def test_avg_firing_rate(self):
'''Test computation of the average firing rate.'''
# Test zero neurons
pop = PopulationSpikes(0, [], [])
rates = pop.avg_firing_rate(0, 1e3)
assert rates.size == 0
# Test one neuron
pop = PopulationSpikes(1, [0, 0, 0, 0], [0., 100, 200, 300])
rates = pop.avg_firing_rate(0, 1e3)
assert len(rates.shape) == 1
assert rates[0] == 4.
# Test two neurons
pop = PopulationSpikes(2, [0, 1, 0, 1, 0, 1, 0], [0., 50, 100, 150, 200,
250, 300])
rates = pop.avg_firing_rate(0, 1e3)
assert len(rates.shape) == 1
np.testing.assert_allclose(rates, [4., 3.])
# tend < tstart
pop = PopulationSpikes(2, [0, 1, 0, 1, 0, 1, 0], [0., 50, 100, 150, 200,
250, 300])
with pytest.raises(ValueError):
rates = pop.avg_firing_rate(1e3, 0)
def test_lists(self):
train_size = 100
n = 10
senders = list(np.random.randint(n, size=train_size * n))
times = list(np.random.rand(train_size * n))
sp = PopulationSpikes(n, senders, times)
# try to retrieve spike trains
for nIdx in range(n):
train = sp[nIdx]
assert train is not None
# Try to run all the methods, None should raise an exception
sp.avg_firing_rate(0, 1)
sp.sliding_firing_rate(0, 1, 0.05, 0.1)
sp.windowed((0, 1))
sp.raster_data()
sp.spike_train_difference(list(range(n)))
