def calibrate_current(self, ttfs):
for current in range(0, 10000, 1):
neuron = Neuron()
for time in range(0, ttfs + 1):
neuron.time_step(current / 10., time)
if neuron.has_spiked(): break
if neuron.last_spike == ttfs:
return current / 10.
def calibrate_current(self, rate):
""" Rate must be less than self.t_window """
for current in range(0, 1000, 1):
neuron = Neuron()
spikes = 0
for c_time in range(1, self.t_window + 1):
if neuron.time_step(current / 10., c_time) == 1:
spikes += 1
if spikes == rate: return current / 10.
if spikes == self.t_window: break
return -1
CAPACITANCE = 2.5
REST_VOLTAGE = 10
SPIKE_VOLTAGE = 75
print('Problem 1')
plt.figure(1)
for x in range(10, 90, 20):
CURRENTS.append(x)
for i in range(1, len(CURRENTS)+1):
neuron = LIF(CAPACITANCE, RESISTANCE, SPIKE_VOLTAGE, REST_VOLTAGE)
current = CURRENTS[i-1]
plt.subplot(810+i)
plt.title('Current: {}'.format(current))
for i in range(TIME_STEPS-1):
neuron.time_step(current, i)
neuron.add_plot(plt)
x1, x2, y1, y2 = plt.axis()
plt.axis((x1, x2, 0, SPIKE_VOLTAGE*SPIKE_MULTIPLIER))
plt.gca().yaxis.set_minor_formatter(NullFormatter())
plt.grid(True)
plt.minorticks_on()
plt.gca().set_yticks([REST_VOLTAGE, SPIKE_VOLTAGE])
plt.gca().set_xticks([])
for i in range(1, len(CURRENTS)+1):
neuron = LIF(CAPACITANCE, RESISTANCE, SPIKE_VOLTAGE, REST_VOLTAGE)
current = CURRENTS[i-1]
plt.subplot(810+i+4)
plt.title('Current: {}'.format(current))
for i in range(int(TIME_STEPS*2/3)):
neuron.time_step(current, i)
RESISTANCE = 2
CAPACITANCE = 2.5
REST_VOLTAGE = 10
SPIKE_VOLTAGE = 75
print('Problem 1')
plt.figure(1)
for x in range(10, 90, 20):
CURRENTS.append(x)
for i in range(1, len(CURRENTS) + 1):
neuron = LIF(CAPACITANCE, RESISTANCE, SPIKE_VOLTAGE, REST_VOLTAGE)
current = CURRENTS[i - 1]
plt.subplot(810 + i)
plt.title('Current: {}'.format(current))
for i in range(TIME_STEPS - 1):
neuron.time_step(current)
neuron.add_plot(plt)
x1, x2, y1, y2 = plt.axis()
plt.axis((x1, x2, 0, SPIKE_VOLTAGE * SPIKE_MULTIPLIER))
plt.gca().yaxis.set_minor_formatter(NullFormatter())
plt.grid(True)
plt.minorticks_on()
plt.gca().set_yticks([REST_VOLTAGE, SPIKE_VOLTAGE])
plt.gca().set_xticks([])
for i in range(1, len(CURRENTS) + 1):
neuron = LIF(CAPACITANCE, RESISTANCE, SPIKE_VOLTAGE, REST_VOLTAGE)
current = CURRENTS[i - 1]
plt.subplot(810 + i + 4)
plt.title('Current: {}'.format(current))
for i in range(int(TIME_STEPS * 2 / 3)):
neuron.time_step(current)