def METHOD_NAME(epoch, func, freq_sl, average, *, output="power"):
    """Aux function."""
    # Decide if we should split this to save memory or not, since doing
    # multiple calls will incur some performance overhead. Eventually we might
    # want to write (really, go back to) our own spectrogram implementation
    # that, if possible, averages after each transform, but this will incur
    # a lot of overhead because of the many Python calls required.
    kwargs = dict(func=func, average=average, freq_sl=freq_sl)
    if epoch.nbytes > 10e6:
        spect = np.apply_along_axis(_decomp_aggregate_mask, -1, epoch, **kwargs)
    else:
        spect = _decomp_aggregate_mask(epoch, **kwargs)
    return spect