def from_memory(recording: se.RecordingExtractor,
serialize=False,
serialize_dtype=None):
if serialize:
if serialize_dtype is None:
raise Exception(
'You must specify the serialize_dtype when serializing recording extractor in from_memory()'
)
with hi.TemporaryDirectory() as tmpdir:
fname = tmpdir + '/' + _random_string(10) + '_recording.mda'
se.BinDatRecordingExtractor.write_recording(
recording=recording,
save_path=fname,
time_axis=0,
dtype=serialize_dtype)
with ka.config(use_hard_links=True):
uri = ka.store_file(fname, basename='raw.mda')
num_channels = recording.get_num_channels()
channel_ids = [int(a) for a in recording.get_channel_ids()]
xcoords = [
recording.get_channel_property(a, 'location')[0]
for a in channel_ids
]
ycoords = [
recording.get_channel_property(a, 'location')[1]
for a in channel_ids
]
recording = LabboxEphysRecordingExtractor({
'recording_format': 'bin1',
'data': {
'raw':
uri,
'raw_num_channels':
num_channels,
'num_frames':
int(recording.get_num_frames()),
'samplerate':
float(recording.get_sampling_frequency()),
'channel_ids':
channel_ids,
'channel_map':
dict(
zip([str(c) for c in channel_ids],
[int(i) for i in range(num_channels)])),
'channel_positions':
dict(
zip([str(c) for c in channel_ids],
[[float(xcoords[i]),
float(ycoords[i])]
for i in range(num_channels)]))
}
})
return recording
obj = {
'recording_format': 'in_memory',
'data': register_in_memory_object(recording)
}
return LabboxEphysRecordingExtractor(obj)
def _get_geom_from_recording(recording: se.RecordingExtractor):
channel_ids = recording.get_channel_ids()
M = len(channel_ids)
location0 = recording.get_channel_property(channel_ids[0], 'location')
nd = len(location0)
geom = np.zeros((M, nd))
for i in range(M):
location_i = recording.get_channel_property(channel_ids[i], 'location')
geom[i, :] = location_i
return geom
def _get_geom_from_recording(recording: se.RecordingExtractor) -> np.ndarray:
"""Retrieve the electrode locations for a recording
Parameters
----------
recording : se.RecordingExtractor
Recording extractor (SpikeInterface)
Returns
-------
np.ndarray
Geom array (M x D) where the dimension D is either 2 or 3
"""
channel_ids = recording.get_channel_ids()
M = len(channel_ids)
location0 = recording.get_channel_property(channel_ids[0], 'location')
nd = len(location0)
geom = np.zeros((M, nd))
for ch_id, ii in enumerate(channel_ids):
location_ii = recording.get_channel_property(
ch_id, 'location')
geom[ii, :] = list(location_ii)
return geom