def __init__(self, domain, index, type, value, decay_time = 0.0):
Neuron.__init__(self, domain, index)
self.type = type
self.decay_time = decay_time
if self.type == 'current':
self.value = value
elif self.type == 'voltage':
self.V_membrane = value
def __init__(self, domain, index, freq, scale, decay):
Neuron.__init__(self, domain, index)
self.type = 'current'
self.freq = freq/1000.0 #Probability of occring in 1ms
self.scale = scale
self.decay = 1.0-1.0/decay
self.value = 0.0
self.spikes_record = []
def __init__(self, domain, index, settings, STDP='on', initial_membrane_potential=0.0):
#settings['reset_potential'] = -70
#settings['spike_potential'] = 0
#settings['threshold'] = -54
#settings['refactory_period'] = 5.0 ms
#settings['left_window_constant'] = (t+)
#settings['right_window_constant'] = (t-)
#settings['learning_rate'] = learning_rate (A+)
#settings['stability'] = stability (B)
#settings['weight_ceiling'] = weight_ceiling
#settings['type'] = 'current' or 'voltage'
#settings['output_current_decay'] = 3.0 (only need if type is current)
#settings['output_current_peak'] = 2.2 (only need if type is current)
Neuron.__init__(self, domain, index)
self.STDP = STDP
self.reset_potential = settings['reset_potential']
self.spike_potential = settings['spike_potential']
self.threshold = settings['threshold']
self.weight_ceiling = settings['weight_ceiling']
self.type = settings['type']
if self.type == 'current':
self.output_current_peak = settings['output_current_peak']
self.output_current_decay = 1.0-1.0/settings['output_current_decay']
self.value = 0.0
self.stability = settings["stability"]
self.left_window_constant = settings["left_window_constant"]
self.left_learning_rate = settings['learning_rate']
self.left_window_width = abs(math.log(0.01) * self.left_window_constant)
self.right_window_constant = settings["right_window_constant"]
self.right_window_width = abs(math.log(0.01) * self.right_window_constant)
self.right_learning_rate = self.left_learning_rate * self.left_window_width * self.stability / self.right_window_width
if initial_membrane_potential == 0.0:
self.membrane_potential = self.reset_potential
else:
self.membrane_potential = initial_membrane_potential
self.left_window = []
self.right_window = []
self.refactory_period = settings['refactory_period']
self.refact = 'no'
self.last_firing_time = -1
self.spikes_number = 0
self.spikes_record = []
self.value_record = []
self.weights_record = []
def __init__(self, domain, index, scale, decay, pool_settings):
Neuron.__init__(self, domain, index)
self.type = 'current'
self.freq = 0.0
self.scale = scale
self.decay = 1.0-1.0/decay
self.alpha = pool_settings['alpha']
self.k = pool_settings['k']
self.a = pool_settings['a']
self.b = pool_settings['b']
self.c = pool_settings['c']
self.d = pool_settings['d']
self.pre_spike_time = []
self.value = 0.0
self.spikes_record = []
self.freq_record = []
