diff --git a/astroquery/jplhorizons/tests/test_jplhorizons_remote.py b/astroquery/jplhorizons/tests/test_jplhorizons_remote.py index 74d8c927fe..518e50222f 100644 --- a/astroquery/jplhorizons/tests/test_jplhorizons_remote.py +++ b/astroquery/jplhorizons/tests/test_jplhorizons_remote.py @@ -23,16 +23,16 @@ def test_ephemerides_query(self): ) res = horizons.ephemerides(quantities=quantities) - # Retrieved 2023 Aug 01: + # Rereshed 2024 Apr 09 via {k: res[k][0] for k in res.colnames} values = { - "targetname": "1 Ceres (A801 AA)", - "H": 3.33, - "G": 0.120, - "datetime_jd": 2451544.5, + 'targetname': "1 Ceres (A801 AA)", "datetime_str": "2000-Jan-01 00:00:00.000", + "datetime_jd": 2451544.5, + "H": 3.34 * u.mag, + "G": 0.12, "solar_presence": "*", "lunar_presence": "", - "RA": 188.70240 * u.deg, + "RA": 188.7024 * u.deg, "DEC": 9.09758 * u.deg, "RA_app": 188.69858 * u.deg, "DEC_app": 9.09806 * u.deg, @@ -48,20 +48,20 @@ def test_ephemerides_query(self): "siderealtime": 22.8737254836 * u.hr, "airmass": 999, "magextinct": np.ma.masked, - "V": 8.259 * u.mag, - "surfbright": 6.799 * u.mag / u.arcsec**2, + "V": 8.269 * u.mag, + "surfbright": 6.832 * u.mag / u.arcsec**2, "illumination": 96.17086 * u.percent, - "illum_defect": 0.0225 * u.arcsec, + "illum_defect": 0.0227 * u.arcsec, "sat_sep": 343433.5 * u.arcsec, "sat_vis": "*", - "ang_width": 0.587419 * u.arcsec, - "PDObsLon": 302.274926 * u.deg, - "PDObsLat": -3.982640 * u.deg, - "PDSunLon": 279.670960 * u.deg, - "PDSunLat": -3.621151 * u.deg, + "ang_width": 0.593755 * u.arcsec, + "PDObsLon": 301.942894 * u.deg, + "PDObsLat": -4.073159 * u.deg, + "PDSunLon": 279.338807 * u.deg, + "PDSunLat": -3.704743 * u.deg, "SubSol_ang": 112.55 * u.deg, "SubSol_dist": 0.11 * u.arcsec, - "NPole_ang": 22.6777 * u.deg, + "NPole_ang": 22.6751 * u.deg, "NPole_dist": -0.271 * u.arcsec, "EclLon": 161.3828 * u.deg, "EclLat": 10.4528 * u.deg, @@ -77,7 +77,7 @@ def test_ephemerides_query(self): "alpha": 22.5696 * u.deg, "lunar_elong": 32.9 * u.deg, "lunar_illum": 27.4882 * u.percent, - "sat_alpha": 62.0400 * u.deg, + "sat_alpha": 62.04 * u.deg, "sunTargetPA": 292.552 * u.deg, "velocityPA": 296.849 * u.deg, "OrbPlaneAng": -1.53489 * u.deg, @@ -85,30 +85,30 @@ def test_ephemerides_query(self): "TDB-UT": 64.183887 * u.s, "ObsEclLon": 184.3424861 * u.deg, "ObsEclLat": 11.7988212 * u.deg, - "NPole_RA": 291.42763 * u.deg, - "NPole_DEC": 66.76033 * u.deg, + "NPole_RA": 291.418 * u.deg, + "NPole_DEC": 66.764 * u.deg, "GlxLon": 289.863376 * u.deg, - "GlxLat": 71.544870 * u.deg, - "solartime": 16.1587871790 * u.hour, + "GlxLat": 71.54487 * u.deg, + "solartime": 16.158787179 * u.hour, "earth_lighttime": 0.000354 * u.minute, - "RA_3sigma": 0.000 * u.arcsec, - "DEC_3sigma": 0.000 * u.arcsec, + "RA_3sigma": 0.0 * u.arcsec, + "DEC_3sigma": 0.0 * u.arcsec, "SMAA_3sigma": 0.00012 * u.arcsec, - "SMIA_3sigma": 0.00005 * u.arcsec, + "SMIA_3sigma": 5e-05 * u.arcsec, "Theta_3sigma": -24.786 * u.deg, - "Area_3sigma": 0.0000000 * u.arcsec**2, - "RSS_3sigma": 0.000 * u.arcsec, + "Area_3sigma": 0.0 * u.arcsec**2, + "RSS_3sigma": 0.0 * u.arcsec, "r_3sigma": 0.0904 * u.km, - "r_rate_3sigma": 0.0000000 * u.km / u.s, - "SBand_3sigma": 0.00 * u.Hz, - "XBand_3sigma": 0.00 * u.Hz, - "DoppDelay_3sigma": 0.000001 * u.s, + "r_rate_3sigma": 0.0 * u.km / u.s, + "SBand_3sigma": 0.0 * u.Hz, + "XBand_3sigma": 0.0 * u.Hz, + "DoppDelay_3sigma": 1e-06 * u.s, "true_anom": 7.1181 * u.deg, "hour_angle": 10.293820034 * u.hour, "alpha_true": 22.5691 * u.deg, "PABLon": 172.8355 * u.deg, "PABLat": 11.3478 * u.deg, - "App_Lon_Sun": 309.1603680 * u.deg, + "App_Lon_Sun": 309.1190962 * u.deg, "RA_ICRF_app": 188.70238 * u.deg, "DEC_ICRF_app": 9.09628 * u.deg, "RA_ICRF_rate_app": 35.17809 * u.arcsec / u.hour, @@ -121,20 +121,17 @@ def test_ephemerides_query(self): } # the ephemeris changes with Ceres's and the planets' orbital elements, - # which can be updated at any time, so only check for 0.1% tolerance, this + # which can be updated at any time, so only check for 10% tolerance, this # is enough to verify that most columns are not being confused, and that # units are correct for column, value in values.items(): if isinstance(value, (u.Quantity, Angle)): - # A few columns have varied a lot more than the others - if column in ["H", "G", "V", "surfbright"]: - rtol = 0.1 - else: - rtol = 0.001 - assert u.isclose(res[column], value, rtol=rtol) + assert u.isclose(res[column], value, rtol=0.1) elif value is np.ma.masked: assert is_masked(res[column]) + elif isinstance(value, (float, int)): + assert np.isclose(res[column], value, rtol=0.1) else: assert res[column] == value