def _compute_outputs(self, inputs=None):
"""Apply basic cuts and compute histograms for output channels."""
logging.debug('Entering events_to_data._compute_outputs')
#Hashing
#TODO What should I hash??
hash_property = [
self.events_file, self.params['dataset'].value, self.output_names
]
this_hash = hash_obj(hash_property, full_hash=self.full_hash)
#if this_hash == self.sample_hash: #TODO Fix this and replace...
# return
#TODO Check there are no inputs
#Fill an events instance from a file
events = Events(self.events_file)
#TODO Handle nominal, etc, etc datasets?
#Extract the neutrino data from the 'Events' instance
nu_data = []
flav_fidg = FlavIntDataGroup(flavint_groups=events.flavints)
for flavint in events.present_flavints:
flav_fidg[flavint] = {
var: events[flavint][var]
for var in events[flavint].keys()
}
nu_data.append(flav_fidg)
#Create the data instance, including the metadata
#Note that there is no muon or noise data in the 'Events'
data = Data(reduce(add, nu_data), metadata=deepcopy(events.metadata))
#Make cuts
if self.params['keep_criteria'].value is not None:
self._data.applyCut(self.params['keep_criteria'].value
) #TODO Shivesh says this needs testing
self._data.update_hash()
#Update hashes
self.sample_hash = this_hash
data.metadata['sample_hash'] = this_hash
data.update_hash()
return data
def load_from_nu_file(events_file, all_flavints, weight, weight_units,
keep_keys, aliases):
flav_fidg = FlavIntDataGroup(flavint_groups=all_flavints)
events = from_file(events_file)
sample.strip_keys(keep_keys, events)
nu_mask = events['ptype'] > 0
nubar_mask = events['ptype'] < 0
cc_mask = events['interaction'] == 1
nc_mask = events['interaction'] == 2
if weight == 'None' or weight == '1':
events['sample_weight'] = \
np.ones(events['ptype'].shape) * ureg.dimensionless
elif weight == '0':
events['sample_weight'] = \
np.zeros(events['ptype'].shape) * ureg.dimensionless
else:
events['sample_weight'] = events[weight] * \
ureg(weight_units)
events['pisa_weight'] = deepcopy(events['sample_weight'])
for alias, expr in aliases:
if alias in events:
logging.warning(
'Overwriting Data key {0} with aliased expression '
'{1}'.format(alias, expr))
events[alias] = eval(re.sub(r'\<(.*?)\>', r"events['\1']", expr))
for flavint in all_flavints:
i_mask = cc_mask if flavint.cc else nc_mask
t_mask = nu_mask if flavint.particle else nubar_mask
flav_fidg[flavint] = {
var: events[var][i_mask & t_mask]
for var in events.iterkeys()
}
return flav_fidg
def __add__(self, other):
muons = None
noise = None
assert isinstance(other, Data)
metadata = {}
for key in self.metadata:
if key == 'flavints_joined':
continue
if key in other.metadata:
if self.metadata[key] != other.metadata[key]:
raise AssertionError('Metadata mismatch, key {0}, {1} != '
'{2}'.format(key, self.metadata[key],
other.metadata[key]))
else:
metadata[key] = deepcopy(self.metadata[key])
else:
metadata[key] = deepcopy(self.metadata[key])
for key in other.metadata:
if key == 'flavints_joined':
continue
if key in self.metadata:
if other.metadata[key] != self.metadata[key]:
raise AssertionError('Metadata mismatch, key {0}, {1} != '
'{2}'.format(key, other.metadata[key],
self.metadata[key]))
else:
metadata[key] = deepcopy(other.metadata[key])
else:
metadata[key] = deepcopy(other.metadata[key])
if self.contains_muons:
if other.contains_muons:
muons = self._merge(deepcopy(self['muons']), other['muons'])
else:
muons = deepcopy(self['muons'])
elif other.contains_muons:
muons = deepcopy(other['muons'])
if self.contains_noise:
if other.contains_noise:
noise = self._merge(deepcopy(self['noise']), other['noise'])
else:
noise = deepcopy(self['noise'])
elif other.contains_noise:
noise = deepcopy(other['noise'])
if len(self.flavint_groups) == 0:
if len(other.flavint_groups) == 0:
a_fidg = FlavIntDataGroup(other)
elif len(other.flavint_groups) == 0:
a_fidg = FlavIntDataGroup(self)
else:
a_fidg = super(Data, self).__add__(other)
metadata['flavints_joined'] = [str(f) for f in a_fidg.flavint_groups]
if muons is not None:
a_dict = dict(a_fidg)
metadata['flavints_joined'] += ['muons']
a_dict['muons'] = muons
a_fidg = a_dict
if noise is not None:
a_dict = dict(a_fidg)
metadata['flavints_joined'] += ['noise']
a_dict['noise'] = noise
a_fidg = a_dict
return Data(a_fidg, metadata=metadata)