def test_functions():
rec, sort = se.example_datasets.toy_example(duration=10, num_channels=4, seed=0)
firing_rates = compute_firing_rates(sort, seed=0)[0]
num_spikes = compute_num_spikes(sort, seed=0)[0]
isi = compute_isi_violations(sort, seed=0)[0]
presence = compute_presence_ratios(sort, seed=0)[0]
amp_cutoff = compute_amplitude_cutoffs(sort, rec, seed=0)[0]
max_drift, cum_drift = compute_drift_metrics(sort, rec, seed=0, memmap=False)[0]
silh = compute_silhouette_scores(sort, rec, seed=0)[0]
iso = compute_isolation_distances(sort, rec, seed=0)[0]
l_ratio = compute_l_ratios(sort, rec, seed=0)[0]
dprime = compute_d_primes(sort, rec, seed=0)[0]
nn_hit, nn_miss = compute_nn_metrics(sort, rec, seed=0)[0]
snr = compute_snrs(sort, rec, seed=0)[0]
metrics = compute_metrics(sort, rec, return_dict=True, seed=0)
assert np.allclose(metrics['firing_rate'][0], firing_rates)
assert np.allclose(metrics['num_spikes'][0], num_spikes)
assert np.allclose(metrics['isi_viol'][0], isi)
assert np.allclose(metrics['amplitude_cutoff'][0], amp_cutoff)
assert np.allclose(metrics['presence_ratio'][0], presence)
assert np.allclose(metrics['silhouette_score'][0], silh)
assert np.allclose(metrics['isolation_distance'][0], iso)
assert np.allclose(metrics['l_ratio'][0], l_ratio)
assert np.allclose(metrics['d_prime'][0], dprime)
assert np.allclose(metrics['snr'][0], snr)
assert np.allclose(metrics['max_drift'][0], max_drift)
assert np.allclose(metrics['cumulative_drift'][0], cum_drift)
assert np.allclose(metrics['nn_hit_rate'][0], nn_hit)
assert np.allclose(metrics['nn_miss_rate'][0], nn_miss)
def test_thresh_silhouettes():
rec, sort = se.example_datasets.toy_example(dump_folder='test',
dumpable=True,
duration=10,
num_channels=4,
K=10,
seed=0)
silhouette_thresh = .5
silhouette = compute_silhouette_scores(sort,
rec,
apply_filter=False,
seed=0)
sort_silhouette = threshold_silhouette_scores(sort,
rec,
silhouette_thresh,
"less",
apply_filter=False,
seed=0)
original_ids = sort.get_unit_ids()
new_silhouette = []
for unit in sort_silhouette.get_unit_ids():
new_silhouette.append(silhouette[original_ids.index(unit)])
new_silhouette = np.array(new_silhouette)
assert np.all(new_silhouette >= silhouette_thresh)
check_dumping(sort_silhouette)
shutil.rmtree('test')
def test_thresh_silhouettes():
rec, sort = se.example_datasets.toy_example(duration=10,
num_channels=4,
seed=0)
silhouette_thresh = .5
_ = threshold_silhouette_scores(sort, rec, silhouette_thresh, "less")
silhouette = np.asarray(compute_silhouette_scores(sort, rec)[0])
new_silhouette = silhouette[np.where(silhouette >= silhouette_thresh)]
assert np.all(new_silhouette >= silhouette_thresh)
def test_functions():
rec, sort = se.example_datasets.toy_example(duration=10, num_channels=4)
firing_rates = compute_firing_rates(sort)
num_spikes = compute_num_spikes(sort)
isi = compute_isi_violations(sort)
presence = compute_presence_ratios(sort)
amp_cutoff = compute_amplitude_cutoffs(sort, rec)
max_drift, cum_drift = compute_drift_metrics(sort, rec)
silh = compute_silhouette_scores(sort, rec)
iso = compute_isolation_distances(sort, rec)
l_ratio = compute_l_ratios(sort, rec)
dprime = compute_d_primes(sort, rec)
nn_hit, nn_miss = compute_nn_metrics(sort, rec)
snr = compute_snrs(sort, rec)
