def test_eeg_absolute(self, subject, events_filename, expected_basenames):
path = resource_filename("cmlreaders.test.data", events_filename)
events = EventReader.fromfile(path)
reader = EEGReader("eeg", subject)
new_events = reader._eegfile_absolute(events)
for eegfile in new_events[
new_events["eegfile"].notnull()]["eegfile"].unique():
assert eegfile in expected_basenames
def test_load_with_empty_events(self):
sources_file = resource_filename("cmlreaders.test.data",
"sources.json")
with patch.object(PathFinder, "find", return_value=sources_file):
reader = EEGReader("eeg")
with pytest.raises(ValueError):
data = np.random.random((10, 10, 10))
with patch.object(RamulatorHDF5Reader,
"read",
return_value=[data, None]):
reader.load()
def test_rereference(self, reader_class, rerefable):
"""Test rereferencing without rhino by using known, fake data."""
if reader_class == SplitEEGReader:
eeg_path = self.to_split_eeg()
if reader_class == RamulatorHDF5Reader:
eeg_path = self.to_ramulator_hdf5(rerefable)
scheme = pd.DataFrame({
"contact_1": [1 + a for a in self.anodes],
"contact_2": [1 + c for c in self.cathodes],
"label": self.pair_labels,
})
with patch.object(PathFinder, "find", return_value=self.sources_path):
reader = EEGReader("eeg", subject="R1111M")
eeg = reader.load(events=self.events(str(eeg_path)),
rel_start=0,
rel_stop=self.data.shape[-1],
scheme=scheme)
assert_equal(eeg.data[0], self.reref_data)