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""" isi_lengths.py
Support for automatic threshold determination
Copyright 2023, Thomas Kreuz
Distributed under the BSD License
"""
import numpy as np
def isi_lengths(spike_times, t_start, t_end):
""" Plain Python implementation of logic to extract ISI lengths
In: spike_times - spike times
t_start, t_end - interval for ISI calculation
Out: isi_lengths - ISI distance between consecutive elements of spike_events
Note: the only complexities are with the edges and N==1
"""
N = len(spike_times)
if N == 0:
return [t_end-t_start]
if spike_times[0] > t_start:
del_start = max(spike_times[0] - t_start, spike_times[1] - spike_times[0])\
if N > 1 else spike_times[0] - t_start
i_start = 0
else:
del_start = spike_times[1] - spike_times[0]\
if N > 1 else t_start - spike_times[0]
i_start = 1
if spike_times[-1] < t_end:
del_end = max(t_end - spike_times[-1], spike_times[-1] - spike_times[-2])\
if N > 1 else t_end - spike_times[0]
i_end = N
else:
del_end = spike_times[-1] - spike_times[-2]\
if N > 1 else spike_times[0] - t_end
i_end = N-1
dels = [spike_times[i+1]-spike_times[i] for i in range(i_start, i_end-1)]
isi_lengths = [del_start] + dels + [del_end]
return isi_lengths
def default_thresh_(train_list, t_start, t_end):
""" Implements default_thresh()
In: train_list - list of list of spike times
t_start, t_end - begin and end times for spikes
Out: threshold
"""
spike_pool = []
for t in train_list:
spike_pool += isi_lengths(t, t_start, t_end)
spike_pool = np.array(spike_pool)
sum_squares = np.sum(spike_pool * spike_pool)
ss_avg = sum_squares/len(spike_pool)
return np.sqrt(ss_avg)
def default_thresh(spike_train_list):
""" Computes a default threshold for a list of spike trains
In: spike_train_list - list of list of SpikeTrain object
Out: threshold as specified in section 2.4 of
"Measures of spike train synchrony for data with multiple time scales"
"""
if len(spike_train_list) == 0:
return 0
st = spike_train_list[0]
train_list = [st.spikes.tolist() for st in spike_train_list]
return default_thresh_(train_list, st.t_start, st.t_end)
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