def __init__(self, n_neurons, machine_time_step, v_init, v_rest, tau_m, cm,
i_offset, v_reset, tau_refrac):
NeuronModelLeakyIntegrate.__init__(self, n_neurons, machine_time_step,
v_init, v_rest, tau_m, cm, i_offset)
self._v_reset = utility_calls.convert_param_to_numpy(
v_reset, n_neurons)
self._tau_refrac = utility_calls.convert_param_to_numpy(
tau_refrac, n_neurons)
def __init__(self, n_neurons, machine_time_step, v_init, v_rest, tau_m, cm,
i_offset, v_reset, tau_refrac):
NeuronModelLeakyIntegrate.__init__(
self, n_neurons, machine_time_step, v_init, v_rest, tau_m, cm,
i_offset)
self._v_reset = utility_calls.convert_param_to_numpy(
v_reset, n_neurons)
self._tau_refrac = utility_calls.convert_param_to_numpy(
tau_refrac, n_neurons)
def __init__(self, n_neurons, v_init, v_rest, tau_m, cm, i_offset, v_reset,
tau_refrac):
NeuronModelLeakyIntegrate.__init__(self, n_neurons, v_init, v_rest,
tau_m, cm, i_offset)
self._v_reset = utility_calls.convert_param_to_numpy(
v_reset, n_neurons)
self._tau_refrac = utility_calls.convert_param_to_numpy(
tau_refrac, n_neurons)
self._countdown_to_refactory_period = \
utility_calls.convert_param_to_numpy(0, n_neurons)
self._my_units = {'v_reset': 'mV', 'tau_refac': 'ms'}
def get_neural_parameters(self):
params = NeuronModelLeakyIntegrate.get_neural_parameters(self)
params.extend([
# countdown to end of next refractory period [timesteps]
# int32_t refract_timer;
NeuronParameter(0, DataType.INT32),
# post-spike reset membrane voltage [mV]
# REAL V_reset;
NeuronParameter(self._v_reset, DataType.S1615),
# refractory time of neuron [timesteps]
# int32_t T_refract;
NeuronParameter(self._tau_refrac_timesteps, DataType.INT32)
])
return params
def get_neural_parameters(self):
params = NeuronModelLeakyIntegrate.get_neural_parameters(self)
params.extend([
# countdown to end of next refractory period [timesteps]
# int32_t refract_timer;
NeuronParameter(0, DataType.INT32),
# post-spike reset membrane voltage [mV]
# REAL V_reset;
NeuronParameter(self._v_reset, DataType.S1615),
# refractory time of neuron [timesteps]
# int32_t T_refract;
NeuronParameter(self._tau_refrac_timesteps, DataType.INT32)
])
return params
def get_neural_parameters(self, machine_time_step):
params = NeuronModelLeakyIntegrate.get_neural_parameters(self)
params.extend([
# count down to end of next refractory period [timesteps]
# int32_t refract_timer;
NeuronParameter(self._countdown_to_refactory_period,
_LIF_TYPES.REFRACT_COUNT.data_type),
# post-spike reset membrane voltage [mV]
# REAL V_reset;
NeuronParameter(self._v_reset, _LIF_TYPES.V_RESET.data_type),
# refractory time of neuron [timesteps]
# int32_t T_refract;
NeuronParameter(self._tau_refrac_timesteps(machine_time_step),
_LIF_TYPES.TAU_REFRACT.data_type)
])
return params
def get_n_cpu_cycles_per_neuron(self):
# A guess - 20 for the reset procedure
return NeuronModelLeakyIntegrate.get_n_cpu_cycles_per_neuron(self) + 20
def get_neural_parameter_types(self):
if_types = NeuronModelLeakyIntegrate.get_neural_parameter_types(self)
if_types.extend([item.data_type for item in _LIF_TYPES])
return if_types
def get_n_neural_parameters(self):
return NeuronModelLeakyIntegrate.get_n_neural_parameters(self) + 3
def get_units(self, variable):
if variable in self._my_units:
return self._my_units[variable]
else:
return NeuronModelLeakyIntegrate.get_units(variable)
def get_n_cpu_cycles_per_neuron(self):
# A guess - 20 for the reset procedure
return NeuronModelLeakyIntegrate.get_n_cpu_cycles_per_neuron(self) + 20
def get_n_neural_parameters(self):
return NeuronModelLeakyIntegrate.get_n_neural_parameters(self) + 3