def fill_histos(dirname, row, weight):
mass = frfits.default_scaler(row.e1_e2_Mass) if "charge_weight" in dirname else row.e1_e2_Mass
mass_up = frfits.default_scaler_up(row.e1_e2_Mass) if "charge_weight" in dirname else row.e1_e2_Mass
mass_dw = frfits.default_scaler_down(row.e1_e2_Mass) if "charge_weight" in dirname else row.e1_e2_Mass
histos[dirname]['ePt' ].Fill(row.e1Pt,weight)
histos[dirname]['eAbsEta' ].Fill(row.e1AbsEta,weight)
histos[dirname]['SCEnergy'].Fill(row.e1SCEnergy,weight)
histos[dirname]['ePt' ].Fill(row.e2Pt,weight)
histos[dirname]['eAbsEta' ].Fill(row.e2AbsEta,weight)
histos[dirname]['SCEnergy'].Fill(row.e2SCEnergy,weight)
histos[dirname]['TrkMass' ].Fill(mass, weight)
histos[dirname]['TrkMass_low' ].Fill(mass_dw, weight)
histos[dirname]['TrkMass_high' ].Fill(mass_up, weight)
#histos[dirname]['SCMass' ].Fill(sc_inv_mass(row),weight)
histos[dirname]["e1Pt" ].Fill(row.e1Pt,weight)
histos[dirname]["e2Pt" ].Fill(row.e2Pt,weight)
histos[dirname]["e1AbsEta"].Fill(row.e1AbsEta,weight)
histos[dirname]["e2AbsEta"].Fill(row.e2AbsEta,weight)
histos[dirname]['TrkMass_NOSCALE'].Fill(row.e1_e2_Mass, weight)
histos[dirname]['TrkMass_NoWeight'].Fill(row.e1_e2_Mass)
histos[dirname]['type1_pfMetEt'].Fill(row.type1_pfMetEt, weight)
histos[dirname]['mva_metEt'].Fill(row.mva_metEt, weight)
if row.run < 2:
histos[dirname]["trig_weight" ].Fill( self.pucorrector(row.nTruePU) )
histos[dirname]["PU_weight" ].Fill( mcCorrectors.get_electron_corrections(row,'e1','e2') )
histos[dirname]["idIso_weight"].Fill( mcCorrectors.double_electron_trigger(row) )
def anti_charge_flip_100(row):
z_Mass_distance = row.e1_e2_Mass - frfits.default_scaler(91.2) \
if row.e1_e2_SS else \
row.e1_e2_Mass - 91.2
z_Mass_distance = abs(z_Mass_distance)
if z_Mass_distance <= 10:
return False
return True
def anti_charge_flip_90(row):
z_Mass_distance = row.e1_e2_Mass - frfits.default_scaler(91.2) \
if row.e1_e2_SS else \
row.e1_e2_Mass - 91.2
z_Mass_distance = abs(z_Mass_distance)
if row.e1AbsEta < 1.48 and row.e2AbsEta < 1.48: #both barrel
return ( ( row.mva_metEt ) > 45 or z_Mass_distance > 10 )
elif row.e1AbsEta < 1.48 or row.e2AbsEta < 1.48: #at least one in barrel
return ( ( row.mva_metEt ) > 55 or z_Mass_distance < 25 )
else: #both in endcap
return ( ( row.mva_metEt ) > 60 or z_Mass_distance > 30 )
return True
def fill_histos(dirname, row, weight):
mass = frfits.default_scaler(
row.e1_e2_Mass
) if "charge_weight" in dirname else row.e1_e2_Mass
mass_up = frfits.default_scaler_up(
row.e1_e2_Mass
) if "charge_weight" in dirname else row.e1_e2_Mass
mass_dw = frfits.default_scaler_down(
row.e1_e2_Mass
) if "charge_weight" in dirname else row.e1_e2_Mass
histos[dirname]['ePt'].Fill(row.e1Pt, weight)
histos[dirname]['eAbsEta'].Fill(row.e1AbsEta, weight)
histos[dirname]['SCEnergy'].Fill(row.e1SCEnergy, weight)
histos[dirname]['ePt'].Fill(row.e2Pt, weight)
histos[dirname]['eAbsEta'].Fill(row.e2AbsEta, weight)
histos[dirname]['SCEnergy'].Fill(row.e2SCEnergy, weight)
histos[dirname]['TrkMass'].Fill(mass, weight)
histos[dirname]['TrkMass_low'].Fill(mass_dw, weight)
histos[dirname]['TrkMass_high'].Fill(mass_up, weight)
#histos[dirname]['SCMass' ].Fill(sc_inv_mass(row),weight)
histos[dirname]["e1Pt"].Fill(row.e1Pt, weight)
histos[dirname]["e2Pt"].Fill(row.e2Pt, weight)
histos[dirname]["e1AbsEta"].Fill(row.e1AbsEta, weight)
histos[dirname]["e2AbsEta"].Fill(row.e2AbsEta, weight)
histos[dirname]['TrkMass_NOSCALE'].Fill(row.e1_e2_Mass, weight)
histos[dirname]['TrkMass_NoWeight'].Fill(row.e1_e2_Mass)
histos[dirname]['type1_pfMetEt'].Fill(row.type1_pfMetEt, weight)
histos[dirname]['mva_metEt'].Fill(row.mva_metEt, weight)
if row.run < 2:
histos[dirname]["trig_weight"].Fill(
self.pucorrector(row.nTruePU))
histos[dirname]["PU_weight"].Fill(
mcCorrectors.get_electron_corrections(row, 'e1', 'e2'))
histos[dirname]["idIso_weight"].Fill(
mcCorrectors.double_electron_trigger(row))
def f(row, weight):
val, w = fcn(row, weight)
return frfits.default_scaler(val), w
def f(row, weight):
val, w = fcn(row, weight)
res = val
if row.ePt < row.mPt:
res = frfits.default_scaler(val)
return res, w
def __init__(self, tree, outfile, **kwargs):
self.channel = 'EMT'
super(WHAnalyzeEMT, self).__init__(tree, outfile, EMuTauTree, **kwargs)
def attr_getter(attribute):
def f(row, weight):
return (getattr(row,attribute), weight)
return f
def mass_scaler(fcn):
def f(row, weight):
val, w = fcn(row, weight)
res = val
if row.ePt < row.mPt:
res = frfits.default_scaler(val)
return res, w
return f
def merge_functions(fcn_1, fcn_2):
def f(row, weight):
r1, w1 = fcn_1(row, weight)
r2, w2 = fcn_2(row, weight)
w = w1 if w1 == w2 else None
return ((r1, r2), w)
return f
def sub_mass(row, weight):
return (row.e_t_Mass, weight) if row.ePt < row.mPt else (row.m_t_Mass, weight)
lead_iso = self.grid_search['']['leading_iso']
sublead_iso = self.grid_search['']['subleading_iso']
#def f_prob(row, weight):
# p_m = ( self.obj1_weight(row, lead_iso, sublead_iso) + \
# self.obj1_qcd_weight(row, lead_iso, sublead_iso))/2
# p_e = ( self.obj2_weight(row, lead_iso, sublead_iso) + \
# self.obj2_qcd_weight(row, lead_iso, sublead_iso))/2
# p_t = frfits.tau_fr(row.tPt)
# return ((p_m + p_e*(1 - p_m) + p_t*(1 - p_m)*(1 - p_e)), weight)
#
#def log_prob(row, weight):
# prob, weight = f_prob(row, weight)
# return math.log(prob), weight
#self.hfunc['faking_prob'] = f_prob
#self.hfunc['log_prob'] = log_prob
#self.hfunc["subMass#faking_prob"] = merge_functions( sub_mass, f_prob )
#self.hfunc["subMass#log_prob" ] = merge_functions( sub_mass, log_prob)
self.hfunc["subMass#LT" ] = merge_functions( sub_mass, attr_getter('LT'))
self.hfunc["subMass#tPt"] = merge_functions( sub_mass, attr_getter('tPt'))
#self.hfunc["subMass*#faking_prob"] = merge_functions( mass_scaler( sub_mass ), f_prob )
#self.hfunc["subMass*#log_prob" ] = merge_functions( mass_scaler( sub_mass ), log_prob)
self.hfunc["subMass*#LT" ] = merge_functions( mass_scaler( sub_mass ), attr_getter('LT'))
self.hfunc["subMass*#tPt"] = merge_functions( mass_scaler( sub_mass ), attr_getter('tPt'))
#maps the name of non-trivial histograms to a function to get the proper value, the function MUST have two args (evt and weight). Used in WHAnalyzerBase.fill_histos later
self.hfunc['subMass'] = sub_mass
self.hfunc['tLeadDR'] = lambda row, weight: (row.m_t_DR, weight) if row.ePt < row.mPt else (row.e_t_DR, weight)
self.hfunc['tSubDR'] = lambda row, weight: (row.e_t_DR, weight) if row.ePt < row.mPt else (row.m_t_DR, weight)
self.hfunc["subPt"] = lambda row, weight: (row.ePt, weight) if row.ePt < row.mPt else (row.mPt, weight)
self.hfunc["leadPt"] = lambda row, weight: (row.mPt, weight) if row.ePt < row.mPt else (row.ePt, weight)
self.hfunc["subJetPt"] = lambda row, weight: (row.eJetPt, weight) if row.ePt < row.mPt else (row.mJetPt, weight)
self.hfunc["leadJetPt"] = lambda row, weight: (row.mJetPt, weight) if row.ePt < row.mPt else (row.eJetPt, weight)
self.hfunc['pt_ratio' ] = lambda row, weight: (row.ePt/row.mPt, weight) if row.ePt < row.mPt else (row.mPt/row.ePt, weight)
self.hfunc["e*_t_Mass"] = lambda row, weight: ( frfits.default_scaler( row.e_t_Mass), weight)
self.hfunc["e*_m_Mass"] = lambda row, weight: ( frfits.default_scaler( row.e_m_Mass), weight)
self.hfunc["subMass*" ] = mass_scaler( sub_mass )
self.hfunc["_recoilDaught" ] = lambda row, weight: (math.sqrt(row.recoilDaught) , weight)
self.hfunc["_recoilWithMet"] = lambda row, weight: (math.sqrt(row.recoilWithMet), weight)
self.hfunc['SYNC'] = lambda row, weight: (row, None) #((row.run, row.lumi, row.evt, row.mPt, row.mEta, row.mPhi, row.ePt, row.eEta, row.ePhi, row.tPt, row.tEta, row.tPhi, weight), None )
self.pucorrector = mcCorrectors.make_puCorrector('mueg')
def f(row, weight):
val, w = fcn(row, weight)
return frfits.default_scaler(val), w
def f(row, weight):
val, w = fcn(row, weight)
res = val
if row.ePt < row.mPt:
res = frfits.default_scaler(val)
return res, w
def __init__(self, tree, outfile, **kwargs):
self.channel = 'EMT'
super(WHAnalyzeEMT, self).__init__(tree, outfile, EMuTauTree, **kwargs)
def attr_getter(attribute):
def f(row, weight):
return (getattr(row, attribute), weight)
return f
def mass_scaler(fcn):
def f(row, weight):
val, w = fcn(row, weight)
res = val
if row.ePt < row.mPt:
res = frfits.default_scaler(val)
return res, w
return f
def merge_functions(fcn_1, fcn_2):
def f(row, weight):
r1, w1 = fcn_1(row, weight)
r2, w2 = fcn_2(row, weight)
w = w1 if w1 == w2 else None
return ((r1, r2), w)
return f
def sub_mass(row, weight):
return (row.e_t_Mass,
weight) if row.ePt < row.mPt else (row.m_t_Mass, weight)
lead_iso = self.grid_search['']['leading_iso']
sublead_iso = self.grid_search['']['subleading_iso']
#def f_prob(row, weight):
# p_m = ( self.obj1_weight(row, lead_iso, sublead_iso) + \
# self.obj1_qcd_weight(row, lead_iso, sublead_iso))/2
# p_e = ( self.obj2_weight(row, lead_iso, sublead_iso) + \
# self.obj2_qcd_weight(row, lead_iso, sublead_iso))/2
# p_t = frfits.tau_fr(row.tPt)
# return ((p_m + p_e*(1 - p_m) + p_t*(1 - p_m)*(1 - p_e)), weight)
#
#def log_prob(row, weight):
# prob, weight = f_prob(row, weight)
# return math.log(prob), weight
#self.hfunc['faking_prob'] = f_prob
#self.hfunc['log_prob'] = log_prob
#self.hfunc["subMass#faking_prob"] = merge_functions( sub_mass, f_prob )
#self.hfunc["subMass#log_prob" ] = merge_functions( sub_mass, log_prob)
self.hfunc["subMass#LT"] = merge_functions(sub_mass, attr_getter('LT'))
self.hfunc["subMass#tPt"] = merge_functions(sub_mass,
attr_getter('tPt'))
#self.hfunc["subMass*#faking_prob"] = merge_functions( mass_scaler( sub_mass ), f_prob )
#self.hfunc["subMass*#log_prob" ] = merge_functions( mass_scaler( sub_mass ), log_prob)
self.hfunc["subMass*#LT"] = merge_functions(mass_scaler(sub_mass),
attr_getter('LT'))
self.hfunc["subMass*#tPt"] = merge_functions(mass_scaler(sub_mass),
attr_getter('tPt'))
#maps the name of non-trivial histograms to a function to get the proper value, the function MUST have two args (evt and weight). Used in WHAnalyzerBase.fill_histos later
self.hfunc['subMass'] = sub_mass
self.hfunc['tLeadDR'] = lambda row, weight: (
row.m_t_DR, weight) if row.ePt < row.mPt else (row.e_t_DR, weight)
self.hfunc['tSubDR'] = lambda row, weight: (
row.e_t_DR, weight) if row.ePt < row.mPt else (row.m_t_DR, weight)
self.hfunc["subPt"] = lambda row, weight: (
row.ePt, weight) if row.ePt < row.mPt else (row.mPt, weight)
self.hfunc["leadPt"] = lambda row, weight: (
row.mPt, weight) if row.ePt < row.mPt else (row.ePt, weight)
self.hfunc["subJetPt"] = lambda row, weight: (
row.eJetPt, weight) if row.ePt < row.mPt else (row.mJetPt, weight)
self.hfunc["leadJetPt"] = lambda row, weight: (
row.mJetPt, weight) if row.ePt < row.mPt else (row.eJetPt, weight)
self.hfunc['pt_ratio'] = lambda row, weight: (
row.ePt / row.mPt, weight) if row.ePt < row.mPt else (row.mPt / row
.ePt, weight)
self.hfunc["e*_t_Mass"] = lambda row, weight: (frfits.default_scaler(
row.e_t_Mass), weight)
self.hfunc["e*_m_Mass"] = lambda row, weight: (frfits.default_scaler(
row.e_m_Mass), weight)
self.hfunc["subMass*"] = mass_scaler(sub_mass)
self.hfunc["_recoilDaught"] = lambda row, weight: (math.sqrt(
row.recoilDaught), weight)
self.hfunc["_recoilWithMet"] = lambda row, weight: (math.sqrt(
row.recoilWithMet), weight)
self.hfunc['SYNC'] = lambda row, weight: (
row, None
) #((row.run, row.lumi, row.evt, row.mPt, row.mEta, row.mPhi, row.ePt, row.eEta, row.ePhi, row.tPt, row.tEta, row.tPhi, weight), None )
self.pucorrector = mcCorrectors.make_puCorrector('mueg')
