def __init__(
self,
n_neurons,
# TODO: update the parameters
i_offset,
my_neuron_parameter,
# TODO: update the state variables if required
v_init=-70.0):
AbstractNeuronModel.__init__(self)
AbstractContainsUnits.__init__(self)
self._units = {
'v_init': 'mV',
'my_neuron_parameter': 'mV',
'i_offset': 'nA'
}
self._n_neurons = n_neurons
# TODO: Store any parameters
self._i_offset = utility_calls.convert_param_to_numpy(
i_offset, n_neurons)
self._my_neuron_parameter = utility_calls.convert_param_to_numpy(
my_neuron_parameter, n_neurons)
# TODO: Store any state variables
self._v_init = utility_calls.convert_param_to_numpy(v_init, n_neurons)
def __init__(self, n_neurons, damping_factor, damping_sum,
incoming_edges_count, outgoing_edges_count, rank_init,
curr_rank_acc_init, curr_rank_count_init, iter_state_init):
AbstractNeuronModel.__init__(self)
AbstractContainsUnits.__init__(self)
self._n_neurons = n_neurons
# Global parameters
self._damping_factor = damping_factor
self._damping_sum = damping_sum
# Store any neural parameters
self._incoming_edges_count = self._var_init(incoming_edges_count)
self._outgoing_edges_count = self._var_init(outgoing_edges_count)
# Store any neural state variables
self._initialize_state_vars([
('rank_init', rank_init),
('curr_rank_acc_init', curr_rank_acc_init),
('curr_rank_count_init', curr_rank_count_init),
('iter_state_init', iter_state_init),
])
def __init__(self, n_neurons, damping_factor, damping_sum,
incoming_edges_count, outgoing_edges_count, rank_init,
curr_rank_acc_init, curr_rank_count_init, iter_state_init):
AbstractNeuronModel.__init__(self)
AbstractContainsUnits.__init__(self)
self._n_neurons = n_neurons
# Global parameters (fixed value throughout simulation)
self._damping_factor = damping_factor
self._damping_sum = damping_sum
# Store any neural parameters (fixed value throughout simulation)
self._incoming_edges_count = self._var_init(incoming_edges_count)
self._outgoing_edges_count = self._var_init(outgoing_edges_count)
# Store any neural state variables (value is expected to change)
self._initialise_state_vars([
('rank_init', rank_init),
('curr_rank_acc_init', curr_rank_acc_init),
('curr_rank_count_init', curr_rank_count_init),
('iter_state_init', iter_state_init),
])
def __init__(self, foo, bar):
AbstractNeuronModel.__init__(self, [], [])
self._foo = foo
self._bar = bar
def __init__(self, foo, bar):
AbstractNeuronModel.__init__(self, [], [])
self._foo = foo
self._bar = bar