def test_Hip1_fit_to_hip70000():
# Hip 70000 parameters from the intermediate data
cntr_ra, cntr_dec = Angle(214.85975459, 'degree'), Angle(14.93570946, 'degree')
plx = 1.26 # mas
pmRA = 1.01 # mas/year
pmDec = 7.27 # mas/year
# generate fitter and parse intermediate data
astro = Astrometry('Hip1', '70000', 'htof/test/data_for_tests/Hip1', central_epoch_ra=1991.25,
central_epoch_dec=1991.25, format='jyear', fit_degree=1, use_parallax=True,
central_ra=cntr_ra, central_dec=cntr_dec)
chisq = np.sum(astro.data.residuals ** 2 / astro.data.along_scan_errs ** 2)
# generate ra and dec for each observation.
year_epochs = Time(astro.data.julian_day_epoch(), format='jd', scale='tcb').jyear - \
Time(1991.25, format='decimalyear').jyear
ra_motion = astro.fitter.parallactic_pertubations['ra_plx']
dec_motion = astro.fitter.parallactic_pertubations['dec_plx']
ra = Angle(ra_motion * plx + pmRA * year_epochs, unit='mas')
dec = Angle(dec_motion * plx + pmDec * year_epochs, unit='mas')
# add residuals
ra += Angle(astro.data.residuals.values * np.sin(astro.data.scan_angle.values), unit='mas')
dec += Angle(astro.data.residuals.values * np.cos(astro.data.scan_angle.values), unit='mas')
#
coeffs, errors, chisq_found, residuals_found = astro.fit(ra.mas, dec.mas, return_all=True)
assert np.isclose(chisq, chisq_found, atol=1E-3)
assert np.allclose([pmRA, pmDec], np.array([coeffs[3], coeffs[4]]).round(2))
assert np.isclose(plx, coeffs[0].round(2), atol=0.01)
assert np.allclose(errors.round(2), np.array([1.11, 0.79, 0.62, 0.82, 0.64]))
def test_Hip2_fit_to_hip27321():
# Hip 27321 parameters from the Hipparcos 21 IAD
cntr_ra, cntr_dec = Angle(86.82118073, 'degree'), Angle(-51.06671341, 'degree')
plx = 51.44 # mas
pmRA = 4.65 # mas/year
pmDec = 83.10 # mas/year
# generate fitter and parse intermediate data
for datadir in ['Hip2', 'Hip21']:
# trying fits with a fresh computation of the parallax factors and without
astro = Astrometry('hip2or21', '27321', f'htof/test/data_for_tests/{datadir}', central_epoch_ra=1991.25,
central_epoch_dec=1991.25, format='jyear', fit_degree=1, use_parallax=True,
central_ra=cntr_ra, central_dec=cntr_dec,
use_catalog_parallax_factors=True)
chisq = np.sum(astro.data.residuals ** 2 / astro.data.along_scan_errs ** 2)
# generate ra and dec for each observation.
year_epochs = Time(astro.data.julian_day_epoch(), format='jd', scale='tcb').jyear - \
Time(1991.25, format='decimalyear').jyear
ra_motion = astro.fitter.parallactic_pertubations['ra_plx']
dec_motion = astro.fitter.parallactic_pertubations['dec_plx']
ra = Angle(ra_motion * plx + pmRA * year_epochs, unit='mas')
dec = Angle(dec_motion * plx + pmDec * year_epochs, unit='mas')
# add residuals
ra += Angle(astro.data.residuals.values * np.sin(astro.data.scan_angle.values), unit='mas')
dec += Angle(astro.data.residuals.values * np.cos(astro.data.scan_angle.values), unit='mas')
#
coeffs, errors, chisq_found, residuals = astro.fit(ra.mas, dec.mas, return_all=True)
residuals = to_along_scan_basis(residuals[:, 0], residuals[:, 1], astro.data.scan_angle.values)
assert np.isclose(chisq, chisq_found, atol=1E-3)
assert np.allclose([pmRA, pmDec], np.array([coeffs[3], coeffs[4]]).round(2))
assert np.isclose(plx, coeffs[0].round(2), atol=0.01)
assert np.allclose(errors.round(2), np.array([0.12, 0.10, 0.11, 0.11, 0.15]), atol=0.01)
assert np.allclose(residuals, astro.data.residuals.values, atol=0.02)
def test_Gaia_fit_to_hip27321():
# Hip 27321 central ra and dec from the gost data file.
cntr_ra, cntr_dec = Angle(1.5153157780177544, 'radian'), Angle(-0.8912787619608181, 'radian')
#
plx = 51.87 # mas
pmRA = 4.65 # mas/year
pmDec = 81.96 # mas/year
# generate fitter and parse intermediate data
for use_catalog_parallax_factors in [False, True]:
print('not '* (not use_catalog_parallax_factors) + 'using catalog parallax factors.')
# trying fits with a fresh computation of the parallax factors and without
astro = Astrometry('GaiaEDR3', '27321', 'htof/test/data_for_tests/GaiaeDR3',
central_epoch_ra=2016, central_epoch_dec=2016,
format='jyear', fit_degree=1, use_parallax=True,
central_ra=cntr_ra, central_dec=cntr_dec,
use_catalog_parallax_factors=use_catalog_parallax_factors)
chisq = np.sum(astro.data.residuals ** 2 / astro.data.along_scan_errs ** 2)
# generate ra and dec for each observation.
year_epochs = Time(astro.data.julian_day_epoch(), format='jd', scale='tcb').jyear - \
Time(2016, format='decimalyear').jyear
ra_motion = astro.fitter.parallactic_pertubations['ra_plx']
dec_motion = astro.fitter.parallactic_pertubations['dec_plx']
ra = Angle(ra_motion * plx + pmRA * year_epochs, unit='mas')
dec = Angle(dec_motion * plx + pmDec * year_epochs, unit='mas')
#
coeffs, errors, chisq_found, residuals = astro.fit(ra.mas, dec.mas, return_all=True)
residuals = to_along_scan_basis(residuals[:, 0], residuals[:, 1], astro.data.scan_angle.values)
assert np.isclose(chisq, chisq_found, atol=1E-3)
assert np.allclose([pmRA, pmDec], np.array([coeffs[3], coeffs[4]]).round(2))
assert np.isclose(plx, coeffs[0].round(2), atol=0.01)
def initialize_data(config):
# load in items from the ConfigParser object
HipID = config.getint('data_paths', 'HipID', fallback=0)
RVFile = config.get('data_paths', 'RVFile')
AstrometryFile = config.get('data_paths', 'AstrometryFile')
GaiaDataDir = config.get('data_paths', 'GaiaDataDir', fallback=None)
Hip2DataDir = config.get('data_paths', 'Hip2DataDir', fallback=None)
Hip1DataDir = config.get('data_paths', 'Hip1DataDir', fallback=None)
use_epoch_astrometry = config.getboolean('mcmc_settings',
'use_epoch_astrometry',
fallback=False)
#
data = orbit.Data(HipID, RVFile, AstrometryFile)
if use_epoch_astrometry:
Gaia_fitter = Astrometry('GaiaDR2',
'%06d' % (HipID),
GaiaDataDir,
central_epoch_ra=data.epRA_G,
central_epoch_dec=data.epDec_G,
central_epoch_fmt='frac_year')
Hip2_fitter = Astrometry('Hip2',
'%06d' % (HipID),
Hip2DataDir,
central_epoch_ra=data.epRA_H,
central_epoch_dec=data.epDec_H,
central_epoch_fmt='frac_year')
Hip1_fitter = Astrometry('Hip1',
'%06d' % (HipID),
Hip1DataDir,
central_epoch_ra=data.epRA_H,
central_epoch_dec=data.epDec_H,
central_epoch_fmt='frac_year')
# instantiate C versions of the astrometric fitter which are must faster than HTOF's Astrometry
hip1_fast_fitter = orbit.AstrometricFitter(Hip1_fitter)
hip2_fast_fitter = orbit.AstrometricFitter(Hip2_fitter)
gaia_fast_fitter = orbit.AstrometricFitter(Gaia_fitter)
data = orbit.Data(HipID,
RVFile,
AstrometryFile,
use_epoch_astrometry,
epochs_Hip1=Hip1_fitter.data.julian_day_epoch(),
epochs_Hip2=Hip2_fitter.data.julian_day_epoch(),
epochs_Gaia=Gaia_fitter.data.julian_day_epoch())
else:
hip1_fast_fitter, hip2_fast_fitter, gaia_fast_fitter = None, None, None
return data, hip1_fast_fitter, hip2_fast_fitter, gaia_fast_fitter
def test_parallax_factors_independent_of_reference_epoch(self):
astron = Astrometry('Hip1', '27321', 'htof/test/data_for_tests/Hip1', central_epoch_ra=2000,
central_epoch_dec=2000, format='jyear', fit_degree=1, use_parallax=True,
central_ra=self.cntr_ra, central_dec=self.cntr_dec)
ra_motionn = astron.fitter.parallactic_pertubations['ra_plx']
dec_motionn = astron.fitter.parallactic_pertubations['dec_plx']
assert np.allclose(to_along_scan_basis(self.ra_motion, self.dec_motion, self.scan_angle),
to_along_scan_basis(ra_motionn, dec_motionn, self.scan_angle))
def test_optimal_central_epochs_forHip1_hip27321_no_parallax():
astro = Astrometry('Hip1', '27321', 'htof/test/data_for_tests/Hip1', central_epoch_ra=1991.25,
central_epoch_dec=1991.25, format='jyear', fit_degree=1,
use_parallax=False)
central_epoch = astro.optimal_central_epochs()
central_epoch_ra, central_epoch_dec = central_epoch['ra'], central_epoch['dec']
#print(central_epoch_ra, central_epoch_dec)
fitter = astro.fitter
cov_matrix = fitter.evaluate_cov_matrix(central_epoch_ra, central_epoch_dec)
ra_mura_cov, dec_mudec_cov = cov_matrix[0, 2], cov_matrix[1, 3]
# do a brute force evaluation of all reasonable central epochs
epoch_t = np.linspace(1991, 1992, 200)
ra_vals, dec_vals = [], []
for t in epoch_t:
cov = fitter.evaluate_cov_matrix(t, t)
ra_vals.append(cov[0, 2])
dec_vals.append(cov[1, 3])
# assert that the optimal central epochs give better covariances than all of those.
assert np.all(np.abs(dec_vals) >= dec_mudec_cov)
assert np.all(np.abs(ra_vals) >= ra_mura_cov)
assert np.allclose([dec_mudec_cov, ra_mura_cov], 0, atol=1e-9)
def test_Hip1_fit_to_hip27321_no_parallax():
# WARNING including the parallax component is important if you want to recover the catalog errors.
# Hip 27321 parameters from the Hipparcos 1 catalogue via Vizier
pmRA = 4.65 # mas/year
pmDec = 81.96 # mas/year
# generate fitter and parse intermediate data
astro = Astrometry('Hip1', '27321', 'htof/test/data_for_tests/Hip1', central_epoch_ra=1991.25,
central_epoch_dec=1991.25, format='jyear', fit_degree=1,
use_parallax=False)
chisq = np.sum(astro.data.residuals ** 2 / astro.data.along_scan_errs ** 2)
# generate ra and dec for each observation.
year_epochs = Time(astro.data.julian_day_epoch(), format='jd', scale='tcb').jyear - \
Time(1991.25, format='decimalyear').jyear
ra = Angle(pmRA * year_epochs, unit='mas')
dec = Angle(pmDec * year_epochs, unit='mas')
# add residuals
ra += Angle(astro.data.residuals.values * np.sin(astro.data.scan_angle.values), unit='mas')
dec += Angle(astro.data.residuals.values * np.cos(astro.data.scan_angle.values), unit='mas')
#
coeffs, errors, chisq_found, residuals_found = astro.fit(ra.mas, dec.mas, return_all=True)
assert np.isclose(chisq, chisq_found, atol=1E-3)
assert np.allclose([pmRA, pmDec], np.array([coeffs[2], coeffs[3]]).round(2))
assert np.allclose(errors.round(2), np.array([0.45, 0.46, 0.53, 0.61]), atol=0.01)
def test_optimal_central_epochs_forHip1_hip27321():
# Hip 27321 parameters from the Hipparcos 1 catalogue via Vizier
cntr_ra, cntr_dec = Angle(86.82118054, 'degree'), Angle(-51.06671341, 'degree')
# generate fitter and parse intermediate data
astro = Astrometry('Hip1', '27321', 'htof/test/data_for_tests/Hip1', central_epoch_ra=1991.25,
central_epoch_dec=1991.25, format='jyear', fit_degree=1, use_parallax=True,
central_ra=cntr_ra, central_dec=cntr_dec)
central_epoch = astro.optimal_central_epochs()
central_epoch_ra, central_epoch_dec = central_epoch['ra'], central_epoch['dec']
#print(central_epoch_ra, central_epoch_dec)
fitter = astro.fitter
cov_matrix = fitter.evaluate_cov_matrix(central_epoch_ra, central_epoch_dec)
ra_mura_cov, dec_mudec_cov = cov_matrix[1, 3], cov_matrix[2, 4]
# do a brute force evaluation of all reasonable central epochs
epoch_t = np.linspace(1991, 1992, 200)
ra_vals, dec_vals = [], []
for t in epoch_t:
cov = fitter.evaluate_cov_matrix(t, t)
ra_vals.append(cov[1, 3])
dec_vals.append(cov[2, 4])
# assert that the optimal central epochs give better covariances than all of those.
assert np.all(np.abs(dec_vals) >= dec_mudec_cov)
assert np.all(np.abs(ra_vals) >= ra_mura_cov)
assert np.allclose([dec_mudec_cov, ra_mura_cov], 0, atol=1e-8)
class TestParallaxFactorsGaia:
"""
Tests the computation of the parallax factors anew, as well as tests the basis transformations from along-scan
to ra and dec.
"""
# Hip 27321 parameters from the Gaia EDR3 archive.
cntr_ra, cntr_dec = Angle(86.82123452009108, 'degree'), Angle(-51.066136257823345, 'degree')
# generate fitter and parse intermediate data
astro = Astrometry('Gaiaedr3', '27321', 'htof/test/data_for_tests/GaiaeDR3', central_epoch_ra=2016,
central_epoch_dec=2016, format='jyear', fit_degree=1, use_parallax=True,
central_ra=cntr_ra, central_dec=cntr_dec)
ra_motion = astro.fitter.parallactic_pertubations['ra_plx']
dec_motion = astro.fitter.parallactic_pertubations['dec_plx']
along_scan_parallax_factors = astro.data.parallax_factors.values
scan_angle = astro.data.scan_angle.values
def test_new_computed_parallax_factors_agree_with_scanninglaw(self):
# test that the newly computed parallax factors agree with
# parallaxFactorAlongScan from the GOST data.
assert np.allclose(self.along_scan_parallax_factors,
to_along_scan_basis(self.ra_motion, self.dec_motion, self.scan_angle), atol=0.03)
class TestParallaxFactors:
"""
Tests the computation of the parallax factors anew, as well as tests the basis transformations from along-scan
to ra and dec.
"""
# Hip 27321 parameters from the Hipparcos 1 catalogue via Vizier
cntr_ra, cntr_dec = Angle(86.82118054, 'degree'), Angle(-51.06671341, 'degree')
# generate fitter and parse intermediate data
astro = Astrometry('Hip1', '27321', 'htof/test/data_for_tests/Hip1', central_epoch_ra=1991.25,
central_epoch_dec=1991.25, format='jyear', fit_degree=1, use_parallax=True,
central_ra=cntr_ra, central_dec=cntr_dec)
ra_motion = astro.fitter.parallactic_pertubations['ra_plx']
dec_motion = astro.fitter.parallactic_pertubations['dec_plx']
along_scan_parallax_factors = astro.data.parallax_factors.values
scan_angle = astro.data.scan_angle.values
def test_new_computed_parallax_factors_agree_with_catalog(self):
assert np.allclose(self.along_scan_parallax_factors,
to_along_scan_basis(self.ra_motion, self.dec_motion, self.scan_angle), atol=0.03)
def test_parallax_factors_backward_transform(self):
# note that this is redundant with test_basis_change_consistency()
ra_motion, dec_motion = to_ra_dec_basis(self.along_scan_parallax_factors, self.scan_angle)
# convert the calculated parallax factors to the along-scan basis and back to null out the AC component.
al_parallax_factor = to_along_scan_basis(self.ra_motion, self.dec_motion, self.scan_angle)
ra_motion_acnull, dec_motion_acnull = to_ra_dec_basis(al_parallax_factor, self.scan_angle)
assert np.allclose(ra_motion, ra_motion_acnull, atol=0.03)
assert np.allclose(dec_motion, dec_motion_acnull, atol=0.03)
def test_parallax_factors_independent_of_reference_epoch(self):
astron = Astrometry('Hip1', '27321', 'htof/test/data_for_tests/Hip1', central_epoch_ra=2000,
central_epoch_dec=2000, format='jyear', fit_degree=1, use_parallax=True,
central_ra=self.cntr_ra, central_dec=self.cntr_dec)
ra_motionn = astron.fitter.parallactic_pertubations['ra_plx']
dec_motionn = astron.fitter.parallactic_pertubations['dec_plx']
assert np.allclose(to_along_scan_basis(self.ra_motion, self.dec_motion, self.scan_angle),
to_along_scan_basis(ra_motionn, dec_motionn, self.scan_angle))
def initialize_data(config, companion_gaia):
# load in items from the ConfigParser object
HipID = config.getint('data_paths', 'HipID', fallback=0)
HGCAFile = config.get('data_paths', 'HGCAFile')
if not os.path.exists(HGCAFile):
raise FileNotFoundError(f'No HGCA file found at {HGCAFile}')
try:
table = fits.open(HGCAFile)[1].data
epoch_ra_gaia = table[table['hip_id'] == 1]['epoch_ra_gaia']
if np.isclose(epoch_ra_gaia, 2015.60211565):
HGCAVersion = 'GaiaDR2'
elif np.isclose(epoch_ra_gaia, 2015.92749023):
HGCAVersion = 'GaiaeDR3'
else:
raise ValueError(
"Cannot match %s to either DR2 or eDR3 based on RA epoch of Gaia"
% (HGCAFile))
except:
raise ValueError("Cannot access HIP 1 in HGCA file" + HGCAFile)
RVFile = config.get('data_paths', 'RVFile', fallback='')
AstrometryFile = config.get('data_paths', 'AstrometryFile', fallback='')
GaiaDataDir = config.get('data_paths', 'GaiaDataDir', fallback='')
Hip2DataDir = config.get('data_paths', 'Hip2DataDir', fallback='')
Hip1DataDir = config.get('data_paths', 'Hip1DataDir', fallback='')
use_epoch_astrometry = config.getboolean('mcmc_settings',
'use_epoch_astrometry',
fallback=False)
data = orbit.Data(HipID,
HGCAFile,
RVFile,
AstrometryFile,
companion_gaia=companion_gaia)
if use_epoch_astrometry and data.use_abs_ast == 1:
# TODO verify that this half-day should indeed be here. This doesnt matter for ~10 year orbits,
# but would matter if we wanted to fit companions with shorter orbital arcs.
to_jd = lambda x: Time(x, format='decimalyear').jd + 0.5
Gaia_fitter = Astrometry(HGCAVersion,
'%06d' % (HipID),
GaiaDataDir,
central_epoch_ra=to_jd(data.epRA_G),
central_epoch_dec=to_jd(data.epDec_G),
format='jd')
Hip2_fitter = Astrometry('Hip2',
'%06d' % (HipID),
Hip2DataDir,
central_epoch_ra=to_jd(data.epRA_H),
central_epoch_dec=to_jd(data.epDec_H),
format='jd')
Hip1_fitter = Astrometry('Hip1',
'%06d' % (HipID),
Hip1DataDir,
central_epoch_ra=to_jd(data.epRA_H),
central_epoch_dec=to_jd(data.epDec_H),
format='jd')
# instantiate C versions of the astrometric fitter which are much faster than HTOF's Astrometry
#print(Gaia_fitter.fitter.astrometric_solution_vector_components['ra'])
hip1_fast_fitter = orbit.AstrometricFitter(Hip1_fitter)
hip2_fast_fitter = orbit.AstrometricFitter(Hip2_fitter)
gaia_fast_fitter = orbit.AstrometricFitter(Gaia_fitter)
data = orbit.Data(HipID,
HGCAFile,
RVFile,
AstrometryFile,
use_epoch_astrometry,
epochs_Hip1=Hip1_fitter.data.julian_day_epoch(),
epochs_Hip2=Hip2_fitter.data.julian_day_epoch(),
epochs_Gaia=Gaia_fitter.data.julian_day_epoch(),
companion_gaia=companion_gaia,
verbose=False)
elif data.use_abs_ast == 1:
hip1_fast_fitter, hip2_fast_fitter, gaia_fast_fitter = None, None, None
else:
hip1_fast_fitter, hip2_fast_fitter, gaia_fast_fitter = None, None, None
try:
data.plx = 1e-3 * config.getfloat('priors_settings', 'parallax')
data.plx_err = 1e-3 * config.getfloat('priors_settings',
'parallax_error')
except:
print("Cannot load absolute astrometry.")
print("Please supply a prior for parallax and parallax_error")
print("in the priors_settings area of the configuration file.")
return data, hip1_fast_fitter, hip2_fast_fitter, gaia_fast_fitter