def test_max_chan():
n_wf_samples = 100
folder = 'test'
if os.path.isdir(folder):
shutil.rmtree(folder)
rec, sort, waveforms, templates, max_chans, amps = create_signal_with_known_waveforms(
n_waveforms=2, n_channels=4, n_wf_samples=n_wf_samples)
rec, sort = create_dumpable_extractors_from_existing(folder, rec, sort)
max_channels = get_unit_max_channels(rec,
sort,
save_property_or_features=False)
assert np.allclose(np.array(max_chans), np.array(max_channels))
assert 'max_channel' not in sort.get_shared_unit_property_names()
max_channels = get_unit_max_channels(rec,
sort,
save_property_or_features=True,
recompute_templates=True,
peak='neg',
recompute_info=True)
assert np.allclose(np.array(max_chans), np.array(max_channels))
assert 'max_channel' in sort.get_shared_unit_property_names()
# multiple channels
max_channels = get_unit_max_channels(rec,
sort,
max_channels=2,
peak='neg',
recompute_info=True)
assert np.allclose(np.array(max_chans), np.array(max_channels)[:, 0])
assert np.array(max_channels).shape[1] == 2
shutil.rmtree('test')
def test_amplitudes():
n_jobs = [0, 2]
memmap = [True, False]
for n in n_jobs:
for m in memmap:
print('N jobs', n, 'memmap', m)
n_wf_samples = 100
folder = 'test'
if os.path.isdir(folder):
shutil.rmtree(folder)
rec, sort, waveforms, templates, max_chans, amps = create_signal_with_known_waveforms(
n_waveforms=2, n_channels=4, n_wf_samples=n_wf_samples)
rec, sort = create_dumpable_extractors_from_existing(
folder, rec, sort)
amp = get_unit_amplitudes(rec,
sort,
frames_before=50,
frames_after=50,
save_property_or_features=False,
n_jobs=n,
memmap=m)
for (a, a_gt) in zip(amp, amps):
assert np.allclose(a, np.abs(a_gt))
assert 'amplitudes' not in sort.get_shared_unit_spike_feature_names(
)
amp = get_unit_amplitudes(rec,
sort,
frames_before=50,
frames_after=50,
save_property_or_features=True,
peak='neg',
n_jobs=n,
memmap=m)
for (a, a_gt) in zip(amp, amps):
assert np.allclose(a, a_gt)
assert 'amplitudes' in sort.get_shared_unit_spike_feature_names()
# relative
amp = get_unit_amplitudes(rec,
sort,
frames_before=50,
frames_after=50,
save_property_or_features=False,
recompute_info=True,
method='relative',
n_jobs=n,
memmap=m)
amps_rel = [a / np.median(a) for a in amps]
for (a, a_gt) in zip(amp, amps_rel):
assert np.allclose(a, np.abs(a_gt), 0.02)
shutil.rmtree('test')
def test_templates():
n_wf_samples = 100
folder = 'test'
if os.path.isdir(folder):
shutil.rmtree(folder)
rec, sort, waveforms, templates, max_chans, amps = create_signal_with_known_waveforms(
n_waveforms=2, n_channels=4, n_wf_samples=n_wf_samples)
rec, sort = create_dumpable_extractors_from_existing(folder, rec, sort)
# get num samples in ms
ms_cut = n_wf_samples // 2 / rec.get_sampling_frequency() * 1000
# no group
temp = get_unit_templates(rec,
sort,
ms_before=ms_cut,
ms_after=ms_cut,
save_property_or_features=False,
save_wf_as_features=False,
recompute_info=True)
for (t, t_gt) in zip(temp, templates):
assert np.allclose(t, t_gt, atol=1)
assert 'template' not in sort.get_shared_unit_property_names()
assert 'waveforms' not in sort.get_shared_unit_spike_feature_names()
# change cut ms
temp = get_unit_templates(rec,
sort,
ms_before=2,
ms_after=2,
save_property_or_features=True,
recompute_waveforms=True,
recompute_info=True)
for (t, t_gt) in zip(temp, templates):
_, samples = t.shape
assert np.allclose(t[:, samples // 2 - n_wf_samples // 2:samples // 2 +
n_wf_samples // 2],
t_gt,
atol=1)
assert 'template' in sort.get_shared_unit_property_names()
assert 'waveforms' in sort.get_shared_unit_spike_feature_names()
# by group
rec.set_channel_groups([0, 0, 1, 1])
temp = get_unit_templates(rec,
sort,
ms_before=ms_cut,
ms_after=ms_cut,
grouping_property='group',
recompute_info=True)
for (t, t_gt) in zip(temp, templates):
assert np.allclose(t, t_gt[:2], atol=1) or np.allclose(
t, t_gt[2:], atol=1)
shutil.rmtree('test')
def test_waveforms():
n_wf_samples = 100
n_jobs = [0, 2]
for n in n_jobs:
for m in memmaps:
print('N jobs', n, 'memmap', m)
folder = 'test'
if os.path.isdir(folder):
shutil.rmtree(folder)
rec, sort, waveforms, templates, max_chans, amps = create_signal_with_known_waveforms(
n_waveforms=2, n_channels=4, n_wf_samples=n_wf_samples)
rec, sort = create_dumpable_extractors_from_existing(
folder, rec, sort)
# get num samples in ms
ms_cut = n_wf_samples // 2 / rec.get_sampling_frequency() * 1000
# no group
wav = get_unit_waveforms(rec,
sort,
ms_before=ms_cut,
ms_after=ms_cut,
save_property_or_features=False,
n_jobs=n,
memmap=m,
recompute_info=True)
for (w, w_gt) in zip(wav, waveforms):
assert np.allclose(w, w_gt)
assert 'waveforms' not in sort.get_shared_unit_spike_feature_names(
)
# small chunks
wav = get_unit_waveforms(rec,
sort,
ms_before=ms_cut,
ms_after=ms_cut,
save_property_or_features=False,
n_jobs=n,
memmap=m,
chunk_mb=5,
recompute_info=True)
for (w, w_gt) in zip(wav, waveforms):
assert np.allclose(w, w_gt)
assert 'waveforms' not in sort.get_shared_unit_spike_feature_names(
)
# change cut ms
wav = get_unit_waveforms(rec,
sort,
ms_before=2,
ms_after=2,
save_property_or_features=True,
n_jobs=n,
memmap=m,
recompute_info=True)
for (w, w_gt) in zip(wav, waveforms):
_, _, samples = w.shape
assert np.allclose(
w[:, :, samples // 2 - n_wf_samples // 2:samples // 2 +
n_wf_samples // 2], w_gt)
assert 'waveforms' in sort.get_shared_unit_spike_feature_names()
# by group
rec.set_channel_groups([0, 0, 1, 1])
wav = get_unit_waveforms(rec,
sort,
ms_before=ms_cut,
ms_after=ms_cut,
grouping_property='group',
n_jobs=n,
memmap=m,
recompute_info=True)
for (w, w_gt) in zip(wav, waveforms):
assert np.allclose(w, w_gt[:, :2]) or np.allclose(
w, w_gt[:, 2:])
# test compute_property_from_recordings
wav = get_unit_waveforms(rec,
sort,
ms_before=ms_cut,
ms_after=ms_cut,
grouping_property='group',
compute_property_from_recording=True,
n_jobs=n,
memmap=m,
recompute_info=True)
for (w, w_gt) in zip(wav, waveforms):
assert np.allclose(w, w_gt[:, :2]) or np.allclose(
w, w_gt[:, 2:])
# test max_spikes_per_unit
wav = get_unit_waveforms(rec,
sort,
ms_before=ms_cut,
ms_after=ms_cut,
max_spikes_per_unit=10,
save_property_or_features=False,
n_jobs=n,
memmap=m,
recompute_info=True)
for w in wav:
assert len(w) <= 10
# test channels
wav = get_unit_waveforms(rec,
sort,
ms_before=ms_cut,
ms_after=ms_cut,
channel_ids=[0, 1, 2],
n_jobs=n,
memmap=m,
recompute_info=True)
for (w, w_gt) in zip(wav, waveforms):
assert np.allclose(w, w_gt[:, :3])
shutil.rmtree('test')
