2import spikeinterface as si
3import numpy as np
4from s3_utils import download_s3_folder
6s3_folder_name = "s3://aind-benchmark-data/ephys-compression/aind-np2/612962_2022-04-13_19-18-04_ProbeB"
7local_folder_name = "612962_2022-04-13_19-18-04_ProbeB.si"
9if not os.path.exists(local_folder_name):
10 download_s3_folder(s3_folder_name, local_folder_name)
12recording = si.load(
13 local_folder_name
14)
16channel_ids = [
17 'CH101',
18 'CH102',
19 'CH103',
20 'CH104',
21 'CH105',
22 'CH106',
23 'CH107',
24 'CH108',
25 'CH109',
26 'CH110'
27]
29fname = f'aind_compression_np2_probeB_ch101-110.raw.npy'
30if not os.path.exists(fname):
31 print(f'Writing {fname}...')
32 X = recording.get_traces(channel_ids=channel_ids, start_frame=30000, end_frame=30000 + 30000 * 10)
33 print(f'X.shape = {X.shape}')
34 np.save(fname, X)