.
s.weightInfo = WeightInfo( s.reweight_pkl )
def __init__(self, name, relative_fraction):
self.name = name
self.relative_fraction = relative_fraction
def setSelectionString(self, *args, **kwargs):
pass
# Lumi
lumi = 150
# Backgrounds
backgrounds = [FakeBackground("bkg1", .1), FakeBackground("bkg2", .2)]
# set selection string
selectionString = cutInterpreter.cutString('lepSel3-onZ-njet3p-nbjet1p')
for sample in [ttZ_sample] + list(backgrounds):
sample.setSelectionString(
cutInterpreter.cutString('lepSel3-onZ-njet3p-nbjet1p'))
# parameter point
params = {'ctZ': 0., 'ctZI': 0.} # Can specify any EFT parameter here
observation = {}
signal_jec_uncertainty = {}
signal_fakerate_uncertainty = {}
ttZ_SM_rate = {}
ttZ_SM_jec_uncertainty = {}
ttZ_SM_fakerate_uncertainty = {}
background_rate = {}
background_jec_uncertainty = {}
