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Home Page: https://stardate.readthedocs.io/en/latest/index.html#
License: MIT License
Combining dating methods for better stellar ages
Home Page: https://stardate.readthedocs.io/en/latest/index.html#
License: MIT License
Allow users to set the priors from the list of priors built into isochrones.
Hi @RuthAngus!
I'm interested in using stardate
for a project I'm working on with fully-convective stars. I see in your paper's Discussion section that these stars perhaps shouldn't trusted with stardate
.ย I'm wondering if you could elaborate a bit on what circumstances need to be met to trust stardate
ages for fully-convective stars?
Thanks so much ๐
Add a tutorial to demonstrate how to do this.
I installed stardate on a new python=3.8 conda environment, following the instructions.
The following example MCMC fits from the readthedocs run fine (no error), but I am not getting the right results:
My code:
import stardate as sd
# Create a dictionary of observables
iso_params = {"teff": (4386, 50), # Teff with uncertainty.
"logg": (4.66, .05), # logg with uncertainty.
"feh": (0.0, .02), # Metallicity with uncertainty.
"parallax": (1.48, .1), # Parallax in milliarcseconds.
"maxAV": .1} # Maximum extinction
prot, prot_err = 29, 3
# Set up the star object.
star = sd.Star(iso_params, prot=prot, prot_err=prot_err) # Here's where you add a rotation period
# Run the MCMC
star.fit(max_n=1000)
# max_n is the maximum number of MCMC samples. I recommend setting this
# much higher when running for real, or using the default value of 100000.
# Print the median age with the 16th and 84th percentile uncertainties.
age, errp, errm, samples = star.age_results()
print("stellar age = {0:.2f} + {1:.2f} + {2:.2f}".format(age, errp, errm))
I get as an output 0.42 + 0.32 + 3.37 rather than 2.97 + 0.60 + 0.55, and the bias towards low stellar ages remains even for larger numbers of steps (10,000).
When directly calling the Praesepe model to get period from age or age from period however, I am getting the expected values.
Another issue is that I am getting 3 failed tests when running pytest (see below).
platform darwin -- Python 3.8.13, pytest-7.1.2, pluggy-1.0.0
rootdir: /Users/caroline/Research/GitHub/stardate
collected 13 items
test/isochrone_test.py F [ 7%]
test/lhf_test.py ..F..F...... [100%]
============================================== FAILURES ===============================================
___________________________________________ test_iso_lnlike ___________________________________________
def test_iso_lnlike():
iso_params = {"teff": (5770, 10),
"feh": (0, .01),
"logg": (4.44, .1),
"parallax": (1, 1)}
mod = SingleStarModel(mist, **iso_params) # StarModel isochrones obj
params = [354, np.log10(4.56*1e9), 0., 1000, 0.]
lnparams = [354, np.log10(4.56*1e9), 0., np.log(1000), 0.]
lnpr = mod.lnprior(params)
# lnparams = [350, 9, 0., 6, 0.]
args1 = [mod, iso_params]
# Calculate the lnprob above
iso_lp = iso_lnprob(lnparams, *args1)
start = time.time()
for i in range(100):
iso_lp = iso_lnprob(lnparams, *args1)
end = time.time()
# Calculate the stardate lnprob
args2 = [mod, None, None, True, False, True, "praesepe"]
start = time.time()
for i in range(100):
lp = lnprob(lnparams, *args2)[0]
end = time.time()
# print("time = ", end - start)
ll = lnlike(lnparams, *args2)
lnprior = lp - ll
assert iso_lp == lp
assert np.isclose(iso_lp - lnpr, ll)
> assert lnpr == lnprior
E assert -18.46720822861122 == -18.46720822861107
test/isochrone_test.py:62: AssertionError
____________________________________________ test_calc_bv _____________________________________________
def test_calc_bv():
sun = [355, np.log10(4.56*1e9), 0., np.log(1000), 0.]
bv_sun = calc_bv(sun)
> assert .6 < bv_sun, "Are you sure you're on the isochrones eep branch?"
E AssertionError: Are you sure you're on the isochrones eep branch?
E assert 0.6 < 0.42834431703148956
test/lhf_test.py:92: AssertionError
_______________________________________ test_gyro_model_rossby ________________________________________
def test_gyro_model_rossby():
"""
Make sure that the rossby model gives Solar values for the Sun.
Make sure it gives a maximum rotation period of pmax.
"""
age = np.log10(4.56*1e9)
sun = [355, age, 0., np.log(1000), 0.]
# iso_params = {"teff": (5777, 10),
# "logg": (4.44, .05),
# "feh": (0., .001),
# "parallax": (1., .01), # milliarcseconds
# "B": (15.48, 0.02)}
# # Set up the StarModel isochrones object.
# mod = StarModel(mist, **iso_params)
# # the lnprob arguments]
# args = [mod, 26., 1., False, True, "praesepe"]
# print(lnprob(sun, *args))
# assert 0
prot_sun = 10**gyro_model_rossby(sun, model="praesepe")[0]
> assert 21 < prot_sun
E assert 21 < 6.909888089400217
test/lhf_test.py:142: AssertionError
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