def check_all_validated(self): ''' Checks that all preferences that have been set have been validated. Logs a warning if not. Should be called by `Network.run` or other key angela functions. ''' if len(self.prefs_unvalidated): from angela2.utils.logger import get_logger logger = get_logger(__name__) logger.warn("The following preferences values have been set but " "are not registered preferences:\n%s\nThis is usually " "because of a spelling mistake or missing library " "import." % ', '.join(self.prefs_unvalidated), once=True)
raise ImportError("angela2.hears is deprecated and will be removed in a future release, please use the angela2hears " "package available at https://angela2hears.readthedocs.io/. If you really want to keep " "using it, note: angela2.hears is a bridge between angela 2 and the version of angela Hears from " "angela 1, you need to have angela 1 installed to use it.") from angela2.core.clocks import Clock from angela2.core.operations import network_operation from angela2.groups.neurongroup import NeuronGroup from angela2.utils.logger import get_logger from angela2.units.fundamentalunits import Quantity from angela2.units import second from numpy import asarray, array, ndarray from inspect import isclass, ismethod logger = get_logger(__name__) logger.warn("angela2.hears is deprecated and will be removed in a future release, please use the angela2hears " "package available at https://angela2hears.readthedocs.io/. If you really want to keep using it, note " "that it is a bridge between angela 2 and angela Hears from angela 1. " "This is not guaranteed to work in all cases that angela.hears works. " "See the limitations in the online documentation.") def convert_unit_b1_to_b2(val): return Quantity.with_dimensions(float(val), arg.dim._dims) def convert_unit_b2_to_b1(val): return b1.Quantity.with_dimensions(float(val), arg.dim._dims) def modify_arg(arg):