def return_nearest_cutoff(name, mass_dict, freqs):
    """
    Given an array of total mass values and an (ascending) list of
    frequencies, this will calculate the specified cutoff formula for each
    mtotal and return the nearest frequency to each cutoff from the input
    list.
    Currently only supports cutoffs that are functions of the total mass
    and no other parameters (SchwarzISCO, LightRing, ERD)

    Parameters
    ----------
    name : string
        Name of the cutoff formula to be approximated
    mass_dict : Dictionary where the keys are used to call the functions
        returned by tmpltbank.named_frequency_cutoffs. The values can be
        numpy arrays or single values.
    freqs : list of floats
        A list of frequencies (must be sorted ascending)

    Returns
    -------
    numpy.array
        The frequencies closest to the cutoff for each value of totmass.
    """
    # A bypass for the redundant case
    if len(freqs) == 1:
        return numpy.zeros(len(mass_dict['m1']), dtype=float) + freqs[0]
    cutoff_fns = pnutils.named_frequency_cutoffs
    if name not in cutoff_fns.keys():
        err_msg = "%s not recognized as a valid cutoff frequency choice." %name
        err_msg += "Recognized choices: " + " ".join(cutoff_fns.keys())
        raise ValueError(err_msg)
    f_cutoff = cutoff_fns[name](mass_dict)
    return find_closest_calculated_frequencies(f_cutoff, freqs)