def test_returns_discretization_bins(self):
start = 2.0 * pq.s
stop = 5.0 * pq.s
sampling_rate = 2.0 * pq.Hz
expected = sp.array([2.0, 2.5, 3.0, 3.5, 4.0, 4.5, 5.0]) * pq.s
st = create_empty_spike_train(start, stop)
_, bins = sigproc.st_convolve(st,
sigproc.GaussianKernel(),
sampling_rate=sampling_rate)
assert_array_almost_equal(expected, bins)
def test_length_of_returned_array_equals_sampling_rate_times_duration(
self):
start = 2.0 * pq.s
stop = 5.0 * pq.s
duration = stop - start
sampling_rate = 12 * pq.Hz
expected_length = (sampling_rate * duration).simplified
st = create_empty_spike_train(start, stop)
result, _ = sigproc.st_convolve(st,
sigproc.GaussianKernel(),
sampling_rate=sampling_rate)
self.assertEqual(expected_length, result.size)
def test_convolution_with_empty_spike_train_returns_array_of_zeros(self):
st = create_empty_spike_train()
result, _ = sigproc.st_convolve(st, sigproc.GaussianKernel(),
1 * pq.Hz)
self.assertTrue(sp.all(result == 0.0))
def test_length_of_returned_array_equals_length_of_binned(self):
binned = sp.ones(10)
sampling_rate = 10 * pq.Hz
result = sigproc.smooth(binned, sigproc.GaussianKernel(),
sampling_rate)
self.assertEqual(binned.size, result.size)
def test_convolution_with_empty_binned_array_returns_array_of_zeros(self):
binned = sp.zeros(10)
sampling_rate = 10 * pq.Hz
result = sigproc.smooth(binned, sigproc.GaussianKernel(),
sampling_rate)
self.assertTrue(sp.all(result == 0.0))
def setUp(self):
self.kernel_size = 500 * pq.ms
self.kernel = sigproc.GaussianKernel(self.kernel_size)