Remove results with small number of samples.
        If n is small (==1), reject the result

    Parameters
    ----------
    taus: array
        List of tau values for which deviation were computed
    devs: array
        List of deviations
    deverrs: array or list of arrays
        List of estimated errors (possibly a list containing two arrays :
        upper and lower values)
    ns: array
        Number of samples for each point

    Returns
    -------
    (taus, devs, deverrs, ns): tuple
        Identical to input, except that values with low ns have been removed.

def remove_small_ns(taus, devs, deverrs, ns):
    """ Remove results with small number of samples.
        If n is small (==1), reject the result

    Parameters
    ----------
    taus: array
        List of tau values for which deviation were computed
    devs: array
        List of deviations
    deverrs: array or list of arrays
        List of estimated errors (possibly a list containing two arrays :
        upper and lower values)
    ns: array
        Number of samples for each point

    Returns
    -------
    (taus, devs, deverrs, ns): tuple
        Identical to input, except that values with low ns have been removed.

    """
    ns_big_enough = ns > 1

    o_taus = taus[ns_big_enough]
    o_devs = devs[ns_big_enough]
    o_ns = ns[ns_big_enough]
    if isinstance(deverrs, list):
        assert len(deverrs) < 3
        o_deverrs = [deverrs[0][ns_big_enough], deverrs[1][ns_big_enough]]
    else:
        o_deverrs = deverrs[ns_big_enough]
    if len(o_devs)==0:
        print("remove_small_ns() nothing remains!?")
        raise UserWarning
         
    return o_taus, o_devs, o_deverrs, o_ns