raab/GP2023_chirp_detection
1
0
Fork 0
Code Issues Pull Requests Releases Wiki Activity

saved chirps

Browse Source
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
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

22
code/chirpdetection.py
View File

@ -527,7 +527,10 @@ def main(datapath: str) -> None:
if len(baseline_ts) == 0 or len(search_ts) == 0 or len(freq_ts) == 0:
continue
#current_chirps = group_timestamps_v2(
# [list(baseline_ts), list(search_ts), list(freq_ts)], 3)
# get index for each feature
baseline_idx = np.zeros_like(baseline_ts)
search_idx = np.ones_like(search_ts)
@ -561,7 +564,7 @@ def main(datapath: str) -> None:
current_chirps.append(np.mean(timestamps[cm]))
electrodes_of_chirps.append(el)
bool_timestamps[cm] = False
# for checking if there are chirps on multiple electrodes
chirps_electrodes.append(current_chirps)
@ -610,11 +613,16 @@ def main(datapath: str) -> None:
cm = index_vector[(sort_chirps_electrodes >= seoc) & (
sort_chirps_electrodes <= seoc + config.chirp_window_threshold)]
chirps_unique = []
for combination in combinations_best_elctrodes:
if set(combination).issubset(sort_electrodes[cm]):
the_real_chirps.append(
np.mean(sort_chirps_electrodes[cm]))
chirps_unique.append(np.mean(sort_chirps_electrodes[cm]))
the_real_chirps.append(np.mean(chirps_unique))
"""
if set([0,1]).issubset(sort_electrodes[cm]):
the_real_chirps.append(np.mean(sort_chirps_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]))
elif set([1,2]).issubset(sort_electrodes[cm]):
the_real_chirps.append(np.mean(sort_chirps_electrodes[cm]))
"""
bool_vector[cm] = False
chirps.append(the_real_chirps)
for ct in the_real_chirps:
axs[0, el].axvline(ct, color='b', lw=1)
embed()
plt.show()
embed()
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 = []
# 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])
embed()
# convert the set to a list
common_timestamps = list(common_timestamps)
# Iterate through the timestamps
for i in range(len(common_timestamps)):
# If the current timestamp is less than 50 milliseconds away from the previous timestamp