def create_readers(self):
if self.verbose:
print "Setting up btag calibration readers"
self.v_sys = getattr(ROOT, 'vector<string>')()
for syst in self.iterative_systs:
self.v_sys.push_back('up_' + syst)
self.v_sys.push_back('down_' + syst)
self.reader = BTagCalibrationReader(3, 'central', self.v_sys)
self.reader.load(self.calibrator, 0, 'iterativefit')
self.reader.load(self.calibrator, 1, 'iterativefit')
self.reader.load(self.calibrator, 2, 'iterativefit')
def create_readers(self):
if self.verbose > 0:
print "Setting up btag calibration readers"
self.readers = {}
# Create empty vector for systematics.
# It would be better to create a single reader, as pointed out here https://hypernews.cern.ch/HyperNews/CMS/get/btag/1341.html , but this would mean reworking this whole module.
# For now, adopted the quicker solution. Will implement the full one in a longer timescale. P.
v_sys = getattr(ROOT, 'vector<string>')()
for wp in [0, 1, 2]:
for syst in [
'central', 'up', 'down', 'up_correlated', 'down_correlated'
]:
for flavor in [0, 1, 2]:
self.readers[(self.mtypes[flavor], wp, syst,
flavor)] = BTagCalibrationReader(
wp, syst, v_sys)
self.readers[(self.mtypes[flavor], wp, syst,
flavor)].load(self.calibrator, flavor,
self.mtypes[flavor])
if self.csvfastsim and 'correlated' not in syst:
self.readers[('fastsim', wp, syst,
flavor)] = BTagCalibrationReader(
wp, syst, v_sys)
self.readers[('fastsim', wp, syst,
flavor)].load(self.calibrator_fastsim,
flavor, 'fastsim')
allsysts = ["up_%s" % s for s in self.iterative_systs]
allsysts += ["down_%s" % s for s in self.iterative_systs]
allsysts += ["central"]
for syst in allsysts:
v_iterativefit_sys = getattr(ROOT, 'vector<string>')()
#v_iterativefit_sys.push_back(syst)
self.readers[('iterative', syst)] = BTagCalibrationReader(
3, syst, v_iterativefit_sys)
self.readers[('iterative', syst)].load(
self.calibrator,
0, #..., #flavour
'iterativefit')
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,
tagger,
wp='medium',
sigma='central',
channel='mutau',
year=2017,
maxeta=2.4):
"""Load b tag weights from CSV file."""
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.wpname = 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
print "Loading BTagWeightTool for %s (%s WP)..." % (tagger, wp)
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
hists = {} # histograms to compute the b tagging efficiencies in MC
effmaps = {
} # b tag efficiencies in MC to compute b tagging weight for an event
efffile = ensureTFile(effname)
default = False
if not efffile:
warning(
"File %s with efficiency histograms does not exist! Reverting to default efficiency histogram..."
% (effname),
title="BTagWeightTool")
default = True
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] = createEfficienyMap(
histname) # numerator = b tagged jets
hists[flavor + '_all'] = createEfficienyMap(
histname + '_all') # denominator = all jets
if efffile:
effmaps[flavor] = efffile.Get(effname)
if not effmaps[flavor]:
warning(
"histogram '%s' does not exist in %s! Reverting to default efficiency histogram..."
% (effname, efffile.GetName()),
title="BTagWeightTool")
default = True
effmaps[flavor] = createDefaultEfficiencyMap(
effname, flavor, wp)
else:
effmaps[flavor] = createDefaultEfficiencyMap(
effname, flavor, wp)
effmaps[flavor].SetDirectory(0)
efffile.Close()
if default:
warning("Made use of default efficiency histograms! The b tag weights from this module should be regarded as placeholders only,\n"+\
"and should NOT be used for analyses. B (mis)tag efficiencies in MC are analysis dependent. Please create your own\n"+\
"efficiency histogram with corrections/btag/getBTagEfficiencies.py after running all MC samples with BTagWeightTool.",title="BTagWeightTool")
self.tagged = tagged
self.calib = calib
self.reader = reader
self.hists = hists
self.effmaps = effmaps
self.maxeta = maxeta
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
class BTagCSVFullShape(object):
def __init__(self, csvfile, verbose=False):
self.csvfile = csvfile
self.verbose = True #verbose
self.algo = 'csvv2'
self.iterative_systs = [
'jes', 'lf', 'hf', 'hfstats1', 'hfstats2', 'lfstats1', 'lfstats2',
'cferr1', 'cferr2'
]
self.init()
self.create_readers()
def init(self):
if self.verbose:
print "Initializing btag calibrator from %s" % self.csvfile
self.calibrator = BTagCalibration(self.algo, self.csvfile)
def create_readers(self):
if self.verbose:
print "Setting up btag calibration readers"
self.v_sys = getattr(ROOT, 'vector<string>')()
for syst in self.iterative_systs:
self.v_sys.push_back('up_' + syst)
self.v_sys.push_back('down_' + syst)
self.reader = BTagCalibrationReader(3, 'central', self.v_sys)
self.reader.load(self.calibrator, 0, 'iterativefit')
self.reader.load(self.calibrator, 1, 'iterativefit')
self.reader.load(self.calibrator, 2, 'iterativefit')
def get_SF(self, pt, eta, flavor, val, syst='central'):
fl_index = min(-flavor + 5, 2)
"""
Note the flavor convention: hadronFlavor is b=5, c=4, f=0
Convert them to the btagging group convention of 0,1,2
"""
syst = syst.lower()
return self.reader.eval_auto_bounds(
syst if self.relevant_iterative_systs(fl_index, syst) else
'central', fl_index, eta, pt, val)
def relevant_iterative_systs(self, flavor, syst):
"""Returns true if a flavor/syst combination is relevant"""
if flavor == 0:
return syst in [
"central", "up_jes", "down_jes", "up_lf", "down_lf",
"up_hfstats1", "down_hfstats1", "up_hfstats2", "down_hfstats2"
]
elif flavor == 1:
return syst in [
"central", "up_cferr1", "down_cferr1", "up_cferr2",
"down_cferr2"
]
elif flavor == 2:
return syst in [
"central", "up_jes", "down_jes", "up_hf", "down_hf",
"up_lfstats1", "down_lfstats1", "up_lfstats2", "down_lfstats2"
]
return True
def __init__(self, tagger='DeepCSV', wp='medium', sigmabc='central', sigmalight='central', channel='ttbar', year=2016):
"""Load b tag weights from CSV file."""
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(sigmabc in ['central','up_correlated','down_correlated','up_uncorrelated','down_uncorrelated']), "BTagWeightTool: You must choose a WP for b/c jets from: central, up_correlated, down_correlated, up_uncorrelated, down_uncorrelated!"
assert(sigmalight in ['central','up_correlated','down_correlated','up_uncorrelated','down_uncorrelated']), "BTagWeightTool: You must choose a WP for light jets from: central, up_correlated, down_correlated, up_uncorrelated, down_uncorrelated!"
#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():
csvnamebc = path+'DeepCSV_2016LegacySF_V1_YearCorrelation-V1.csv'
csvnamelight = path+'DeepCSV_2016LegacySF_WP_V1.csv'
effname = path+'DeepCSV_2016_Moriond17_eff.root'
else:
csvnamebc = path+'CSVv2_Moriond17_B_H.csv'
csvnamelight = path+'CSVv2_Moriond17_B_H.csv'
effname = path+'CSVv2_2016_Moriond17_eff.root'
elif year==2017:
if 'deep' in tagger.lower():
csvnamebc = path+'DeepCSV_94XSF_V4_B_F_YearCorrelation-V1.csv'
csvnamelight = path+'DeepCSV_94XSF_WP_V4_B_F.csv'
effname = path+'DeepCSV_2017_Fall17_eff.root'
else:
csvnamebc = path+'CSVv2_Moriond17_B_H.csv'
csvnamelight = path+'CSVv2_Moriond17_B_H.csv'
effname = path+'CSVv2_2017_Fall17_eff.root'
elif year==2018:
if 'deep' in tagger.lower():
csvnamebc = path+'DeepCSV_102XSF_V1_YearCorrelation-V1.csv'
csvnamelight = path+'DeepCSV_102XSF_WP_V1.csv'
effname = path+'DeepCSV_2018_Autumn18_eff.root'
else:
csvnamebc = path+'CSVv2_94XSF_V2_B_F.csv'
csvnamelight = path+'CSVv2_94XSF_V2_B_F.csv'
effname = path+'CSVv2_2018_Autumn18_eff.root'
# TAGGING WP
self.wpname = wp
self.wp = getattr(BTagWPs(tagger,year),wp)
if 'deep' in tagger.lower():
tagged = lambda j: j.btagDeepB>self.wp
else:
tagged = lambda j: j.btagCSVV2>self.wp
# CSV READER
print "Loading BTagWeightTool for %s (%s WP)..."%(tagger,wp)
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 = 'mujets' # 'mujets' for QCD; 'comb' for QCD+TT
#Load reader for b/c jets
calibbc = BTagCalibration(tagger, csvnamebc)
readerbc = BTagCalibrationReader(op, sigmabc)
readerbc.load(calibbc, FLAV_B, type_bc)
readerbc.load(calibbc, FLAV_C, type_bc)
#Load reader for light jets
caliblight = BTagCalibration(tagger, csvnamelight)
readerlight = BTagCalibrationReader(op, sigmalight)
readerlight.load(caliblight, FLAV_UDSG, type_udsg)
# EFFICIENCIES
effmaps = { } # b tag efficiencies in MC to compute b tagging weight for an event
efffile = ensureTFile(effname)
default = False
if not efffile:
warning("File %s with efficiency histograms does not exist! Reverting to default efficiency histogram..."%(effname),title="BTagWeightTool")
default = True
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)
if efffile:
effmaps[flavor] = efffile.Get(effname)
if not effmaps[flavor]:
warning("histogram '%s' does not exist in %s! Reverting to default efficiency histogram..."%(effname,efffile.GetName()),title="BTagWeightTool")
default = True
effmaps[flavor] = createDefaultEfficiencyMap(effname,flavor,wp)
else:
effmaps[flavor] = createDefaultEfficiencyMap(effname,flavor,wp)
effmaps[flavor].SetDirectory(0)
efffile.Close()
if default:
warning("Made use of default efficiency histograms! The b tag weights from this module should be regarded as placeholders only,\n"+\
"and should NOT be used for analyses. B (mis)tag efficiencies in MC are analysis dependent. Please create your own\n"+\
"efficiency histogram with corrections/btag/getBTagEfficiencies.py after running all MC samples with BTagWeightTool.",title="BTagWeightTool")
self.tagged = tagged
self.calibbc = calibbc
self.readerbc = readerbc
self.caliblight = caliblight
self.readerlight = readerlight
self.effmaps = effmaps