def __init__(self, is_up, np=None, **kwargs):
# *** Set up the uncertainty tools ***
# Tag assumed: JetUncertainties-00-05-09-02
super(JES, self).__init__(is_up, **kwargs)
assert np in self.all_nps and hasattr(self, '_'+np)
self.np = np
self.run_np = getattr(self, '_' + np)
self.jes_tool = None
if self.year == 2011:
self.jes_tool = MultijetJESUncertaintyProvider(
"JES_2011/Final/MultijetJES_2011.config",
"JES_2011/Final/InsituJES2011_17NP_ByCategory.config",
"AntiKt4TopoLC",
"MC11c",
JetUncertainties.RESOURCE_PATH)
elif self.year == 2012:
self.jes_tool = MultijetJESUncertaintyProvider(
"JES_2012/Moriond2013/MultijetJES_2012.config",
#"JES_2012/Moriond2013/InsituJES2012_AllNuisanceParameters.config",
"JES_2012/Moriond2013/InsituJES2012_20NP_ByCategory.config",
"AntiKt4TopoLC",
"MC12a",
JetUncertainties.RESOURCE_PATH)
else:
raise ValueError('No JES defined for year %d' % year)
def __init__(self, is_up, np=None, **kwargs):
# *** Set up the uncertainty tools ***
# Tag assumed: JetUncertainties-00-05-09-02
super(JES, self).__init__(is_up, **kwargs)
assert np in self.all_nps and hasattr(self, '_' + np)
self.np = np
self.run_np = getattr(self, '_' + np)
self.jes_tool = None
if self.year == 2011:
self.jes_tool = MultijetJESUncertaintyProvider(
"JES_2011/Final/MultijetJES_2011.config",
"JES_2011/Final/InsituJES2011_17NP_ByCategory.config",
"AntiKt4TopoLC", "MC11c", JetUncertainties.RESOURCE_PATH)
elif self.year == 2012:
self.jes_tool = MultijetJESUncertaintyProvider(
"JES_2012/Moriond2013/MultijetJES_2012.config",
#"JES_2012/Moriond2013/InsituJES2012_AllNuisanceParameters.config",
"JES_2012/Moriond2013/InsituJES2012_20NP_ByCategory.config",
"AntiKt4TopoLC",
"MC12a",
JetUncertainties.RESOURCE_PATH)
else:
raise ValueError('No JES defined for year %d' % year)
class JES(JetSystematic):
# All 14 NPs in the 2013 recommendation
all_nps = [
'Statistical',
'Modelling',
'Detector',
'Mixed',
'EtaModelling',
'EtaMethod',
'PURho',
'PUPt',
'PUNPV',
'PUMu',
'FlavComp',
'FlavResp',
'BJet',
'NonClosure',
]
def __init__(self, is_up, np=None, **kwargs):
# *** Set up the uncertainty tools ***
# Tag assumed: JetUncertainties-00-05-09-02
super(JES, self).__init__(is_up, **kwargs)
assert np in self.all_nps and hasattr(self, '_'+np)
self.np = np
self.run_np = getattr(self, '_' + np)
self.jes_tool = None
if self.year == 2011:
self.jes_tool = MultijetJESUncertaintyProvider(
"JES_2011/Final/MultijetJES_2011.config",
"JES_2011/Final/InsituJES2011_17NP_ByCategory.config",
"AntiKt4TopoLC",
"MC11c",
JetUncertainties.RESOURCE_PATH)
elif self.year == 2012:
self.jes_tool = MultijetJESUncertaintyProvider(
"JES_2012/Moriond2013/MultijetJES_2012.config",
#"JES_2012/Moriond2013/InsituJES2012_AllNuisanceParameters.config",
"JES_2012/Moriond2013/InsituJES2012_20NP_ByCategory.config",
"AntiKt4TopoLC",
"MC12a",
JetUncertainties.RESOURCE_PATH)
else:
raise ValueError('No JES defined for year %d' % year)
def _Statistical(self, jet, event):
# HACK: use only stat1 for now
uncs = [0.]
#for i in range(3):
uncs[0] = self.jes_tool.getRelUncertComponent(
"EffectiveNP_Statistical1", jet.pt, jet.eta)
return uncs
def _Modelling(self, jet, event):
# HACK: use only modelling1 for now
uncs = [0.]
#for i in range(4):
uncs[0] = self.jes_tool.getRelUncertComponent(
"EffectiveNP_Modelling1", jet.pt, jet.eta)
return uncs
def _Detector(self, jet, event):
# HACK: use only detector1 for now
uncs = [0.]
#for i in range(3):
uncs[0] = self.jes_tool.getRelUncertComponent(
"EffectiveNP_Detector1", jet.pt, jet.eta)
return uncs
def _Mixed(self, jet, event):
uncs = [0., 0.]
for i in range(2):
uncs[i] = self.jes_tool.getRelUncertComponent("EffectiveNP_Mixed%d" % (i+1), jet.pt, jet.eta)
return uncs
def _EtaModelling(self, jet, event):
return [ self.jes_tool.getRelUncertComponent("EtaIntercalibration_Modelling", jet.pt, jet.eta) ]
def _EtaMethod(self, jet, event):
return [ self.jes_tool.getRelUncertComponent("EtaIntercalibration_StatAndMethod", jet.pt, jet.eta) ]
def _PURho(self, jet, event):
return [ self.jes_tool.getRelPileupRhoTopology(jet.pt, jet.eta) ]
def _PUPt(self, jet, event):
return [ self.jes_tool.getRelPileupPtTerm(jet.pt, jet.eta, self.tree.nvtxjets, event.averageIntPerXing) ]
def _PUNPV(self, jet, event):
return [ self.jes_tool.getRelNPVOffsetTerm(jet.pt, jet.eta, self.tree.nvtxjets) ]
def _PUMu(self, jet, event):
return [ self.jes_tool.getRelMuOffsetTerm(jet.pt, jet.eta, event.averageIntPerXing) ]
def _FlavComp(self, jet, event):
uncs = [0.]
is_b = jet.flavor_truth_dRminToB < 0.4
if not is_b:
uncs[0] = self.jes_tool.getRelFlavorCompUncert(jet.pt, jet.eta, True)
return uncs
def _FlavResp(self, jet, event):
uncs = [0.]
is_b = jet.flavor_truth_dRminToB < 0.4
if not is_b:
uncs[0] = self.jes_tool.getRelFlavorResponseUncert(jet.pt, jet.eta)
return uncs
def _BJet(self, jet, event):
uncs = [0.]
is_b = jet.flavor_truth_dRminToB < 0.4
if not is_b:
uncs[0] = self.jes_tool.getRelBJESUncert(jet.pt, jet.eta)
return uncs
def _NonClosure(self, jet, event):
uncs = [0., 0.]
uncs[0] = self.jes_tool.getRelUncertComponent("SingleParticle_HighPt", jet.pt, jet.eta)
uncs[1] = self.jes_tool.getRelUncertComponent("RelativeNonClosure_Pythia8", jet.pt, jet.eta)
# TODO: If AFII, use "RelativeNonClosure_AFII" instead
return uncs
@JetSystematic.set
def run(self, jet, event):
# Safest to assume nothing about the uncertainties on soft jets.
# These will go into SoftJets anyhow, and so the JES systematics
# aren't used.
shift = 0.
# OLD 2011 code
#if self.year == 2011:
# if jet.pt > 20e3 and jet.pt < 7000e3 and abs(jet.eta) < 4.5:
#
# # delta R cut needed to apply close-by jets uncertainty
# drmin=9999
# for otherjet in event.jets:
# if otherjet.emscale_pt > 7000:
# if jet.index != otherjet.index:
# dr = utils.dR(jet.eta, jet.phi,
# otherjet.eta,
# otherjet.phi)
# if dr < drmin:
# drmin = dr
#
# # TODO: shift is symmetric (is_up argument is not needed)
# if self.is_up:
# shift = self.jes_tool.getRelUncert(
# jet.pt,
# jet.eta,
# drmin,
# True, # is up
# self.sys_util.nvtxjets,
# event.averageIntPerXing,
# False) # is b jet
# else:
# shift = -1 * self.jes_tool.getRelUncert(
# jet.pt,
# jet.eta,
# drmin,
# False, # is up
# self.sys_util.nvtxjets,
# event.averageIntPerXing,
# False) # is b jet
if jet.pt > 15e3 and jet.pt < 7000e3 and abs(jet.eta) < 4.5:
uncs = self.run_np(jet, event)
if len(uncs) > 1:
unc = 0.
for u in uncs:
unc += u**2.
unc = unc**0.5
else:
unc = uncs[0]
if abs(max(uncs)) < abs(min(uncs)):
unc = -unc; # set total to sign of max
if self.is_up:
shift = unc;
else:
shift = -unc;
jet.pt *= 1. + shift
class JES(JetSystematic):
# All 14 NPs in the 2013 recommendation
all_nps = [
'Statistical',
'Modelling',
'Detector',
'Mixed',
'EtaModelling',
'EtaMethod',
'PURho',
'PUPt',
'PUNPV',
'PUMu',
'FlavComp',
'FlavResp',
'BJet',
'NonClosure',
]
def __init__(self, is_up, np=None, **kwargs):
# *** Set up the uncertainty tools ***
# Tag assumed: JetUncertainties-00-05-09-02
super(JES, self).__init__(is_up, **kwargs)
assert np in self.all_nps and hasattr(self, '_' + np)
self.np = np
self.run_np = getattr(self, '_' + np)
self.jes_tool = None
if self.year == 2011:
self.jes_tool = MultijetJESUncertaintyProvider(
"JES_2011/Final/MultijetJES_2011.config",
"JES_2011/Final/InsituJES2011_17NP_ByCategory.config",
"AntiKt4TopoLC", "MC11c", JetUncertainties.RESOURCE_PATH)
elif self.year == 2012:
self.jes_tool = MultijetJESUncertaintyProvider(
"JES_2012/Moriond2013/MultijetJES_2012.config",
#"JES_2012/Moriond2013/InsituJES2012_AllNuisanceParameters.config",
"JES_2012/Moriond2013/InsituJES2012_20NP_ByCategory.config",
"AntiKt4TopoLC",
"MC12a",
JetUncertainties.RESOURCE_PATH)
else:
raise ValueError('No JES defined for year %d' % year)
def _Statistical(self, jet, event):
# HACK: use only stat1 for now
uncs = [0.]
#for i in range(3):
uncs[0] = self.jes_tool.getRelUncertComponent(
"EffectiveNP_Statistical1", jet.pt, jet.eta)
return uncs
def _Modelling(self, jet, event):
# HACK: use only modelling1 for now
uncs = [0.]
#for i in range(4):
uncs[0] = self.jes_tool.getRelUncertComponent("EffectiveNP_Modelling1",
jet.pt, jet.eta)
return uncs
def _Detector(self, jet, event):
# HACK: use only detector1 for now
uncs = [0.]
#for i in range(3):
uncs[0] = self.jes_tool.getRelUncertComponent("EffectiveNP_Detector1",
jet.pt, jet.eta)
return uncs
def _Mixed(self, jet, event):
uncs = [0., 0.]
for i in range(2):
uncs[i] = self.jes_tool.getRelUncertComponent(
"EffectiveNP_Mixed%d" % (i + 1), jet.pt, jet.eta)
return uncs
def _EtaModelling(self, jet, event):
return [
self.jes_tool.getRelUncertComponent(
"EtaIntercalibration_Modelling", jet.pt, jet.eta)
]
def _EtaMethod(self, jet, event):
return [
self.jes_tool.getRelUncertComponent(
"EtaIntercalibration_StatAndMethod", jet.pt, jet.eta)
]
def _PURho(self, jet, event):
return [self.jes_tool.getRelPileupRhoTopology(jet.pt, jet.eta)]
def _PUPt(self, jet, event):
return [
self.jes_tool.getRelPileupPtTerm(jet.pt, jet.eta,
self.tree.nvtxjets,
event.averageIntPerXing)
]
def _PUNPV(self, jet, event):
return [
self.jes_tool.getRelNPVOffsetTerm(jet.pt, jet.eta,
self.tree.nvtxjets)
]
def _PUMu(self, jet, event):
return [
self.jes_tool.getRelMuOffsetTerm(jet.pt, jet.eta,
event.averageIntPerXing)
]
def _FlavComp(self, jet, event):
uncs = [0.]
is_b = jet.flavor_truth_dRminToB < 0.4
if not is_b:
uncs[0] = self.jes_tool.getRelFlavorCompUncert(
jet.pt, jet.eta, True)
return uncs
def _FlavResp(self, jet, event):
uncs = [0.]
is_b = jet.flavor_truth_dRminToB < 0.4
if not is_b:
uncs[0] = self.jes_tool.getRelFlavorResponseUncert(jet.pt, jet.eta)
return uncs
def _BJet(self, jet, event):
uncs = [0.]
is_b = jet.flavor_truth_dRminToB < 0.4
if not is_b:
uncs[0] = self.jes_tool.getRelBJESUncert(jet.pt, jet.eta)
return uncs
def _NonClosure(self, jet, event):
uncs = [0., 0.]
uncs[0] = self.jes_tool.getRelUncertComponent("SingleParticle_HighPt",
jet.pt, jet.eta)
uncs[1] = self.jes_tool.getRelUncertComponent(
"RelativeNonClosure_Pythia8", jet.pt, jet.eta)
# TODO: If AFII, use "RelativeNonClosure_AFII" instead
return uncs
@JetSystematic.set
def run(self, jet, event):
# Safest to assume nothing about the uncertainties on soft jets.
# These will go into SoftJets anyhow, and so the JES systematics
# aren't used.
shift = 0.
# OLD 2011 code
#if self.year == 2011:
# if jet.pt > 20e3 and jet.pt < 7000e3 and abs(jet.eta) < 4.5:
#
# # delta R cut needed to apply close-by jets uncertainty
# drmin=9999
# for otherjet in event.jets:
# if otherjet.emscale_pt > 7000:
# if jet.index != otherjet.index:
# dr = utils.dR(jet.eta, jet.phi,
# otherjet.eta,
# otherjet.phi)
# if dr < drmin:
# drmin = dr
#
# # TODO: shift is symmetric (is_up argument is not needed)
# if self.is_up:
# shift = self.jes_tool.getRelUncert(
# jet.pt,
# jet.eta,
# drmin,
# True, # is up
# self.sys_util.nvtxjets,
# event.averageIntPerXing,
# False) # is b jet
# else:
# shift = -1 * self.jes_tool.getRelUncert(
# jet.pt,
# jet.eta,
# drmin,
# False, # is up
# self.sys_util.nvtxjets,
# event.averageIntPerXing,
# False) # is b jet
if jet.pt > 15e3 and jet.pt < 7000e3 and abs(jet.eta) < 4.5:
uncs = self.run_np(jet, event)
if len(uncs) > 1:
unc = 0.
for u in uncs:
unc += u**2.
unc = unc**0.5
else:
unc = uncs[0]
if abs(max(uncs)) < abs(min(uncs)):
unc = -unc
# set total to sign of max
if self.is_up:
shift = unc
else:
shift = -unc
jet.pt *= 1. + shift
