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