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

adding with ittertools the combinations

Browse Source
This commit is contained in:
wendtalexander 2023-01-18 09:16:34 +01:00
parent 363f2dd14c
commit 00d6fed161
1 changed files with 20 additions and 14 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

34
code/chirpdetection.py
View File

@ -1,4 +1,4 @@
import os import itertools
import numpy as np import numpy as np
from IPython import embed from IPython import embed
@ -598,25 +598,31 @@ def main(datapath: str) -> None:
bool_vector = np.ones(len(sort_chirps_electrodes), dtype=bool) bool_vector = np.ones(len(sort_chirps_electrodes), dtype=bool)
# make index vector # make index vector
index_vector = np.arange(len(sort_chirps_electrodes)) index_vector = np.arange(len(sort_chirps_electrodes))
# make it more than only two electrodes for the search after chirps
combinations_best_elctrodes = list(itertools.combinations(range(3), 2))
the_real_chirps = [] the_real_chirps = []
for chirp_index, seoc in enumerate(sort_chirps_electrodes): for chirp_index, seoc in enumerate(sort_chirps_electrodes):
if bool_vector[chirp_index] == False: if bool_vector[chirp_index] == False:
continue continue
else: 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)]
for combination in combinations_best_elctrodes:
if set([0,1]).issubset(sort_electrodes[cm]): if set(combination).issubset(sort_electrodes[cm]):
the_real_chirps.append(np.mean(sort_chirps_electrodes[cm]))
elif set([1,0]).issubset(sort_electrodes[cm]):
the_real_chirps.append(np.mean(sort_chirps_electrodes[cm]))
elif set([0,2]).issubset(sort_electrodes[cm]):
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])) the_real_chirps.append(np.mean(sort_chirps_electrodes[cm]))
"""
bool_vector[cm] = False 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]):
the_real_chirps.append(np.mean(sort_chirps_electrodes[cm]))
elif set([0,2]).issubset(sort_electrodes[cm]):
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
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()