def anomalous_signals(hklin):
    """
    Compute some measures of anomalous signal: df / f and di / sig(di).
    """
    from iotbx import mtz
    m = mtz.object(hklin)
    mas = m.as_miller_arrays()
    data = None
    for ma in mas:
        if not ma.anomalous_flag():
            continue
        if str(ma.observation_type()) != 'xray.intensity':
            continue
        data = ma
    if not data:
        raise RuntimeError('no data found')
    df_f = data.anomalous_signal()
    differences = data.anomalous_differences()
    di_sigdi = sum(abs(differences.data())) / sum(differences.sigmas())
    return df_f, di_sigdi
