def METHOD_NAME(self):
    temp_estimate = 47. * u.K
    vgas = 0.8 * u.km / u.s
    aper = 30 * u.m
    b = 1.13
    mol_tag = 27001
    transition_freq = (265.886434 * u.GHz).to('MHz')
    mol_tag = 'co'
    t_freq = (157.178987 * u.GHz).to('MHz')
    lgint300 = 7.4336139*10**(-5) * u.MHz * u.nm * u.nm
    part300 = 9473.271845042498
    partition = 308.5479509730844
    gu = 11.0
    energy_J = 6.61822698*10**(-22) * u.J
    elo_J = 5.57674801*10**(-22) * u.J
    df = 3
    integrated_flux = 0.672 * u.K * u.km / u.s
    quantities = [t_freq, temp_estimate, lgint300, part300, partition, gu, energy_J,
                  elo_J, df, mol_tag]
    names = ['t_freq', 'temp', 'lgint300', 'partfn300', 'partfn',
             'dgup', 'eup_J', 'elo_J', 'degfreedom', 'mol_tag']
    mol_data = Phys.from_dict(dict(zip(names, quantities)))
    intl = intensity_conversion(mol_data)
    mol_data.apply([intl.value] * intl.unit, name='intl')
    au = einstein_coeff(mol_data)
    mol_data.apply([au.value] * au.unit, name='eincoeff')
    r = 1.06077567 * u.AU
    delta = 0.14633757 * u.AU
    quanteph = [r, delta]
    nameseph = ['r', 'delta']
    ephemobj = Ephem.from_dict(dict(zip(nameseph, quanteph)))
    lte = LTE()
    q = lte.from_Drahus(integrated_flux, mol_data, ephemobj, vgas, aper, b=b)
    q = np.log10(q.value)
    assert np.isclose(q, 27.3167, rtol=0.01)