def __init__(self):
EDM.__init__(self)
# force this class to hold some extra params to read the external information
# into a root file. This is call by metadata information. Usually, this metadata
# is stored into the same basepath as the main ttree (event).
self._useMetadataParams = True
# the name of the ttree metadata where is stored the information
# do not change is name.
self._metadataName = 'tdt'
# decision core (default)
self._core = DecisionCore.TriggerDecisionTool
def __init__(self):
EDM.__init__(self)
# Detector ROI dimesions:
# |--------- EM ----------|----------- HAD ----------|
# 15cm 30cm 3cm 40cm 40cm 20cm
# + +--------------------------------------------------+
# | | | | | | | |
# 48cm | | | | | | |
# | | | | | | | |
# + +--------------------------------------------------+
# Eletromagnetic layers
self._first_em_sampling = NotSet
self._second_em_sampling = NotSet
self._third_em_sampling = NotSet
# Hadronic layers
self._first_had_sampling = NotSet
self._second_had_sampling = NotSet
self._third_had_sampling = NotSet
def __init__(self):
self._elCand = 2
EDM.__init__(self)
def __init__(self):
EDM.__init__(self)
def __init__(self, **kw):
EDM.__init__(self)
self.__dict__.update(
('_' + k, v) for k, v in kw.items() if k in self.__allow_keys)
def __init__(self):
EDM.__init__(self)
self._nrings = [46, 5, 5, 4, 4, 2] # 86 rings
self._ringsE = [0.0 for _ in range(sum(self._nrings))]