def __call__(self, features, **params):
p = ParamOverrides(self, params, allow_extra_keywords=True)
self.features = features
self._initialize_featureresponses(p)
self._measure_responses(p)
results = self._collate_results(p)
if p.measurement_storage_hook:
p.measurement_storage_hook(results)
return results
def __call__(self, features, **params):
"""
Present the given input patterns and collate the responses.
Responses are statistics on the distributions of measure for
every unit, extracted by functions that are subclasses of
DistributionStatisticFn, and could be specified in each
feature with the preference_fn parameter, otherwise the
default in self.preference_fn is used.
"""
p = ParamOverrides(self, params, allow_extra_keywords=True)
self.features = features
self._initialize_featureresponses(p)
self._measure_responses(p)
results = self._collate_results(p)
if p.measurement_storage_hook:
p.measurement_storage_hook(results)
return results
