def test_short_spiketrain(self):
# this spike train has the same length as anasig0
s1, f1 = sta.spike_field_coherence(
self.anasig0, self.bst3, window='boxcar')
# this spike train has the same spikes as above, but is shorter than
# anasig0
s2, f2 = sta.spike_field_coherence(
self.anasig0, self.bst4, window='boxcar')
# the results above should be the same, nevertheless
assert_array_equal(s1.magnitude, s2.magnitude)
assert_array_equal(f1.magnitude, f2.magnitude)
def test_non_binned_spiketrain_input(self):
s, f = sta.spike_field_coherence(self.anasig0, self.st0)
f_ind = np.where(f >= 19.)[0][0]
max_ind = np.argmax(s[1:]) + 1
self.assertEqual(f_ind, max_ind)
self.assertAlmostEqual(s[f_ind], 1., delta=0.01)
def test_spike_field_coherence_perfect_coherence(self):
# check for detection of 20Hz peak in anasig0/bst0
s, f = sta.spike_field_coherence(
self.anasig0, self.bst0, window='boxcar')
f_ind = np.where(f >= 19.)[0][0]
max_ind = np.argmax(s[1:]) + 1
self.assertEqual(f_ind, max_ind)
self.assertAlmostEqual(s[f_ind], 1., delta=0.01)
def test_signal_dimensions(self):
# single analogsignal trace and single spike train
s_single, f_single = sta.spike_field_coherence(self.anasig0, self.bst0)
self.assertEqual(len(f_single.shape), 1)
self.assertEqual(len(s_single.shape), 2)
# multiple analogsignal traces and single spike train
s_multi, f_multi = sta.spike_field_coherence(self.anasig4, self.bst0)
self.assertEqual(len(f_multi.shape), 1)
self.assertEqual(len(s_multi.shape), 2)
# frequencies are identical since same sampling frequency was used
# in both cases and data length is the same
assert_array_equal(f_single, f_multi)
# coherences of s_single and first signal in s_multi are identical,
# since first analogsignal trace in anasig4 is same as in anasig0
assert_array_equal(s_single[:, 0], s_multi[:, 0])
def test_output_frequencies(self):
nfft = 256
_, f = sta.spike_field_coherence(self.anasig3, self.bst1, nfft=nfft)
# check number of frequency samples
self.assertEqual(len(f), nfft / 2 + 1)
# check values of frequency samples
assert_array_almost_equal(
f, np.linspace(
0, self.anasig3.sampling_rate.rescale('Hz').magnitude / 2,
nfft / 2 + 1) * pq.Hz)
def test_output_frequencies(self):
nfft = 256
_, f = sta.spike_field_coherence(self.anasig3, self.bst1, nfft=nfft)
# check number of frequency samples
self.assertEqual(len(f), nfft / 2 + 1)
f_max = self.anasig3.sampling_rate.rescale('Hz').magnitude / 2
f_ground_truth = np.linspace(start=0,
stop=f_max,
num=nfft // 2 + 1) * pq.Hz
# check values of frequency samples
assert_array_almost_equal(f, f_ground_truth)
def test_spike_field_coherence_perfect_coherence(self):
# check for detection of 20Hz peak in anasig0/bst0
with warnings.catch_warnings():
warnings.simplefilter("ignore")
"""
When the spiketrain is a vector with zero values, ignore the
warning RuntimeWarning: invalid value encountered in true_divide
Cxy = np.abs(Pxy)**2 / Pxx / Pyy.
"""
s, f = sta.spike_field_coherence(
self.anasig0, self.bst0, window='boxcar')
f_ind = np.where(f >= 19.)[0][0]
max_ind = np.argmax(s[1:]) + 1
self.assertEqual(f_ind, max_ind)
self.assertAlmostEqual(s[f_ind], 1., delta=0.01)
