def rungtd1d(time: Union[datetime, str, np.ndarray],
             altkm: np.ndarray,
             glat: float, glon: float) -> xarray.Dataset:
    """
    This is the "atomic" function looped by other functions
    """
    time = todt64(time)
    # %% get solar parameters for date
    f107Ap = gi.getApF107(time, smoothdays=81)
    f107a = f107Ap['f107s'].item()
    f107 = f107Ap['f107'].item()
    Ap = f107Ap['Ap'].item()
# %% dimensions
    altkm = np.atleast_1d(altkm)
    assert altkm.ndim == 1
    assert isinstance(glon, (int, float))
    assert isinstance(glat, (int, float))
    assert isinstance(time, np.datetime64) or (time.size == 1 and isinstance(
        time[0], np.datetime64)), 'if you have multiple times, for loop over them'

# don't check ap, too complicated
    assert isinstance(MASS, (float, int))
    assert len(TSELECOPS) == 25
# %%
    gtd7.tselec(TSELECOPS)  # like the msis_driver example

    iyd, utsec, stl = datetime2gtd(time, glon)
    altkm = np.atleast_1d(altkm)

    gtd7.meters(1)  # makes output in m^-3 and kg/m^-3
# %%
    if isinstance(Ap, (float, int)):
        Ap = [Ap]*7  # even if SW(9) == 1 due to f2py needs for array

    dens = np.empty((altkm.size, len(species)))
    temp = np.empty((altkm.size, len(ttypes)))
    for i, a in enumerate(altkm):
        dens[i, :], temp[i, :] = gtd7.gtd7(iyd, utsec, a, glat, glon, stl, f107a, f107, Ap, MASS)

    dsf = {k: (('time', 'alt_km', 'lat', 'lon'), v[None, :, None, None]) for (k, v) in zip(species, dens.T)}
    dsf.update({'Tn':  (('time', 'alt_km', 'lat', 'lon'), temp[:, 1][None, :, None, None]),
                'Texo': (('time', 'alt_km', 'lat', 'lon'), temp[:, 0][None, :, None, None])})

    atmos = xarray.Dataset(dsf,
                           coords={'time': time.astype(datetime), 'alt_km': altkm, 'lat': [glat], 'lon': [glon], },
                           attrs={'Ap': Ap, 'f107': f107, 'f107a': f107a,
                                  'species': species})

    return atmos