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')