def __init__(self,
n,
equations,
threshold,
reset=brian.NoReset(),
refractory=0 * ms,
implicit=False,
compile=True,
**parameters):
if "tau_refrac" in parameters:
max_refractory = parameters["tau_refrac"].max() * ms
else:
max_refractory = None
brian.NeuronGroup.__init__(self,
n,
model=equations,
threshold=threshold,
reset=reset,
refractory=refractory,
max_refractory=max_refractory,
compile=compile,
clock=simulator.state.network.clock,
max_delay=simulator.state.max_delay * ms,
implicit=implicit,
freeze=False)
for name, value in parameters.items():
setattr(self, name, value)
self._S0 = self._S[:, 0] # store parameter values in case of reset.
# TODO: update this when parameters are modified
self.initial_values = {}
def __init__(self, n, equations, spiketimes=None):
threshold = brian.directcontrol.MultipleSpikeGeneratorThreshold(
[st.value for st in spiketimes])
reset = brian.NoReset()
refractory = 0*ms
BaseNeuronGroup.__init__(self, n,
brian.LazyStateUpdater(),
threshold, reset, refractory,
spiketimes=spiketimes)
def __init__(self, n, equations, **parameters):
threshold = brian.PoissonThreshold()
reset = brian.NoReset()
refractory = 0*ms
BaseNeuronGroup.__init__(self, n,
brian.LazyStateUpdater(),
threshold, reset, refractory,
**parameters)
self.initialize()