def user_SetParameter(self, parameter, value, datasets, level):
# algorithm
if parameter == "algorithm":
# Switch off the clustering
if value == "none":
test = True
for dataset in datasets:
if not test:
break
for file in dataset.filenames:
if file.endswith('lhe') or \
file.endswith('lhe.gz') or \
file.endswith('hep') or \
file.endswith('hep.gz') or \
file.endswith('hepmc') or \
file.endswith('hepmc.gz'):
test = False
break
if not test:
logging.getLogger('MA5').error(
"some datasets contain partonic/hadronic file format. Clustering algorithm cannot be switched off."
)
return
# Switch on the clustering
elif value in ["kt","antikt","cambridge","genkt",\
"gridjet","cdfmidpoint","cdfjetclu",\
"siscone"]:
# Only in reco mode
if level != MA5RunningType.RECO:
logging.getLogger('MA5').error(
"clustering algorithm is only available in RECO mode")
return
test = True
for dataset in datasets:
if not test:
break
for file in dataset.filenames:
if file.endswith('lhco') or \
file.endswith('lhco.gz') or \
file.endswith('root'):
test = False
break
if not test:
logging.getLogger('MA5').error(
"some datasets contain reconstructed file format. Clustering algorithm cannot be switched on."
)
return
if value == "kt":
self.algorithm = "kt"
self.clustering = ClusteringKt()
elif value == "antikt":
self.algorithm = "antikt"
self.clustering = ClusteringAntiKt()
elif value == "cambridge":
self.algorithm = "cambridge"
self.clustering = ClusteringCambridge()
elif value == "genkt":
self.algorithm = "genkt"
self.clustering = ClusteringGenKt()
elif value == "gridjet":
self.algorithm = "gridjet"
self.clustering = ClusteringGridJet()
elif value == "cdfmidpoint":
self.algorithm = "cdfmidpoint"
self.clustering = ClusteringCDFMidPoint()
elif value == "cdfjetclu":
self.algorithm = "cdfjetclu"
self.clustering = ClusteringCDFJetClu()
elif value == "siscone":
self.algorithm = "siscone"
self.clustering = ClusteringSisCone()
elif value == "none":
self.algorithm = "none"
self.clustering = 0
else:
logging.getLogger('MA5').error("algorithm called '" + value +
"' is not found.")
return
# other rejection if no algo specified
if self.algorithm == "none":
logging.getLogger('MA5').error(
"'clustering' has no parameter called '" + parameter + "'")
return
# exclusive_id
if parameter == "exclusive_id":
if value == "true":
self.exclusive_id = True
elif value == "false":
self.exclusive_id = False
else:
logging.getLogger('MA5').error("The allowed values for 'exclusive_id' " +\
"parameter are 'true' or 'false'.")
return
# other
elif parameter.startswith('bjet_id.'):
return self.beauty.user_SetParameter(parameter, value)
elif parameter.startswith('tau_id.'):
return self.tau.user_SetParameter(parameter, value)
else:
return self.clustering.user_SetParameter(parameter, value)
def __init__(self):
self.algorithm = "antikt"
self.clustering = ClusteringAntiKt()
self.beauty = BeautyIdentification()
self.tau = TauIdentification()
self.exclusive_id = True
class ClusteringConfiguration:
userVariables = { "algorithm" : ["kt","antikt","genkt",\
"cambridge","gridjet",\
"siscone",\
"cdfjetclu", "cdfmidpoint",\
"none"],
"exclusive_id" : ["true","false"]
}
def __init__(self):
self.algorithm = "antikt"
self.clustering = ClusteringAntiKt()
self.beauty = BeautyIdentification()
self.tau = TauIdentification()
self.exclusive_id = True
def Display(self):
self.user_DisplayParameter("algorithm")
if self.algorithm != "none":
self.clustering.Display()
self.user_DisplayParameter("exclusive_id")
self.beauty.Display()
self.tau.Display()
def user_DisplayParameter(self, parameter):
if parameter == "algorithm":
logging.getLogger('MA5').info(" clustering algorithm : " +
self.algorithm)
return
if self.algorithm != "none":
if parameter == "exclusive_id":
word = ""
if self.exclusive_id:
word = "true"
else:
word = "false"
logging.getLogger('MA5').info(
" + exclusive identification = " + word)
elif parameter.startswith('bjet_id.'):
self.beauty.user_DisplayParameter(parameter)
elif parameter.startswith('tau_id.'):
self.tau.user_DisplayParameter(parameter)
else:
self.clustering.user_DisplayParameter(parameter)
def SampleAnalyzerConfigString(self):
if self.algorithm != "none":
mydict = {}
if self.exclusive_id:
mydict['exclusive_id'] = '1'
else:
mydict['exclusive_id'] = '0'
mydict.update(self.clustering.SampleAnalyzerConfigString())
mydict.update(self.beauty.SampleAnalyzerConfigString())
mydict.update(self.tau.SampleAnalyzerConfigString())
return mydict
else:
return {}
def user_SetParameter(self, parameter, value, datasets, level):
# algorithm
if parameter == "algorithm":
# Switch off the clustering
if value == "none":
test = True
for dataset in datasets:
if not test:
break
for file in dataset.filenames:
if file.endswith('lhe') or \
file.endswith('lhe.gz') or \
file.endswith('hep') or \
file.endswith('hep.gz') or \
file.endswith('hepmc') or \
file.endswith('hepmc.gz'):
test = False
break
if not test:
logging.getLogger('MA5').error(
"some datasets contain partonic/hadronic file format. Clustering algorithm cannot be switched off."
)
return
# Switch on the clustering
elif value in ["kt","antikt","cambridge","genkt",\
"gridjet","cdfmidpoint","cdfjetclu",\
"siscone"]:
# Only in reco mode
if level != MA5RunningType.RECO:
logging.getLogger('MA5').error(
"clustering algorithm is only available in RECO mode")
return
test = True
for dataset in datasets:
if not test:
break
for file in dataset.filenames:
if file.endswith('lhco') or \
file.endswith('lhco.gz') or \
file.endswith('root'):
test = False
break
if not test:
logging.getLogger('MA5').error(
"some datasets contain reconstructed file format. Clustering algorithm cannot be switched on."
)
return
if value == "kt":
self.algorithm = "kt"
self.clustering = ClusteringKt()
elif value == "antikt":
self.algorithm = "antikt"
self.clustering = ClusteringAntiKt()
elif value == "cambridge":
self.algorithm = "cambridge"
self.clustering = ClusteringCambridge()
elif value == "genkt":
self.algorithm = "genkt"
self.clustering = ClusteringGenKt()
elif value == "gridjet":
self.algorithm = "gridjet"
self.clustering = ClusteringGridJet()
elif value == "cdfmidpoint":
self.algorithm = "cdfmidpoint"
self.clustering = ClusteringCDFMidPoint()
elif value == "cdfjetclu":
self.algorithm = "cdfjetclu"
self.clustering = ClusteringCDFJetClu()
elif value == "siscone":
self.algorithm = "siscone"
self.clustering = ClusteringSisCone()
elif value == "none":
self.algorithm = "none"
self.clustering = 0
else:
logging.getLogger('MA5').error("algorithm called '" + value +
"' is not found.")
return
# other rejection if no algo specified
if self.algorithm == "none":
logging.getLogger('MA5').error(
"'clustering' has no parameter called '" + parameter + "'")
return
# exclusive_id
if parameter == "exclusive_id":
if value == "true":
self.exclusive_id = True
elif value == "false":
self.exclusive_id = False
else:
logging.getLogger('MA5').error("The allowed values for 'exclusive_id' " +\
"parameter are 'true' or 'false'.")
return
# other
elif parameter.startswith('bjet_id.'):
return self.beauty.user_SetParameter(parameter, value)
elif parameter.startswith('tau_id.'):
return self.tau.user_SetParameter(parameter, value)
else:
return self.clustering.user_SetParameter(parameter, value)
def user_GetParameters(self):
if self.algorithm != "none":
table = ClusteringConfiguration.userVariables.keys()
table.extend(self.clustering.user_GetParameters())
table.extend(self.beauty.user_GetParameters())
table.extend(self.tau.user_GetParameters())
else:
table = ["algorithm"]
return table
def user_GetValues(self, variable):
table = []
if self.algorithm != "none":
try:
table.extend(ClusteringConfiguration.userVariables[variable])
except:
pass
try:
table.extend(self.clustering.user_GetValues(variable))
except:
pass
try:
table.extend(self.beauty.user_GetValues(variable))
except:
pass
try:
table.extend(self.tau.user_GetValues(variable))
except:
pass
else:
if variable == "algorithm":
table.extend(
ClusteringConfiguration.userVariables["algorithm"])
return table
def user_SetParameter(self,parameter,value,datasets,level):
# algorithm
if parameter=="algorithm":
# Switch off the clustering
if value=="none":
test=True
for dataset in datasets:
if not test:
break
for file in dataset.filenames:
if file.endswith('lhe') or \
file.endswith('lhe.gz') or \
file.endswith('hep') or \
file.endswith('hep.gz') or \
file.endswith('hepmc') or \
file.endswith('hepmc.gz'):
test=False
break
if not test:
logging.error("some datasets contain partonic/hadronic file format. Clustering algorithm cannot be switched off.")
return
# Switch on the clustering
elif value in ["kt","antikt","cambridge","genkt",\
"gridjet","cdfmidpoint","cdfjetclu",\
"siscone"]:
# Only in reco mode
if level!=MA5RunningType.RECO:
logging.error("clustering algorithm is only available in RECO mode")
return
test=True
for dataset in datasets:
if not test:
break
for file in dataset.filenames:
if file.endswith('lhco') or \
file.endswith('lhco.gz') or \
file.endswith('root'):
test=False
break
if not test:
logging.error("some datasets contain reconstructed file format. Clustering algorithm cannot be switched on.")
return
if value=="kt":
self.algorithm="kt"
self.clustering = ClusteringKt()
elif value=="antikt":
self.algorithm="antikt"
self.clustering = ClusteringAntiKt()
elif value=="cambridge":
self.algorithm="cambridge"
self.clustering = ClusteringCambridge()
elif value=="genkt":
self.algorithm="genkt"
self.clustering = ClusteringGenKt()
elif value=="gridjet":
self.algorithm="gridjet"
self.clustering = ClusteringGridJet()
elif value=="cdfmidpoint":
self.algorithm="cdfmidpoint"
self.clustering = ClusteringCDFMidPoint()
elif value=="cdfjetclu":
self.algorithm="cdfjetclu"
self.clustering = ClusteringCDFJetClu()
elif value=="siscone":
self.algorithm="siscone"
self.clustering = ClusteringSisCone()
elif value=="none":
self.algorithm="none"
self.clustering = 0
else:
logging.error("algorithm called '"+value+"' is not found.")
return
# other rejection if no algo specified
if self.algorithm=="none":
logging.error("'clustering' has no parameter called '"+parameter+"'")
return
# exclusive_id
if parameter=="exclusive_id":
if value=="true":
self.exclusive_id=True
elif value=="false":
self.exclusive_id=False
else:
logging.error("The allowed values for 'exclusive_id' " +\
"parameter are 'true' or 'false'.")
return
# other
elif parameter.startswith('bjet_id.'):
return self.beauty.user_SetParameter(parameter,value)
elif parameter.startswith('tau_id.'):
return self.tau.user_SetParameter(parameter,value)
else:
return self.clustering.user_SetParameter(parameter,value)
def __init__(self):
self.algorithm = "antikt"
self.clustering = ClusteringAntiKt()
self.beauty = BeautyIdentification()
self.tau = TauIdentification()
self.exclusive_id = True
class ClusteringConfiguration:
userVariables = { "algorithm" : ["kt","antikt","genkt",\
"cambridge","gridjet",\
"siscone",\
"cdfjetclu", "cdfmidpoint",\
"none"],
"exclusive_id" : ["true","false"]
}
def __init__(self):
self.algorithm = "antikt"
self.clustering = ClusteringAntiKt()
self.beauty = BeautyIdentification()
self.tau = TauIdentification()
self.exclusive_id = True
def Display(self):
self.user_DisplayParameter("algorithm")
if self.algorithm!="none":
self.clustering.Display()
self.user_DisplayParameter("exclusive_id")
self.beauty.Display()
self.tau.Display()
def user_DisplayParameter(self,parameter):
if parameter=="algorithm":
logging.info(" clustering algorithm : "+self.algorithm)
return
if self.algorithm!="none":
if parameter=="exclusive_id":
word=""
if self.exclusive_id:
word="true"
else:
word="false"
logging.info(" + exclusive identification = "+word)
elif parameter.startswith('bjet_id.'):
self.beauty.user_DisplayParameter(parameter)
elif parameter.startswith('tau_id.'):
self.tau.user_DisplayParameter(parameter)
else:
self.clustering.user_DisplayParameter(parameter)
def SampleAnalyzerConfigString(self):
if self.algorithm!="none":
mydict = {}
if self.exclusive_id:
mydict['exclusive_id'] = '1'
else:
mydict['exclusive_id'] = '0'
mydict.update(self.clustering.SampleAnalyzerConfigString())
mydict.update(self.beauty.SampleAnalyzerConfigString())
mydict.update(self.tau.SampleAnalyzerConfigString())
return mydict
else:
return {}
def user_SetParameter(self,parameter,value,datasets,level):
# algorithm
if parameter=="algorithm":
# Switch off the clustering
if value=="none":
test=True
for dataset in datasets:
if not test:
break
for file in dataset.filenames:
if file.endswith('lhe') or \
file.endswith('lhe.gz') or \
file.endswith('hep') or \
file.endswith('hep.gz') or \
file.endswith('hepmc') or \
file.endswith('hepmc.gz'):
test=False
break
if not test:
logging.error("some datasets contain partonic/hadronic file format. Clustering algorithm cannot be switched off.")
return
# Switch on the clustering
elif value in ["kt","antikt","cambridge","genkt",\
"gridjet","cdfmidpoint","cdfjetclu",\
"siscone"]:
# Only in reco mode
if level!=MA5RunningType.RECO:
logging.error("clustering algorithm is only available in RECO mode")
return
test=True
for dataset in datasets:
if not test:
break
for file in dataset.filenames:
if file.endswith('lhco') or \
file.endswith('lhco.gz') or \
file.endswith('root'):
test=False
break
if not test:
logging.error("some datasets contain reconstructed file format. Clustering algorithm cannot be switched on.")
return
if value=="kt":
self.algorithm="kt"
self.clustering = ClusteringKt()
elif value=="antikt":
self.algorithm="antikt"
self.clustering = ClusteringAntiKt()
elif value=="cambridge":
self.algorithm="cambridge"
self.clustering = ClusteringCambridge()
elif value=="genkt":
self.algorithm="genkt"
self.clustering = ClusteringGenKt()
elif value=="gridjet":
self.algorithm="gridjet"
self.clustering = ClusteringGridJet()
elif value=="cdfmidpoint":
self.algorithm="cdfmidpoint"
self.clustering = ClusteringCDFMidPoint()
elif value=="cdfjetclu":
self.algorithm="cdfjetclu"
self.clustering = ClusteringCDFJetClu()
elif value=="siscone":
self.algorithm="siscone"
self.clustering = ClusteringSisCone()
elif value=="none":
self.algorithm="none"
self.clustering = 0
else:
logging.error("algorithm called '"+value+"' is not found.")
return
# other rejection if no algo specified
if self.algorithm=="none":
logging.error("'clustering' has no parameter called '"+parameter+"'")
return
# exclusive_id
if parameter=="exclusive_id":
if value=="true":
self.exclusive_id=True
elif value=="false":
self.exclusive_id=False
else:
logging.error("The allowed values for 'exclusive_id' " +\
"parameter are 'true' or 'false'.")
return
# other
elif parameter.startswith('bjet_id.'):
return self.beauty.user_SetParameter(parameter,value)
elif parameter.startswith('tau_id.'):
return self.tau.user_SetParameter(parameter,value)
else:
return self.clustering.user_SetParameter(parameter,value)
def user_GetParameters(self):
if self.algorithm!="none":
table = ClusteringConfiguration.userVariables.keys()
table.extend(self.clustering.user_GetParameters())
table.extend(self.beauty.user_GetParameters())
table.extend(self.tau.user_GetParameters())
else:
table = ["algorithm"]
return table
def user_GetValues(self,variable):
table = []
if self.algorithm!="none":
try:
table.extend(ClusteringConfiguration.userVariables[variable])
except:
pass
try:
table.extend(self.clustering.user_GetValues(variable))
except:
pass
try:
table.extend(self.beauty.user_GetValues(variable))
except:
pass
try:
table.extend(self.tau.user_GetValues(variable))
except:
pass
else:
if variable=="algorithm":
table.extend(ClusteringConfiguration.userVariables["algorithm"])
return table