def test_waveforms_arange_single_spiketrain(self):
target_snr = 0.9
waveforms = np.arange(20).reshape((2, 1, 10))
snr_float = waveform_features.waveform_snr(waveforms)
self.assertIsInstance(snr_float, float)
self.assertEqual(snr_float, target_snr)
self.assertEqual(waveform_features.waveform_snr(np.squeeze(waveforms)),
target_snr)
def test_zero_waveforms(self):
zero_waveforms = [np.zeros((5, 10)),
np.zeros((5, 1, 10)),
np.zeros((5, 3, 10))]
for zero_wf in zero_waveforms:
with self.assertWarns(UserWarning):
# expect np.nan result when waveform noise is zero.
result = waveform_features.waveform_snr(zero_wf)
self.assertTrue(np.all(np.isnan(result)))
def test_waveforms_arange_multiple_spiketrains(self):
target_snr = [0.3, 0.3, 0.3]
waveforms = np.arange(60).reshape((2, 3, 10))
snr_arr = waveform_features.waveform_snr(waveforms)
self.assertIsInstance(snr_arr, np.ndarray)
assert_array_almost_equal(snr_arr, target_snr)
def test_with_waveforms(self):
target_value = 0.9
result = waveform_features.waveform_snr(self.spiketrain_with_waveforms)
self.assertEqual(result, target_value)
def test_with_zero_waveforms(self):
with self.assertWarns(UserWarning):
# expect np.nan result when spiketrain noise is zero.
result = waveform_features.waveform_snr(
self.spiketrain_with_zero_waveforms)
self.assertTrue(np.isnan(result))
def test_with_waveforms(self):
target_value = 0.9
result = waveform_features.waveform_snr(
self.spiketrain_with_waveforms)
self.assertEqual(result, target_value)
def test_with_zero_waveforms(self):
result = waveform_features.waveform_snr(
self.spiketrain_with_zero_waveforms)
self.assertTrue(np.isnan(result))