def calc_point_dist_vary(mus1, fUpper1, mus2, fUpper2, fMap, norm_map, MMdistA
    ):
    """
    Function to determine if two points, with differing upper frequency cutoffs
    have a mismatch < MMdistA for *both* upper frequency cutoffs.

    Parameters
    ----------
    mus1 : List of numpy arrays
        mus1[i] will give the array of point 1's position in the \\chi_j
        coordinate system. The i element corresponds to varying values of the
        upper frequency cutoff. fMap is used to map between i and actual
        frequencies
    fUpper1 : float
        The upper frequency cutoff of point 1.
    mus2 : List of numpy arrays
        mus2[i] will give the array of point 2's position in the \\chi_j
        coordinate system. The i element corresponds to varying values of the
        upper frequency cutoff. fMap is used to map between i and actual
        frequencies
    fUpper2 : float
        The upper frequency cutoff of point 2.
    fMap : dictionary
        fMap[fUpper] will give the index needed to get the \\chi_j coordinates
        in the two sets of mus
    norm_map : dictionary
        norm_map[fUpper] will give the relative frequency domain template
        amplitude (sigma) at the given value of fUpper.
    MMdistA
        The minimal mismatch allowed between the points

    Returns
    --------
    Boolean
        True if the points have a mismatch < MMdistA
        False if the points have a mismatch > MMdistA
    """
    f_upper = min(fUpper1, fUpper2)
    f_other = max(fUpper1, fUpper2)
    idx = fMap[f_upper]
    vecs1 = mus1[idx]
    vecs2 = mus2[idx]
    val = ((vecs1 - vecs2) * (vecs1 - vecs2)).sum()
    if val > MMdistA:
        return False
    norm_fac = norm_map[f_upper] / norm_map[f_other]
    val = 1 - (1 - val) * norm_fac
    return val < MMdistA
