def __init__(self, bg, neurons_action=50, threshold_action=0.2,
mutual_inhibit=1, route_inhibit=3,
synapse_inhibit=0.008, synapse_bg=0.008, synapse_direct=0.01,
neurons_channel_dim=50, subdim_channel=16,
synapse_channel=0.01,
neurons_cconv=200,
neurons_gate=40, threshold_gate=0.3, synapse_to_gate=0.002):
self.bg = bg
self.neurons_action = neurons_action
self.mutual_inhibit = mutual_inhibit
self.route_inhibit = route_inhibit
self.synapse_inhibit = synapse_inhibit
self.synapse_direct = synapse_direct
self.threshold_action = threshold_action
self.neurons_channel_dim = neurons_channel_dim
self.subdim_channel = subdim_channel
self.synapse_channel = synapse_channel
self.neurons_gate = neurons_gate
self.neurons_cconv = neurons_cconv
self.threshold_gate = threshold_gate
self.synapse_to_gate = synapse_to_gate
self.synapse_bg = synapse_bg
self.gates = {} # gating ensembles per action (created as needed)
self.channels = {} # channels to pass transformed data between modules
Module.__init__(self)
nengo.networks.Thalamus.__init__(
self, self.bg.actions.count,
n_neurons_per_ensemble=self.neurons_action,
mutual_inhib=self.mutual_inhibit,
threshold=self.threshold_action)
def __init__(self, actions, input_synapse=0.002,
label=None, seed=None, add_to_container=None):
self.actions = actions
self.input_synapse = input_synapse
self._bias = None
Module.__init__(self, label, seed, add_to_container)
nengo.networks.BasalGanglia(dimensions=self.actions.count, net=self)
def __init__(self, actions, input_synapse=0.002):
self.actions = actions
self.input_synapse = input_synapse
self._bias = None
Module.__init__(self)
nengo.networks.BasalGanglia.__init__(self,
dimensions=self.actions.count)
def __init__(self, bg, neurons_action=50, threshold_action=0.2,
mutual_inhibit=1.0, route_inhibit=3.0,
synapse_inhibit=0.008, synapse_bg=0.008, synapse_direct=0.01,
neurons_channel_dim=50, subdim_channel=16,
synapse_channel=0.01,
neurons_cconv=200,
neurons_gate=40, threshold_gate=0.3, synapse_to_gate=0.002,
label=None, seed=None, add_to_container=None):
self.bg = bg
self.neurons_action = neurons_action
self.mutual_inhibit = mutual_inhibit
self.route_inhibit = route_inhibit
self.synapse_inhibit = synapse_inhibit
self.synapse_direct = synapse_direct
self.threshold_action = threshold_action
self.neurons_channel_dim = neurons_channel_dim
self.subdim_channel = subdim_channel
self.synapse_channel = synapse_channel
self.neurons_gate = neurons_gate
self.neurons_cconv = neurons_cconv
self.threshold_gate = threshold_gate
self.synapse_to_gate = synapse_to_gate
self.synapse_bg = synapse_bg
self.gates = {} # gating ensembles per action (created as needed)
self.channels = {} # channels to pass transformed data between modules
Module.__init__(self, label, seed, add_to_container)
nengo.networks.Thalamus(self.bg.actions.count,
n_neurons_per_ensemble=self.neurons_action,
mutual_inhib=self.mutual_inhibit,
threshold=self.threshold_action,
net=self)
def __init__(self, actions, input_synapse=0.002):
self.actions = actions
self.input_synapse = input_synapse
self._bias = None
Module.__init__(self)
nengo.networks.BasalGanglia.__init__(self, dimensions=self.actions.count)
