Some of the values in the light curve are nans when evaluating the following:
from pytransit import GravityDarkenedModel
rstar = 1.661671
k = [0.08381965]
rho = 0.375759167
rperiod = 0.236134363449647
tpole = 7650
phi = 1.3339553017948966
beta = 0.25
ldc = [0.5739341461489451, 0.1268867674944764]
t0 = 0
p = 1.76358769
a = 3.9532587719177115
i = 1.5111688037790845
l = 0.682913618
e = 0
w = np.pi/4
tmo = GravityDarkenedModel(rstar=rstar,sres=100, pres=8,filters=600,model='blackbody',tmax=10500)
t = np.linspace(-2./24,+2./24,1000)
tmo.set_data(t)
lc = tmo.evaluate_ps(k, rho, rperiod, tpole, phi, beta, ldc, t0, p, a, i, l, e, w)
The first instance of a nan appearing seems to be when calculate_luminosity_interpolation_table is executed inside oblate_model_s
Some of the values in the light curve are nans when evaluating the following:
from pytransit import GravityDarkenedModel
rstar = 1.661671
k = [0.08381965]
rho = 0.375759167
rperiod = 0.236134363449647
tpole = 7650
phi = 1.3339553017948966
beta = 0.25
ldc = [0.5739341461489451, 0.1268867674944764]
t0 = 0
p = 1.76358769
a = 3.9532587719177115
i = 1.5111688037790845
l = 0.682913618
e = 0
w = np.pi/4
tmo = GravityDarkenedModel(rstar=rstar,sres=100, pres=8,filters=600,model='blackbody',tmax=10500)
t = np.linspace(-2./24,+2./24,1000)
tmo.set_data(t)
lc = tmo.evaluate_ps(k, rho, rperiod, tpole, phi, beta, ldc, t0, p, a, i, l, e, w)
The first instance of a nan appearing seems to be when calculate_luminosity_interpolation_table is executed inside oblate_model_s