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import pymc3 as pm
import aesara_theano_fallback.tensor as tt
import pymc3_ext as pmx
from celerite2.theano import terms, GaussianProcess
with pm.Model() as model:
# Stellar parameters
mean = pm.Normal("mean", mu=0.0, sigma=10.0)
u = xo.QuadLimbDark("u")
star_params = [mean, u]
# Gaussian process noise model
sigma = pm.InverseGamma("sigma", alpha=3.0, beta=2 * np.median(yerr))
log_sigma_gp = pm.Normal("log_sigma_gp", mu=0.0, sigma=10.0)
log_rho_gp = pm.Normal("log_rho_gp", mu=np.log(10.0), sigma=10.0)
kernel = terms.SHOTerm(
sigma=tt.exp(log_sigma_gp), rho=tt.exp(log_rho_gp), Q=1.0 / 3
)
noise_params = [sigma, log_sigma_gp, log_rho_gp]
# Planet parameters
log_ror = pm.Normal(
"log_ror", mu=0.5 * np.log(depth_guess * 1e-3), sigma=10.0
)
ror = pm.Deterministic("ror", tt.exp(log_ror))
# Orbital parameters
log_period = pm.Normal("log_period", mu=np.log(period_guess), sigma=1.0)
period = pm.Deterministic("period", tt.exp(log_period))
t0 = pm.Normal("t0", mu=t0_guess, sigma=1.0)
log_dur = pm.Normal("log_dur", mu=np.log(0.1), sigma=10.0)
dur = pm.Deterministic("dur", tt.exp(log_dur))
b = xo.distributions.ImpactParameter("b", ror=ror)
# Set up the orbit
orbit = xo.orbits.KeplerianOrbit(period=period, duration=dur, t0=t0, b=b)
# We're going to track the implied density for reasons that will become clear later
pm.Deterministic("rho_circ", orbit.rho_star)
# Set up the mean transit model
star = xo.LimbDarkLightCurve(u)
lc_model = mean + 1e3 * tt.sum(
star.get_light_curve(orbit=orbit, r=ror, t=x), axis=-1
)
# Finally the GP observation model
gp = GaussianProcess(kernel, t=x, diag=yerr**2 + sigma**2)
gp.marginal("obs", observed=y - lc_model)
# Double check that everything looks good - we shouldn't see any NaNs!
print(model.check_test_point())
# Optimize the model
map_soln = model.test_point
map_soln = pmx.optimize(map_soln, [sigma])
map_soln = pmx.optimize(map_soln, [ror, b, dur])
map_soln = pmx.optimize(map_soln, noise_params)
map_soln = pmx.optimize(map_soln, star_params)
map_soln = pmx.optimize(map_soln)
produces this error
Output exceeds the size limit. Open the full output data in a text editor
FileNotFoundError Traceback (most recent call last)
Cell In[5], line 54
51 gp.marginal("obs", observed=y - lc_model)
53 # Double check that everything looks good - we shouldn't see any NaNs!
---> 54 print(model.check_test_point())
56 # Optimize the model
57 map_soln = model.test_point
File /opt/anaconda3/envs/rmeffect/lib/python3.8/site-packages/pymc3/model.py:1384, in Model.check_test_point(self, test_point, round_vals)
1380 if test_point is None:
1381 test_point = self.test_point
1383 return Series(
-> 1384 {RV.name: np.round(RV.logp(test_point), round_vals) for RV in self.basic_RVs},
1385 name="Log-probability of test_point",
1386 )
File /opt/anaconda3/envs/rmeffect/lib/python3.8/site-packages/pymc3/model.py:1384, in (.0)
1380 if test_point is None:
1381 test_point = self.test_point
1383 return Series(
-> 1384 {RV.name: np.round(RV.logp(test_point), round_vals) for RV in self.basic_RVs},
1385 name="Log-probability of test_point",
1386 )
...
--> 454 for f in os.listdir(d.strip('"')):
455 if f.endswith(".so") or f.endswith(".dylib") or f.endswith(".dll"):
456 if any([f.find(ll) >= 0 for ll in l]):
FileNotFoundError: [Errno 2] No such file or directory: '/usr/local/lib'
Your setup (please complete the following information):
To Reproduce
Running this portion of the transit fitting example code (https://gallery.exoplanet.codes/tutorials/quick-tess/)
import pymc3 as pm
import aesara_theano_fallback.tensor as tt
import pymc3_ext as pmx
from celerite2.theano import terms, GaussianProcess
with pm.Model() as model:
# Stellar parameters
mean = pm.Normal("mean", mu=0.0, sigma=10.0)
u = xo.QuadLimbDark("u")
star_params = [mean, u]
produces this error
Output exceeds the size limit. Open the full output data in a text editor
FileNotFoundError Traceback (most recent call last)
Cell In[5], line 54
51 gp.marginal("obs", observed=y - lc_model)
53 # Double check that everything looks good - we shouldn't see any NaNs!
---> 54 print(model.check_test_point())
56 # Optimize the model
57 map_soln = model.test_point
File /opt/anaconda3/envs/rmeffect/lib/python3.8/site-packages/pymc3/model.py:1384, in Model.check_test_point(self, test_point, round_vals)
1380 if test_point is None:
1381 test_point = self.test_point
1383 return Series(
-> 1384 {RV.name: np.round(RV.logp(test_point), round_vals) for RV in self.basic_RVs},
1385 name="Log-probability of test_point",
1386 )
File /opt/anaconda3/envs/rmeffect/lib/python3.8/site-packages/pymc3/model.py:1384, in (.0)
1380 if test_point is None:
1381 test_point = self.test_point
1383 return Series(
-> 1384 {RV.name: np.round(RV.logp(test_point), round_vals) for RV in self.basic_RVs},
1385 name="Log-probability of test_point",
1386 )
...
--> 454 for f in os.listdir(d.strip('"')):
455 if f.endswith(".so") or f.endswith(".dylib") or f.endswith(".dll"):
456 if any([f.find(ll) >= 0 for ll in l]):
FileNotFoundError: [Errno 2] No such file or directory: '/usr/local/lib'
Your setup (please complete the following information):
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