raab/GP2023_chirp_detection
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patrick übernimmt

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This commit is contained in:
wendtalexander 2023-01-18 11:43:11 +01:00
parent 76b8042619
commit ba3803bb56
1 changed files with 13 additions and 3 deletions
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code/chirpdetection.py
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@ -12,7 +12,7 @@ from sklearn.preprocessing import normalize
from modules.filters import bandpass_filter, envelope, highpass_filter
from modules.filehandling import ConfLoader, LoadData
from modules.plotstyle import PlotStyle
from modules.timestamps import group_timestamps, group_timestamps_v2
ps = PlotStyle()
@ -649,10 +649,20 @@ def main(datapath: str) -> None:
t0 = (3 * 60 * 60 + 6 * 60 + 43.5)
data_oi = data.raw[window_starts[0]:window_starts[-1]+ int(dt*data.raw_rate), 10]
plot_spectrogram(ax, data_oi, data.raw_rate, t0)
chirps = np.concatenate(chirps)
for ch in chirps:
chirps_concat = np.concatenate(chirps)
for ch in chirps_concat:
ax. axvline(ch, color='b', lw=1)
chirps_new = []
chirps_ids = []
[chirps[x] for x in tr_index]
for tr in np.unique(fish_ids):
tr_index = np.asarray(fish_ids) == tr
ts = list(np.ravel(chirps[fish_ids == int(tr)]))
chirps_new.extend(ts)
chirps_ids.extend(list(np.ones_like(ts)*tr))