def _get_standard_10_20_positions(raw_or_epoch=None, ordered_ch_names=None):
    """Returns standard 10-20 sensors position matrix (for instantiating
    SensorsRotation for example).

    Parameters
    ----------
    raw_or_epoch : mne.io.Raw | mne.Epoch, optional
        Example of raw or epoch to retrieve ordered channels list from. Need to
        be named as in 10-20. By default None.
    ordered_ch_names : list, optional
        List of strings representing the channels of the montage considered.
        The order has to be consistent with the order of channels in the input
        matrices that will be fed to `SensorsRotation` transform. By
        default None.
    """
    assert raw_or_epoch is not None or ordered_ch_names is not None, (
        "At least one of raw_or_epoch and ordered_ch_names is needed."
    )
    if ordered_ch_names is None:
        ordered_ch_names = raw_or_epoch.info["ch_names"]
    ten_twenty_montage = make_standard_montage("standard_1020")
    positions_dict = ten_twenty_montage.get_positions()["ch_pos"]
    positions_subdict = {
        k: positions_dict[k] for k in ordered_ch_names if k in positions_dict
    }
    return np.stack(list(positions_subdict.values())).T
Returns standard 10-20 sensors position matrix (for instantiating
    SensorsRotation for example).

    Parameters
    ----------
    raw_or_epoch : mne.io.Raw | mne.Epoch, optional
        Example of raw or epoch to retrieve ordered channels list from. Need to
        be named as in 10-20. By default None.
    ordered_ch_names : list, optional
        List of strings representing the channels of the montage considered.
        The order has to be consistent with the order of channels in the input
        matrices that will be fed to `SensorsRotation` transform. By
        default None.
    
braindecode/augmentation/transforms.py