def apply_function(self):
'''Cf. `PiStage` docs.'''
# TODO: do we need following line? Isn't this handled universally
# by the base class (in PiStage's apply)?
self.data.data_specs = self.output_specs
# reset weights to initial weights prior to downstream stages running
for container in self.data:
vectorizer.assign(container['initial_weights'], out=container['weights'])
def setup_function(self):
"""Setup the stage"""
# set the correct data mode
self.data.data_specs = self.calc_specs
for container in self.data:
container['calculated_pid'] = np.empty((container.size), dtype=FTYPE)
container['original_pid'] = np.empty((container.size), dtype=FTYPE)
vectorizer.assign(vals=container['pid'], out=container['original_pid'])
def compute_function(self):
for container in self.data:
vectorizer.assign(vals=container["weights"],
out=container["manual_variance"])
vectorizer.scale(
vals=container["manual_variance"],
scale=self.variance_scale,
out=container["manual_variance"],
)
if self.divide_n:
vectorizer.scale(
vals=container["manual_variance"],
scale=self.expected_total_mc /
self.total_mc[container.name],
out=container["manual_variance"],
)
if self.variance_floor is not None:
apply_floor(self.variance_floor,
out=container["manual_variance"])
def apply_function(self):
for container in self.data:
# set the pid value to the calculated one
vectorizer.assign(vals=container['calculated_pid'], out=container['pid'])
def compute_function(self):
for container in self.data:
vectorizer.assign(vals=container["errors"], out=container["frozen_errors"])
container['frozen_errors'].mark_changed(WHERE)
def apply_function(self):
for container in self.data:
vectorizer.assign(vals=container['frozen_errors'], out=container['errors'])
container['errors'].mark_changed(WHERE)
def apply_function(self):
# reset weights
for container in self.data:
vectorizer.assign(container['initial_weights'], out=container['weights'])