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_threshold_drift_metrics():
rec, sort = se.example_datasets.toy_example(dump_folder='test', dumpable=True, duration=10, num_channels=4, K=10,
seed=0)
s_threshold = 1
sort_max = threshold_drift_metrics(sort, rec, s_threshold, 'greater', metric_name="max_drift",
apply_filter=False, seed=0)
sort_cum = threshold_drift_metrics(sort, rec, s_threshold, 'greater', metric_name="cumulative_drift",
apply_filter=False, seed=0)
new_max_drift, _ = compute_drift_metrics(sort_max, rec, apply_filter=False, seed=0)
_, new_cum_drift = compute_drift_metrics(sort_cum, rec, apply_filter=False, seed=0)
assert np.all(new_max_drift <= s_threshold)
assert np.all(new_cum_drift <= s_threshold)
check_dumping(sort_max)
check_dumping(sort_cum)
shutil.rmtree('test')
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)