ab1e700e55f26fca141c2439ddcc52316dde9e19,autoreject/tests/test_autoreject.py,,test_autoreject,#,29

Before Change

        epochs.load_data()
        assert_raises(ValueError, compute_thresholds, epochs, "dfdfdf")
        for method in ["random_search", "bayesian_optimization"]:
            compute_thresholds(epochs, picks=picks, method=method)

After Change

        mne.pick_types(epochs.info, meg="mag", eeg=False)[::30],
        mne.pick_types(epochs.info, meg="grad", eeg=False)[::60],
        mne.pick_types(epochs.info, meg=False, eeg=True)[::16],
        mne.pick_types(epochs.info, meg=False, eeg=False, eog=True)]
    pick_ch_names = [epochs.ch_names[pp] for pp in pre_picks]
    epochs.pick_channels(pick_ch_names)
    epochs_fit = epochs[:10]

Instances