def test_isi_violations():
# 1. check value for fixed spike train parameters:
train1 = simulated_spike_train(100, 10, 10)
fpRate1, num_violations1 = isi_violations(train1, np.max(train1), 0.001)
assert np.isclose(fpRate1, 0.4901480247, rtol=0, atol=1e-5)
assert num_violations1 == 10
# 2. check that the value doesn't depend on recording duration:
train2 = simulated_spike_train(200, 10, 20)
fpRate2, num_violations2 = isi_violations(train2, np.max(train2), 0.001)
assert np.isclose(fpRate1, fpRate2, rtol=0, atol=1e-5)
# 3. check that the value increases with the number of violations:
train3 = simulated_spike_train(100, 10, 20)
fpRate3, num_violations3 = isi_violations(train3, np.max(train3), 0.001)
assert fpRate3 > fpRate1
# 4. check that the value decreases with a longer violation window:
fpRate4, num_violations4 = isi_violations(train1, np.max(train1), 0.002)
assert fpRate4 < fpRate1
# 5. check that the value decreases with firing rate:
train4 = simulated_spike_train(100, 20, 10)
fpRate5, num_violations5 = isi_violations(train4, np.max(train4), 0.001)
assert fpRate5 < fpRate1
def simulated_spike_times():
max_time = 100
trains = [simulated_spike_train(max_time, 10, 2),
simulated_spike_train(max_time, 5, 4),
simulated_spike_train(max_time, 5, 10)]
labels = [np.ones((len(trains[i]),), dtype='int') * i for i in range(len(trains))]
spike_times = np.concatenate(trains)
spike_clusters = np.concatenate(labels)
order = np.argsort(spike_times)
spike_times = spike_times[order]
spike_clusters = spike_clusters[order]
return {'spike_times': spike_times, 'spike_clusters': spike_clusters}
def test_firing_rate():
# 1. check that the output value is correct:
max_time = 100
simulated_firing_rate = 10.0
train = simulated_spike_train(max_time, simulated_firing_rate, 0)
assert firing_rate(train, duration=max_time) == simulated_firing_rate
# 2. check that widening the boundaries decreases the rate:
assert firing_rate(train, duration=100) > firing_rate(train, duration=200)
def test_presence_ratio(overall_duration, expected_value):
spike_times = simulated_spike_train(100, 20, 0)
assert presence_ratio(spike_times, 0, overall_duration) == expected_value