def __init__( self, year=2017, sigma='central' ):
"""Load data and MC pilup profiles."""
assert( year in [2016,2017,2018] ), "You must choose a year from: 2016, 2017, or 2018."
assert( sigma in ['central','up','down'] ), "You must choose a s.d. variation from: 'central', 'up', or 'down'."
minbias = '69p2'
if sigma=='down':
minbias = '66p0168' # -4.6%
elif sigma=='up':
minbias = '72p3832' # +4.6%
if year==2016:
self.datafile = ensureTFile( path+'Data_PileUp_2016_%s.root'%(minbias), 'READ')
self.mcfile = ensureTFile( path+'MC_PileUp_2016.root', 'READ')
elif year==2017:
self.datafile = ensureTFile( path+'Data_PileUp_2017_%s.root'%(minbias), 'READ')
self.mcfile = ensureTFile( path+'MC_PileUp_2017.root', 'READ')
else:
self.datafile = ensureTFile( path+'Data_PileUp_2018_%s.root'%(minbias), 'READ')
self.mcfile = ensureTFile( path+'MC_PileUp_2018.root', 'READ')
self.datahist = self.datafile.Get('pileup')
self.mchist = self.mcfile.Get('pileup')
self.datahist.SetDirectory(0)
self.mchist.SetDirectory(0)
self.datahist.Scale(1./self.datahist.Integral())
self.mchist.Scale(1./self.mchist.Integral())
self.datafile.Close()
self.mcfile.Close()
def __init__(self, year=2017, sigma='central'):
"""Load data and MC pilup profiles."""
assert (year
in [2016, 2017,
2018]), "You must choose a year from: 2016, 2017, or 2018."
assert (
sigma in ['central', 'up', 'down']
), "You must choose a s.d. variation from: 'central', 'up', or 'down'."
if year == 2016:
self.datafile = ensureTFile(path + 'Data_PileUp_2016_69p2.root',
'READ')
self.mcfile = ensureTFile(path + 'MC_PileUp_2016_Moriond17.root',
'READ')
if year == 2017:
self.datafile = ensureTFile(path + 'Data_PileUp_2017_69p2.root',
'READ')
self.mcfile = ensureTFile(path + 'MC_PileUp_2017_Winter17_V2.root',
'READ')
else:
self.datafile = ensureTFile(path + 'Data_PileUp_2018_69p2.root',
'READ')
self.mcfile = ensureTFile(path + 'MC_PileUp_2018_Autumn18.root',
'READ')
self.datahist = self.datafile.Get('pileup')
self.mchist = self.mcfile.Get('pileup')
self.datahist.SetDirectory(0)
self.mchist.SetDirectory(0)
self.datahist.Scale(1. / self.datahist.Integral())
self.mchist.Scale(1. / self.mchist.Integral())
self.datafile.Close()
self.mcfile.Close()
def __init__(self, year=2017):
"""Load Z pT weights."""
assert year in [
2016, 2017, 2018
], "ZptCorrectionTool: You must choose a year from: 2016, 2017, or 2018."
if year == 2016:
filename = zptpath + "Zpt_weights_2016.root"
elif year == 2017:
filename = zptpath + "Zpt_weights_2017.root"
else:
filename = zptpath + "Zpt_weights_2018.root"
file = ensureTFile(filename, 'READ')
hist = file.Get('zptmass_weights')
hist.SetDirectory(0)
file.Close()
self.hist = hist
self.filename = filename
def __init__(self,
tagger,
wp='medium',
sigma='central',
channel='mutau',
year=2017):
"""Load b tag weights from CSV file."""
print "Loading BTagWeightTool for %s (%s WP)..." % (tagger, wp)
assert (year
in [2016, 2017,
2018]), "You must choose a year from: 2016, 2017, or 2018."
assert (tagger in [
'CSVv2', 'DeepCSV'
]), "BTagWeightTool: You must choose a tagger from: CSVv2, DeepCSV!"
assert (wp in [
'loose', 'medium', 'tight'
]), "BTagWeightTool: You must choose a WP from: loose, medium, tight!"
assert (sigma in [
'central', 'up', 'down'
]), "BTagWeightTool: You must choose a WP from: central, up, down!"
#assert(channel in ['mutau','eletau','tautau','mumu']), "BTagWeightTool: You must choose a channel from: mutau, eletau, tautau, mumu!"
# FILE
if year == 2016:
if 'deep' in tagger.lower():
csvname = path + 'DeepCSV_Moriond17_B_H.csv'
effname = path + 'DeepCSV_2016_Moriond17_eff.root'
else:
csvname = path + 'CSVv2_Moriond17_B_H.csv'
effname = path + 'CSVv2_2016_Moriond17_eff.root'
elif year == 2017:
if 'deep' in tagger.lower():
csvname = path + 'DeepCSV_94XSF_V3_B_F.csv'
effname = path + 'DeepCSV_2017_12Apr2017_eff.root'
else:
csvname = path + 'CSVv2_94XSF_V2_B_F.csv'
effname = path + 'CSVv2_2017_12Apr2017_eff.root'
elif year == 2018:
if 'deep' in tagger.lower():
csvname = path + 'DeepCSV_94XSF_V3_B_F.csv'
effname = path + 'DeepCSV_2018_Autumn18_eff.root'
else:
csvname = path + 'CSVv2_94XSF_V2_B_F.csv'
effname = path + 'CSVv2_2018_Autumn18_eff.root'
# TAGGING WP
self.wp = getattr(BTagWPs(tagger, year), wp)
if 'deep' in tagger.lower():
tagged = lambda e, i: e.Jet_btagDeepB[i] > self.wp
else:
tagged = lambda e, i: e.Jet_btagCSVV2[i] > self.wp
# CSV READER
op = OP_LOOSE if wp == 'loose' else OP_MEDIUM if wp == 'medium' else OP_TIGHT if wp == 'tight' else OP_RESHAPING
type_udsg = 'incl'
type_bc = 'comb' # 'mujets' for QCD; 'comb' for QCD+TT
calib = BTagCalibration(tagger, csvname)
reader = BTagCalibrationReader(op, sigma)
reader.load(calib, FLAV_B, type_bc)
reader.load(calib, FLAV_C, type_bc)
reader.load(calib, FLAV_UDSG, type_udsg)
# EFFICIENCIES
ptbins = array(
'd', [10, 20, 30, 50, 70, 100, 140, 200, 300, 500, 1000, 1500])
etabins = array('d', [-2.5, -1.5, 0.0, 1.5, 2.5])
bins = (len(ptbins) - 1, ptbins, len(etabins) - 1, etabins)
hists = {}
effs = {}
efffile = ensureTFile(effname)
for flavor in [0, 4, 5]:
flavor = flavorToString(flavor)
histname = "%s_%s_%s" % (tagger, flavor, wp)
effname = "%s/eff_%s_%s_%s" % (channel, tagger, flavor, wp)
hists[flavor] = TH2F(histname, histname, *bins)
hists[flavor + '_all'] = TH2F(histname + '_all', histname + '_all',
*bins)
effs[flavor] = efffile.Get(effname)
hists[flavor].SetDirectory(0)
hists[flavor + '_all'].SetDirectory(0)
effs[flavor].SetDirectory(0)
efffile.Close()
self.tagged = tagged
self.calib = calib
self.reader = reader
self.hists = hists
self.effs = effs
def __init__(self, trigger, wp='medium', id='MVAv2', year=2016):
"""Load tau trigger histograms from files."""
print "Loading TauTriggerSFs for %s (%s WP)..." % (trigger, wp)
trigger = trigger.replace('tautau', 'ditau').replace('eletau', 'etau')
assert (trigger
in ['ditau', 'mutau',
'etau']), "Choose from: 'ditau', 'mutau', 'etau' triggers."
assert (
wp in ['vloose', 'loose', 'medium', 'tight', 'vtight', 'vvtight']
), "You must choose a WP from: vloose, loose, medium, tight, vtight, or vvtight"
assert (
id in ['MVAv2', 'dR0p3']
), "Choose from two provided ID types: 'MVAv2', 'dR0p3'. 'MVAv2' uses dR0p5, and 'dR0p3' is also an MVA-based ID."
assert (
id == 'MVAv2'
), "Tau POG is currently only providing efficiencies for MVAv2, sorry."
assert (year
in [2016, 2017,
2018]), "You must choose a year from: 2016, 2017, or 2018."
print "Loading Efficiencies for trigger %s usingTau %s ID WP %s for year %i" % (
trigger, id, wp, year)
# Assume this is in CMSSW with the below path structure
if year == 2018: year = 2017
file = ensureTFile(
path + '%d/tauTriggerEfficiencies%i.root' % (year, year), 'r')
self.fit_data = {}
self.fit_mc = {}
self.fitUnc_data = {}
self.fitUnc_mc = {}
self.effEtaPhi_data = {}
self.effEtaPhi_mc = {}
self.effEtaPhiAvg_data = {}
self.effEtaPhiAvg_mc = {}
for dm in [0, 1, 10]:
# Load the TF1s containing the analytic best-fit results.
self.fit_data[dm] = extractTH1(
file, '%s_%s%s_dm%d_DATA_fit' % (trigger, wp, id, dm))
self.fit_mc[dm] = extractTH1(
file, '%s_%s%s_dm%d_MC_fit' % (trigger, wp, id, dm))
# Load the TH1s containing the analytic best-fit result in 1 GeV incriments and the associated uncertainty.
self.fitUnc_data[dm] = extractTH1(
file, '%s_%s%s_dm%d_DATA_errorBand' % (trigger, wp, id, dm))
self.fitUnc_mc[dm] = extractTH1(
file, '%s_%s%s_dm%d_MC_errorBand' % (trigger, wp, id, dm))
# Load the TH2s containing the eta phi efficiency corrections
self.effEtaPhi_data[dm] = extractTH1(
file, '%s_%s%s_dm%d_DATA' % (trigger, wp, id, dm))
self.effEtaPhi_mc[dm] = extractTH1(
file, '%s_%s%s_dm%d_MC' % (trigger, wp, id, dm))
# Eta Phi Averages
self.effEtaPhiAvg_data[dm] = extractTH1(
file, '%s_%s%s_dm%d_DATA_AVG' % (trigger, wp, id, dm))
self.effEtaPhiAvg_mc[dm] = extractTH1(
file, '%s_%s%s_dm%d_MC_AVG' % (trigger, wp, id, dm))
file.Close()
self.trigger = trigger
self.year = year
self.wp = wp
self.id = id
def __init__(self,
tagger,
jettype,
wp='loose',
sigma='central',
channel='ll',
year=2017):
"""Load b tag weights from CSV file."""
#print "Loading BTagWeightTool for %s (%s WP)..."%(tagger,wp)
assert (year
in [2016, 2017,
2018]), "You must choose a year from: 2016, 2017, or 2018."
assert (tagger in [
'CSVv2', 'DeepCSV'
]), "BTagWeightTool: You must choose a tagger from: CSVv2, DeepCSV!"
assert (wp in [
'loose', 'medium', 'tight'
]), "BTagWeightTool: You must choose a WP from: loose, medium, tight!"
assert (sigma in [
'central', 'up', 'down'
]), "BTagWeightTool: You must choose a WP from: central, up, down!"
self.jettype = jettype
# FILE
if year == 2016:
csvname = path + 'DeepCSV_2016LegacySF_V1.csv'
effname = path + 'DeepCSV_%s_2016_eff.root' % jettype
elif year == 2017:
csvname = path + 'DeepCSV_94XSF_V5_B_F.csv'
effname = path + 'DeepCSV_%s_2017_eff.root' % jettype
elif year == 2018:
csvname = path + 'DeepCSV_102XSF_V1.csv'
effname = path + 'DeepCSV_%s_2018_eff.root' % jettype
# TAGGING WP
self.wp = getattr(BTagWPs(tagger, year), wp)
# CSV READER
op = OP_LOOSE if wp == 'loose' else OP_MEDIUM if wp == 'medium' else OP_TIGHT if wp == 'tight' else OP_RESHAPING
type_udsg = 'incl'
type_bc = 'comb' # 'mujets' for QCD; 'comb' for QCD+TT
calib = BTagCalibration(tagger, csvname)
reader = BTagCalibrationReader(op, sigma)
reader.load(calib, FLAV_B, type_bc)
reader.load(calib, FLAV_C, type_bc)
reader.load(calib, FLAV_UDSG, type_udsg)
self.sigma = sigma
# EFFICIENCIES
ptbins = array(
'd', [10, 20, 30, 50, 70, 100, 140, 200, 300, 500, 1000, 1500])
etabins = array('d', [-2.5, -1.5, 0.0, 1.5, 2.5])
bins = (len(ptbins) - 1, ptbins, len(etabins) - 1, etabins)
hists = {}
effs = {}
if tagger in ['CSVv2', 'DeepCSV']:
efffile = ensureTFile(effname)
for flavor in [0, 4, 5]:
flavor = flavorToString(flavor)
histname = "%s_%s_%s" % (tagger, flavor, wp)
effname = "%s/eff_%s_%s_%s" % (channel, tagger, flavor, wp)
hists[flavor] = TH2F(histname, histname, *bins)
hists[flavor + '_all'] = TH2F(histname + '_all',
histname + '_all', *bins)
effs[flavor] = efffile.Get(effname)
hists[flavor].SetDirectory(0)
hists[flavor + '_all'].SetDirectory(0)
effs[flavor].SetDirectory(0)
efffile.Close()
else:
efffile = ensureTFile(effname)
for flavor in [0, 4, 5]:
flavor = flavorToString(flavor)
histname = "%s_%s_%s" % (tagger, flavor, wp)
effname = "%s/eff_%s_%s_%s" % (channel, tagger, flavor, wp)
hists[flavor] = TH2F(histname, histname, *bins)
hists[flavor + '_all'] = TH2F(histname + '_all',
histname + '_all', *bins)
#effs[flavor] = efffile.Get(effname)
hists[flavor].SetDirectory(0)
hists[flavor + '_all'].SetDirectory(0)
#effs[flavor].SetDirectory(0)
efffile.Close()
self.calib = calib
self.reader = reader
self.hists = hists
self.effs = effs