71 lines
2.0 KiB
Python
71 lines
2.0 KiB
Python
import numpy as np
|
|
import matplotlib.pyplot as plt
|
|
from my_util import functions as fu
|
|
import time
|
|
|
|
|
|
def main():
|
|
|
|
x_values = np.arange(-1, 1, 0.01)
|
|
popt = [0, 0, 0, 0]
|
|
y_values = [fu.full_boltzmann(x, popt[0], popt[1], popt[2], popt[3]) for x in x_values]
|
|
|
|
plt.plot(x_values, y_values)
|
|
plt.show()
|
|
quit()
|
|
|
|
for freq in [700, 50, 100, 500, 1000]:
|
|
reps = 1000
|
|
start = time.time()
|
|
for i in range(reps):
|
|
mean_isi = 1 / freq
|
|
n = 0.7
|
|
phase_locking_strength = 0.7
|
|
size = 100000
|
|
|
|
final_isis = np.array([])
|
|
while len(final_isis) < size:
|
|
|
|
isis = np.random.normal(mean_isi, mean_isi*n, size)
|
|
isi_phase = (isis % mean_isi) / mean_isi
|
|
diff = abs_phase_diff(isi_phase, 0.5)
|
|
chance = np.random.random(size)
|
|
|
|
isis_phase_cleaned = []
|
|
for i in range(len(diff)):
|
|
if 1-diff[i]**0.05 > chance[i]:
|
|
isis_phase_cleaned.append(isis[i])
|
|
|
|
final_isis = np.concatenate((final_isis, isis_phase_cleaned))
|
|
|
|
spikes = np.cumsum(final_isis)
|
|
spikes = np.sort(spikes[spikes > 0])
|
|
clean_isis = np.diff(spikes)
|
|
|
|
bins = np.arange(-0.01, 0.01, 0.0001)
|
|
plt.hist(clean_isis, alpha=0.5, bins=bins)
|
|
plt.hist(isis, alpha=0.5, bins=bins)
|
|
plt.show()
|
|
quit()
|
|
|
|
end = time.time()
|
|
|
|
print("It took {:.2f} s to simulate 10s of spikes at {} Hz".format(end-start, freq))
|
|
|
|
|
|
def abs_phase_diff(rel_phases:list, ref_phase:float):
|
|
"""
|
|
|
|
:param rel_phases: relative phases as a list of values between 0 and 1
|
|
:param ref_phase: reference phase to which the difference is calculated (between 0 and 1)
|
|
:return: list of absolute differences
|
|
"""
|
|
|
|
diff = [abs(min(x-ref_phase, x-ref_phase+1)) for x in rel_phases]
|
|
|
|
return diff
|
|
|
|
|
|
if __name__ == '__main__':
|
|
main()
|