def get_mnu0_data(filename, configs, return_3p=False, **kwargs):
    """Import data post-processed as 3P data (NMU0), i.e., measured towards
    common ground.

    Parameters
    ----------
    filename : string (usually: eit_data_mnu0.mat)
        filename of matlab file
    configs : Nx4 numpy.ndarray|filename|function
        4P measurements configurations (ABMN) to generate out of the data. If
        this parameter is a callable, then call it with the MD DataFrame as its
        sole parameter and expect a Nx4 numpy.ndarray as return value
    return_3p : bool, optional
        also return 3P data
    **kwargs : dict, optional
        all other parameters will be handled down to the extract functions

    Returns
    -------
    data_emd_4p : pandas.DataFrame
        The generated 4P data
    data_md_raw : pandas.DataFrame|None
        MD data (sometimes this data is not imported, then we return None here)
    data_emd_3p : pandas.DataFrame
        The imported 3P data (only if return_3p==True)
    """
    if not os.path.isfile(filename):
        print('File not found: {}'.format(filename))
        exit()
    version = _get_file_version(filename)
    importer = mat_version_importers.get(version, None)
    if importer is not None:
        mat = sio.loadmat(filename, squeeze_me=True)
        data_md_raw = importer._extract_md(mat, **kwargs)
        data_emd_3p = importer._extract_emd(mat, **kwargs)

        # check configs
        if callable(configs):
            configs_abmn = configs(data_md_raw)
        else:
            configs_abmn = configs

        if data_emd_3p is not None:
            data_emd_4p = compute_quadrupoles(data_emd_3p, configs_abmn)
        else:
            data_emd_4p = None
    else:
        raise Exception(
            'The file version "{}" is not supported yet.'.format(
                version)
        )

    if return_3p:
        return data_emd_4p, data_md_raw, data_emd_3p
    else:
        return data_emd_4p, data_md_raw