def set_up():
rng = np.random.RandomState(42)
info = mne.create_info(ch_names=['0', '1'], sfreq=50, ch_types='eeg')
raw = mne.io.RawArray(data=rng.randn(2, 1000), info=info)
desc = pd.Series({'pathological': True, 'gender': 'M', 'age': 48})
base_dataset = BaseDataset(raw, desc, target_name='age')
events = np.array([[100, 0, 1],
[200, 0, 2],
[300, 0, 1],
[400, 0, 4],
[500, 0, 3]])
window_idxs = [(0, 0, 100),
(0, 100, 200),
(1, 0, 100),
(2, 0, 100),
(2, 50, 150)]
i_window_in_trial, i_start_in_trial, i_stop_in_trial = list(
zip(*window_idxs))
metadata = pd.DataFrame(
{'sample': events[:, 0],
'x': events[:, 1],
'target': events[:, 2],
'i_window_in_trial': i_window_in_trial,
'i_start_in_trial': i_start_in_trial,
'i_stop_in_trial': i_stop_in_trial})
mne_epochs = mne.Epochs(raw=raw, events=events, metadata=metadata)
windows_dataset = WindowsDataset(mne_epochs, desc)
return raw, base_dataset, mne_epochs, windows_dataset, events, window_idxs
def test_windows_dataset_from_target_channels_raise_valuerror():
with pytest.raises(ValueError):
WindowsDataset(None, None, targets_from='non-existing')