def test_consistency_with_horizons(use_DE440s, obstime):
# Check that the high-accuracy Astropy ephemeris has been set
assert solar_system_ephemeris.get() == 'de440s'
# Check whether the location of Earth is the same between Astropy and JPL HORIZONS
e1 = get_earth(obstime)
e2 = get_horizons_coord('Geocenter', obstime)
assert_quantity_allclose(e2.separation_3d(e1), 0 * u.km, atol=50 * u.m)
# Check whether the location of Mars is the same between Astropy and JPL HORIZONS
e1 = get_body_heliographic_stonyhurst('mars', obstime)
e2 = get_horizons_coord('Mars barycenter', obstime)
assert_quantity_allclose(e2.separation_3d(e1), 0 * u.km, atol=500 * u.m)
def use_DE440s():
# This class is for test functions that need the Astropy ephemeris to be set to DE432s
pytest.importorskip("astroquery")
old_ephemeris = solar_system_ephemeris.get()
try:
solar_system_ephemeris.set('de440s')
except ValueError:
pytest.skip(
"The installed version of Astropy cannot set the ephemeris to DE440s"
)
yield
solar_system_ephemeris.set(old_ephemeris)
def astropy_ephemeris_de432s():
# Temporarily set Astropy's ephemeris to DE432s
old_ephemeris = solar_system_ephemeris.get()
solar_system_ephemeris.set('de432s')
yield solar_system_ephemeris.get()
solar_system_ephemeris.set(old_ephemeris)
def setup_class(cls):
cls.old_ephemeris = solar_system_ephemeris.get()
solar_system_ephemeris.set('de432s')
def do_stage(self, image) -> ObservationFrame:
if image.classification is None:
logger.warning('No classification to use for an RV template',
image=image)
return image
phoenix_loader = phoenix.PhoenixModelLoader(self.runtime_context)
template = phoenix_loader.load(image.classification)
# Pick orders near the center of the detector that have a high Signal to noise and are free of tellurics.
orders_to_use = np.arange(
self.runtime_context.MIN_ORDER_TO_CORRELATE,
self.runtime_context.MAX_ORDER_TO_CORRELATE + 1, 1)
rv_measured, rv_err, coarse_ccfs, ccfs = calculate_rv(
image, orders_to_use, template)
# Compute the barycentric RV and observing time corrections
rv_correction, bjd_tdb = barycentric_correction(
image.dateobs, image.exptime, image.ra, image.dec,
dbs.get_site(image.instrument.site,
self.runtime_context.db_address))
# Correct the RV per Wright & Eastman (2014) and save in the header
rv_correction += rv_measured * rv_correction / constants.c
rv = rv_measured + rv_correction
image.meta['RV'] = rv.to(
'm / s').value, 'Radial Velocity in Barycentric Frame [m/s]'
# The following assumes that the uncertainty on the barycentric correction is negligible w.r.t. that
# on the RV measured from the CCF, which should generally be true
image.meta['RVERR'] = rv_err.to(
'm / s').value, 'Radial Velocity Uncertainty [m/s]'
image.meta['BARYCORR'] = rv_correction.to(
'm / s').value, 'Barycentric Correction Applied to the RV [m/s]'
image.meta['TCORR'] = bjd_tdb.to_value(
'jd'), 'Exposure Mid-Time (Barycentric Julian Date)'
image.meta[
'TCORVERN'] = 'astropy.time.light_travel_time', 'Time correction code version'
# TODO: verify that the following are in fact the time corrections done by astropy;
# this isn't completely obvious from the online documentation
image.meta['TCORCOMP'] = 'ROMER, CLOCK', 'Time corrections done'
image.meta['TCOREPOS'] = 'ERFA', 'Source of Earth position'
image.meta[
'TCORSYST'] = 'BJD_TDB ', 'Ref. frame_timesystem of TCORR column'
image.meta['PLEPHEM'] = solar_system_ephemeris.get(
), 'Source of planetary ephemerides'
# save the fine + coarse ccfs together
# sort the coarse and fine ccf's
coarse_ccfs.sort('order')
ccfs.sort('order')
# remove entries from the coarse ccf's that fall within the velocity range of the fine ccf's
ccf_range = (np.min(ccfs['v'][0]), np.max(ccfs['v'][0]))
entries_to_keep = np.logical_or(coarse_ccfs['v'][0] < min(ccf_range),
coarse_ccfs['v'][0] > max(ccf_range))
coarse_ccfs['v'] = coarse_ccfs['v'][:, entries_to_keep]
coarse_ccfs['xcor'] = coarse_ccfs['xcor'][:, entries_to_keep]
#
final_ccfs = Table({
'order':
ccfs['order'],
'v':
np.hstack([coarse_ccfs['v'], ccfs['v']]),
'xcor':
np.hstack([coarse_ccfs['xcor'], ccfs['xcor']])
})
# sorting xcor by the velocity grid so that things are in order
sort_array = np.argsort(final_ccfs['v'][0])
final_ccfs['xcor'] = final_ccfs['xcor'][:, sort_array]
final_ccfs['v'] = final_ccfs['v'][:, sort_array]
image.add_or_update(DataTable(final_ccfs, name='CCF'))
return image
