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):
