def test_calculate_pc_metrics():
we = WaveformExtractor.load_from_folder('toy_waveforms')
print(we)
pca = WaveformPrincipalComponent.load_from_folder('toy_waveforms')
print(pca)
res = calculate_pc_metrics(pca)
print(res)
def test_compute_quality_metrics():
we = WaveformExtractor.load_from_folder('toy_waveforms')
print(we)
# without PC
metrics = compute_quality_metrics(we, metric_names=['snr'])
assert 'snr' in metrics.columns
assert 'isolation_distance' not in metrics.columns
print(metrics)
# with PCs
pca = WaveformPrincipalComponent(we)
pca.set_params(n_components=5, mode='by_channel_local')
pca.run()
metrics = compute_quality_metrics(we)
assert 'isolation_distance' in metrics.columns
print(metrics)
# reload as an extension from we
assert QualityMetricCalculator in we.get_available_extensions()
assert we.is_extension('quality_metrics')
qmc = we.load_extension('quality_metrics')
assert isinstance(qmc, QualityMetricCalculator)
assert qmc._metrics is not None
# print(qmc._metrics)
qmc = QualityMetricCalculator.load_from_folder('toy_waveforms')
assert qmc._metrics is not None
def test_compute_quality_metrics():
we = WaveformExtractor.load_from_folder('toy_waveforms')
print(we)
# without PC
metrics = compute_quality_metrics(we, metric_names=['snr'])
print(metrics)
print(metrics.columns)
# with PCs
pca = WaveformPrincipalComponent(we)
pca.set_params(n_components=5, mode='by_channel_local')
pca.run()
metrics = compute_quality_metrics(we, waveform_principal_component=pca)
print(metrics)
print(metrics.columns)
def setup_module():
for folder in ('toy_rec', 'toy_sorting', 'toy_waveforms'):
if Path(folder).is_dir():
shutil.rmtree(folder)
recording, sorting = toy_example(num_segments=2, num_units=10)
recording = recording.save(folder='toy_rec')
sorting = sorting.save(folder='toy_sorting')
we = WaveformExtractor.create(recording, sorting, 'toy_waveforms')
we.set_params(ms_before=3., ms_after=4., max_spikes_per_unit=500)
we.run_extract_waveforms(n_jobs=1, chunk_size=30000)
pca = WaveformPrincipalComponent(we)
pca.set_params(n_components=5, mode='by_channel_local')
pca.run()
def test_WaveformPrincipalComponent():
we = WaveformExtractor.load_from_folder('toy_waveforms_2seg')
unit_ids = we.sorting.unit_ids
num_channels = we.recording.get_num_channels()
pc = WaveformPrincipalComponent(we)
for mode in ('by_channel_local', 'by_channel_global'):
pc.set_params(n_components=5, mode=mode)
print(pc)
pc.run()
for i, unit_id in enumerate(unit_ids):
proj = pc.get_projections(unit_id)
# print(comp.shape)
assert proj.shape[1:] == (5, 4)
# import matplotlib.pyplot as plt
# cmap = plt.get_cmap('jet', len(unit_ids))
# fig, axs = plt.subplots(ncols=num_channels)
# for i, unit_id in enumerate(unit_ids):
# comp = pca.get_components(unit_id)
# print(comp.shape)
# for chan_ind in range(num_channels):
# ax = axs[chan_ind]
# ax.scatter(comp[:, 0, chan_ind], comp[:, 1, chan_ind], color=cmap(i))
# plt.show()
for mode in ('concatenated',):
pc.set_params(n_components=5, mode=mode)
print(pc)
pc.run()
for i, unit_id in enumerate(unit_ids):
proj = pc.get_projections(unit_id)
assert proj.shape[1] == 5
# print(comp.shape)
all_labels, all_components = pc.get_all_components()
# relod as an extension from we
assert WaveformPrincipalComponent in we.get_available_extensions()
assert we.is_extension('principal_components')
pc = we.load_extension('principal_components')
assert isinstance(pc, WaveformPrincipalComponent)
pc = WaveformPrincipalComponent.load_from_folder('toy_waveforms_2seg')