raab/GP2023_chirp_detection
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saved chirps

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This commit is contained in:
wendtalexander 2023-01-18 10:25:48 +01:00
parent 844f65e24e
commit ad888734dd
2 changed files with 18 additions and 7 deletions
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18
code/chirpdetection.py
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@ -527,6 +527,9 @@ def main(datapath: str) -> None:
if len(baseline_ts) == 0 or len(search_ts) == 0 or len(freq_ts) == 0: if len(baseline_ts) == 0 or len(search_ts) == 0 or len(freq_ts) == 0:
continue continue
#current_chirps = group_timestamps_v2(
# [list(baseline_ts), list(search_ts), list(freq_ts)], 3)
# get index for each feature # get index for each feature
baseline_idx = np.zeros_like(baseline_ts) baseline_idx = np.zeros_like(baseline_ts)
@ -610,11 +613,16 @@ def main(datapath: str) -> None:
cm = index_vector[(sort_chirps_electrodes >= seoc) & ( cm = index_vector[(sort_chirps_electrodes >= seoc) & (
sort_chirps_electrodes <= seoc + config.chirp_window_threshold)] sort_chirps_electrodes <= seoc + config.chirp_window_threshold)]
chirps_unique = []
for combination in combinations_best_elctrodes: for combination in combinations_best_elctrodes:
if set(combination).issubset(sort_electrodes[cm]): if set(combination).issubset(sort_electrodes[cm]):
the_real_chirps.append( chirps_unique.append(np.mean(sort_chirps_electrodes[cm]))
np.mean(sort_chirps_electrodes[cm]))
the_real_chirps.append(np.mean(chirps_unique))
"""
if set([0,1]).issubset(sort_electrodes[cm]): if set([0,1]).issubset(sort_electrodes[cm]):
the_real_chirps.append(np.mean(sort_chirps_electrodes[cm])) the_real_chirps.append(np.mean(sort_chirps_electrodes[cm]))
elif set([1,0]).issubset(sort_electrodes[cm]): elif set([1,0]).issubset(sort_electrodes[cm]):
@ -623,12 +631,14 @@ def main(datapath: str) -> None:
the_real_chirps.append(np.mean(sort_chirps_electrodes[cm])) the_real_chirps.append(np.mean(sort_chirps_electrodes[cm]))
elif set([1,2]).issubset(sort_electrodes[cm]): elif set([1,2]).issubset(sort_electrodes[cm]):
the_real_chirps.append(np.mean(sort_chirps_electrodes[cm])) the_real_chirps.append(np.mean(sort_chirps_electrodes[cm]))
"""
bool_vector[cm] = False bool_vector[cm] = False
chirps.append(the_real_chirps)
for ct in the_real_chirps: for ct in the_real_chirps:
axs[0, el].axvline(ct, color='b', lw=1) axs[0, el].axvline(ct, color='b', lw=1)
embed() embed()
plt.show()
if __name__ == "__main__": if __name__ == "__main__":

3
code/modules/timestamps.py
View File

@ -82,7 +82,8 @@ def group_timestamps_v2(sublists: List[List[Union[int, float]]], n: int, time_th
current_group = [] current_group = []
# Create a set to store the timestamps that occur in at least n of the sublists # Create a set to store the timestamps that occur in at least n of the sublists
common_timestamps = set.intersection(*[set(lst) for lst in sublists]) common_timestamps = set.intersection(*[set(lst) for lst in sublists])
embed() # convert the set to a list
common_timestamps = list(common_timestamps)
# Iterate through the timestamps # Iterate through the timestamps
for i in range(len(common_timestamps)): for i in range(len(common_timestamps)):
# If the current timestamp is less than 50 milliseconds away from the previous timestamp # If the current timestamp is less than 50 milliseconds away from the previous timestamp