def test_exdir_extractors(self):
path1 = self.test_dir + '/raw.exdir'
se.ExdirRecordingExtractor.write_recording(self.RX, path1)
RX_exdir = se.ExdirRecordingExtractor(path1)
self._check_recording_return_types(RX_exdir)
self._check_recordings_equal(self.RX, RX_exdir)
path2 = self.test_dir + '/firings.exdir'
se.ExdirSortingExtractor.write_sorting(self.SX, path2, self.RX)
SX_exdir = se.ExdirSortingExtractor(path2)
self._check_sorting_return_types(SX_exdir)
self._check_sortings_equal(self.SX, SX_exdir)
def load_spiketrains(data_path,
channel_group=None,
load_waveforms=False,
sample_rate=None,
remove_group=None,
t_start=0 * pq.s):
'''
Parameters
----------
data_path
channel_group
load_waveforms
remove_label
Returns
-------
'''
if sample_rate is None:
sample_rate = 30000 * pq.Hz
sorting = se.ExdirSortingExtractor(data_path,
sample_rate=sample_rate.magnitude,
channel_group=channel_group,
load_waveforms=load_waveforms)
sptr = []
# build neo pbjects
for u in sorting.get_unit_ids():
times = sorting.get_unit_spike_train(u) / sample_rate
t_stop = np.max(times)
if load_waveforms and 'waveforms' in sorting.get_unit_spike_feature_names(
u):
wf = sorting.get_unit_spike_features(u, 'waveforms')
else:
wf = None
times = times - t_start
times = times[np.where(times > 0)]
if wf is not None:
wf = wf[np.where(times > 0)]
st = neo.SpikeTrain(times=times, t_stop=t_stop, waveforms=wf)
for p in sorting.get_unit_property_names(u):
st.annotations.update({p: sorting.get_unit_property(u, p)})
sptr.append(st)
sptr_rm = []
if remove_group is not None:
for st in sptr:
if st.annotations['cluster_group'] != remove_group:
sptr_rm.append(st)
else:
sptr_rm = sptr
return sptr_rm
def load_spiketrains(data_path,
channel_group=None,
load_waveforms=False,
lim=None):
'''
Parameters
----------
data_path
channel_group
load_waveforms
remove_label
Returns
-------
'''
sample_rate = get_sample_rate(data_path)
sorting = se.ExdirSortingExtractor(data_path,
sampling_frequency=sample_rate,
channel_group=channel_group,
load_waveforms=load_waveforms)
sptr = []
# build neo pbjects
for u in sorting.get_unit_ids():
times = sorting.get_unit_spike_train(u) / sample_rate
if lim is None:
t_stop = get_duration(data_path)
t_start = 0 * pq.s
else:
t_start = pq.Quantity(lim[0], 's')
t_stop = pq.Quantity(lim[1], 's')
mask = (times >= t_start) & (times <= t_stop)
times = times[mask]
if load_waveforms and 'waveforms' in sorting.get_unit_spike_feature_names(
u):
wf = sorting.get_unit_spike_features(u, 'waveforms')
wf = wf[mask] * pq.uV
else:
wf = None
st = neo.SpikeTrain(times=times,
t_stop=t_stop,
waveforms=wf,
sampling_rate=sample_rate)
for p in sorting.get_unit_property_names(u):
st.annotations.update({p: sorting.get_unit_property(u, p)})
sptr.append(st)
return sptr
def load_spiketrains(data_path,
channel_group=None,
load_waveforms=False,
t_start=0 * pq.s):
'''
Parameters
----------
data_path
channel_group
load_waveforms
remove_label
Returns
-------
'''
sample_rate = get_sample_rate(data_path)
sorting = se.ExdirSortingExtractor(data_path,
sample_rate=sample_rate.magnitude,
channel_group=channel_group,
load_waveforms=load_waveforms)
sptr = []
# build neo pbjects
for u in sorting.get_unit_ids():
times = sorting.get_unit_spike_train(u) / sample_rate
t_stop = np.max(times)
if load_waveforms and 'waveforms' in sorting.get_unit_spike_feature_names(
u):
wf = sorting.get_unit_spike_features(u, 'waveforms')
else:
wf = None
times = times - t_start
times = times[np.where(times > 0)]
wf = wf[np.where(times > 0)]
st = neo.SpikeTrain(times=times,
t_stop=t_stop,
waveforms=wf,
sampling_rate=sample_rate)
for p in sorting.get_unit_property_names(u):
st.annotations.update({p: sorting.get_unit_property(u, p)})
sptr.append(st)
return sptr
def load_unit_annotations(data_path, channel_group):
'''
Parameters
----------
data_path
channel_group
Returns
-------
'''
sample_rate = get_sample_rate(data_path)
sorting = se.ExdirSortingExtractor(data_path,
sampling_frequency=sample_rate,
channel_group=channel_group,
load_waveforms=False)
units = []
for u in sorting.get_unit_ids():
annotations = {}
for p in sorting.get_unit_property_names(u):
annotations.update({p: sorting.get_unit_property(u, p)})
units.append(annotations)
return units
