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_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_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
print(
"Done! This fit took {:.1f} mins on my machine.".format(duration_mins))
### ACTUAL ORBITIZE ###
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]
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)
def test_with_hip_iad():
'''
Make sure the labels are generated correctly for all of the basis sets for the configuration of
the driver where Hipparcos data is supplied. Again, for the XYZ basis, expect there to be errors thrown.
'''
filename = "{}/betaPic.csv".format(DATADIR)
hip_num = '027321'
hipp_filename = "{}/HIP{}.d".format(DATADIR, hip_num)
num_secondary_bodies = 1
system_mass = 1.75
mass_err = 0
plx = 51.44
plx_err = 0.12
myHip = hipparcos.HipparcosLogProb(hipp_filename, hip_num,
num_secondary_bodies)
hip_labels = ['pm_ra', 'pm_dec', 'alpha0', 'delta0']
for basis in basis_names:
if basis != 'SemiAmp':
expected_labels = [item + '1' for item in basis_names[basis]
] + ['plx'] + hip_labels + ['m1', 'm0']
else:
expected_labels = [item + '1' for item in basis_names[basis]
] + ['plx'] + hip_labels + ['m0']
if basis == 'XYZ': # Should throw an error for XYZ basis
with pytest.raises(Exception) as excinfo:
my_driver = driver.Driver(filename,
'MCMC',
num_secondary_bodies,
system_mass,
plx,
mass_err=mass_err,
plx_err=plx_err,
system_kwargs={
'fit_secondary_mass': True,
'tau_ref_epoch': 0,
'hipparcos_IAD': myHip,
'fitting_basis': basis
})
assert str(
excinfo.value
) == "For now, the XYZ basis requires data in RA and DEC offsets."
else:
my_driver = driver.Driver(filename,
'MCMC',
num_secondary_bodies,
system_mass,
plx,
mass_err=mass_err,
plx_err=plx_err,
system_kwargs={
'fit_secondary_mass': True,
'tau_ref_epoch': 0,
'hipparcos_IAD': myHip,
'fitting_basis': basis
})
assert expected_labels == my_driver.system.labels