def test_dr2_edr3():
"""
Test that both DR2 and eDR3 retrieval gives ballpark similar values for
beta Pic
"""
hip_num = '027321' # beta Pic
edr3_num = 4792774797545800832
dr2_number = 4792774797545105664
num_secondary_bodies = 1
path_to_iad_file = '{}HIP{}.d'.format(DATADIR, hip_num)
myHip = hipparcos.HipparcosLogProb(path_to_iad_file, hip_num,
num_secondary_bodies)
dr3Gaia = gaia.GaiaLogProb(edr3_num, myHip, dr='edr3')
dr2Gaia = gaia.GaiaLogProb(dr2_number, myHip, dr='dr2')
assert np.isclose(dr2Gaia.ra, dr3Gaia.ra,
atol=0.1) # abs tolerance in degrees
def test_valueerror():
"""
Check that if I don't say dr2 or edr3, I get a value error
"""
hip_num = '027321' # beta Pic
edr3_num = '4792774797545800832'
num_secondary_bodies = 1
path_to_iad_file = '{}HIP{}.d'.format(DATADIR, hip_num)
myHip = hipparcos.HipparcosLogProb(path_to_iad_file, hip_num,
num_secondary_bodies)
try:
myGaia = gaia.GaiaLogProb(edr3_num, myHip, dr='dr3')
assert False, 'Test failed!'
except ValueError:
pass
def test_save_and_load_gaia_and_hipparcos():
"""
Test that a Results object for a Gaia+Hipparcos fit
is saved and loaded properly.
"""
hip_num = '027321'
gaia_num = 4792774797545105664
num_secondary_bodies = 1
path_to_iad_file = '{}HIP{}.d'.format(DATADIR, hip_num)
myHip = hipparcos.HipparcosLogProb(path_to_iad_file, hip_num,
num_secondary_bodies)
myGaia = gaia.GaiaLogProb(gaia_num, myHip)
input_file = os.path.join(DATADIR, 'betaPic.csv')
data_table_with_rvs = read_input.read_file(input_file)
mySys = system.System(1,
data_table_with_rvs,
1.22,
56.95,
mass_err=0.08,
plx_err=0.26,
hipparcos_IAD=myHip,
gaia=myGaia,
fit_secondary_mass=True)
mySamp = sampler.MCMC(mySys, num_temps=1, num_walkers=50)
mySamp.run_sampler(1, burn_steps=0)
save_name = 'test_results.h5'
mySamp.results.save_results(save_name)
loadedResults = results.Results()
loadedResults.load_results(save_name)
assert np.all(loadedResults.system.hipparcos_IAD.epochs ==
mySys.hipparcos_IAD.epochs)
assert np.all(loadedResults.system.tau_ref_epoch == mySys.tau_ref_epoch)
assert np.all(loadedResults.system.gaia.ra == mySys.gaia.ra)
os.system('rm {}'.format(save_name))
def test_system_setup():
"""
Test that a System object with Hipparcos and Gaia is initialized correctly
"""
hip_num = '027321' # beta Pic
edr3_num = '4792774797545800832'
num_secondary_bodies = 1
path_to_iad_file = '{}HIP{}.d'.format(DATADIR, hip_num)
myHip = hipparcos.HipparcosLogProb(path_to_iad_file, hip_num,
num_secondary_bodies)
myGaia = gaia.GaiaLogProb(edr3_num, myHip, dr='edr3')
input_file = os.path.join(DATADIR, 'betaPic.csv')
plx = 51.5
num_secondary_bodies = 1
data_table = read_input.read_file(input_file)
betaPic_system = system.System(num_secondary_bodies,
data_table,
1.75,
plx,
hipparcos_IAD=myHip,
gaia=myGaia,
fit_secondary_mass=True,
mass_err=0.01,
plx_err=0.01)
assert betaPic_system.labels == [
'sma1', 'ecc1', 'inc1', 'aop1', 'pan1', 'tau1', 'plx', 'pm_ra',
'pm_dec', 'alpha0', 'delta0', 'm1', 'm0'
]
assert betaPic_system.fit_secondary_mass
assert betaPic_system.track_planet_perturbs
data_table = read_input.read_file(filename)
print(data_table)
# system parameters
num_secondary_bodies = 1
hipparcos_number = hip_num
hipparcos_filename = IAD_file
# HIP logprob
HD142527_Hip = hipparcos.HipparcosLogProb(hipparcos_filename,
hipparcos_number,
num_secondary_bodies)
# gaia logprob
HD142527_edr3_number = 5994826707951507200
HD142527_Gaia = gaia.GaiaLogProb(HD142527_edr3_number,
HD142527_Hip,
dr='edr3')
# more system parameters
m0 = 2.05 # [Msol]
plx = 6.35606723729484 # [mas]
fit_secondary_mass = True
mass_err = 0.5 # [Msol]
plx_err = 0.04714455423 # [mas]
HD142527_system = system.System(num_secondary_bodies,
data_table,
m0,
plx,
hipparcos_IAD=HD142527_Hip,
def test_orbit_calculation():
"""
Test that the Gaia module correctly calculates log likelihood
for simulated astrometric motion due to:
1) proper motion only
2) fitted offset in Hipparcos positon only
3) orbital motion only
NOTE: this only works as long as lnlike is defined as (data - model) in
the Gaia module (i.e. no constant offset term applied), since
I'm checking that the absolute likelihood probability is 1 when data =
model.
"""
sma = 1
ecc = 0
inc = 0
aop = 0
pan = 0
tau = 0
pm_a = 0
pm_d = 0
plx = 100 # [mas]
m0 = 1
m1 = 1
a0 = 0
d0 = 0
hip_num = '027321' # beta Pic
edr3_num = '4792774797545800832'
num_secondary_bodies = 1
path_to_iad_file = '{}HIP{}.d'.format(DATADIR, hip_num)
myHip = hipparcos.HipparcosLogProb(path_to_iad_file, hip_num,
num_secondary_bodies)
myGaia = gaia.GaiaLogProb(edr3_num, myHip, dr='edr3')
param_idx = {
'sma1': 0,
'ecc1': 1,
'inc1': 2,
'aop1': 3,
'pan1': 4,
'tau1': 5,
'plx': 6,
'm0': 7,
'm1': 8,
'alpha0': 9,
'delta0': 10,
'pm_ra': 11,
'pm_dec': 12
}
# Case 1: only proper motion explains Gaia-Hip offset
pm_a = 100 # [mas/yr]
pm_d = 100 # [mas/yr]
sma = 1e-17
raoff = np.zeros((2, 1))
deoff = np.zeros((2, 1))
myGaia.ra = myHip.alpha0 + (myGaia.mas2deg * pm_a *
(myGaia.gaia_epoch - myGaia.hipparcos_epoch) /
np.cos(np.radians(myHip.delta0)))
myGaia.dec = myHip.delta0 + (myGaia.mas2deg * pm_d *
(myGaia.gaia_epoch - myGaia.hipparcos_epoch))
test_samples = [
sma, ecc, inc, aop, pan, tau, plx, m0, m1, a0, d0, pm_a, pm_d
]
lnlike = myGaia.compute_lnlike(raoff, deoff, test_samples, param_idx)
assert np.isclose(np.exp(lnlike), 1)
# Case 2: only H0 offset explains Gaia-Hip offset
test_samples[param_idx['pm_dec']] = 0
test_samples[param_idx['pm_ra']] = 0
a0 = 100
d0 = 100
test_samples[param_idx['alpha0']] = a0 # [mas]
test_samples[param_idx['delta0']] = d0 # [mas]
myGaia.ra = myHip.alpha0 + myGaia.mas2deg * a0 / np.cos(
np.radians(myHip.delta0))
myGaia.dec = myHip.delta0 + myGaia.mas2deg * d0
lnlike = myGaia.compute_lnlike(raoff, deoff, test_samples, param_idx)
assert np.isclose(np.exp(lnlike), 1)
# Case 3: only orbital motion explains Gaia-Hip offset
test_samples[param_idx['alpha0']] = 0
test_samples[param_idx['delta0']] = 0
mas2arcsec = 1e-3
deg2arcsec = 3600
myGaia.ra = myHip.alpha0
myGaia.dec = myHip.delta0 + 1
sma = 2 * (myGaia.dec - myHip.delta0) * deg2arcsec * (plx * mas2arcsec
) # [au]
per = 2 * (myGaia.gaia_epoch - myGaia.hipparcos_epoch) # [yr]
mtot = sma**3 / per**2
test_samples[param_idx['sma1']] = sma
test_samples[param_idx['m0']] = mtot / 2
test_samples[param_idx['m1']] = mtot / 2
# passes through peri (+sma decl for e=0 orbits) at Hipparcos epoch
# -> @ Gaia epoch, primary should be at +sma decl
tau = basis.tp_to_tau(myGaia.hipparcos_epoch, 58849, per)
test_samples[param_idx['tau1']] = tau
# choose sma and mass so that Hipparcos/Gaia difference is only due to orbit.
deoff[1, :] = (myGaia.dec - myHip.delta0) / myGaia.mas2deg
deoff[0, :] = 0
lnlike = myGaia.compute_lnlike(raoff, deoff, test_samples, param_idx)
assert np.isclose(np.exp(lnlike), 1)