Load sEIT data from data directory. This function loads data previously
    exported from reda using reda.exporters.crtomo.write_files_to_directory

    Parameters
    ----------
    directory : string
        input directory
    frequency_file : string, optional
        file (located in directory) that contains the frequencies
    data_prefix: string, optional
        for each frequency a corresponding data file must be present in the
        input directory. Frequencies and files are matched by sorting the
        frequencies AND the filenames, retrieved using glob and the
        data_prefix

    Returns
    -------
    df : pandas.DataFrame
        A DataFrame suitable for the sEIT container
    electrodes : None
        No electrode data is imported
    topography : None
        No topography data is imported

def load_seit_data(directory, frequency_file='frequencies.dat',
                   data_prefix='volt_', **kwargs):
    """Load sEIT data from data directory. This function loads data previously
    exported from reda using reda.exporters.crtomo.write_files_to_directory

    Parameters
    ----------
    directory : string
        input directory
    frequency_file : string, optional
        file (located in directory) that contains the frequencies
    data_prefix: string, optional
        for each frequency a corresponding data file must be present in the
        input directory. Frequencies and files are matched by sorting the
        frequencies AND the filenames, retrieved using glob and the
        data_prefix

    Returns
    -------
    df : pandas.DataFrame
        A DataFrame suitable for the sEIT container
    electrodes : None
        No electrode data is imported
    topography : None
        No topography data is imported

    """
    frequencies = np.loadtxt(directory + os.sep + frequency_file)
    data_files = sorted(glob(directory + os.sep + data_prefix + '*'))
    # check that the number of frequencies matches the number of data files
    if frequencies.size != len(data_files):
        raise Exception(
            'number of frequencies does not match number of data files')

    # load data
    data_list = []
    for frequency, filename in zip(frequencies, data_files):
        subdata = load_mod_file(filename)
        subdata['frequency'] = frequency
        data_list.append(subdata)
    df = pd.concat(data_list)
    return df, None, None