def __init__(self,
lc_data,
priors,
filter_names,
filter_centers,
nwalkers=150,
npol=100,
nthreads=2):
super(BlendLogPosteriorFunction,
self).__init__(lc_data, nwalkers, npol, nthreads)
self.n_colors = len(lc_data)
self.filter_names = filter_names
self.filter_centers = filter_centers
pr = priors
self.priors = [
pr.get('tc'), ## 0
pr.get('p'), ## 1
pr.get(
'k2',
UP(0.07**2, 0.16**2, 'k2', 'Squared radius ratio',
'sqrt(1/Rs)')), ## 2
pr.get('it', UP(10, 50, 'it', '2 / transit duration',
'1/d')), ## 3
pr.get('b', UP(0, 0.99, 'b', 'impact parameter')), ## 4
pr.get('c', UP(0, 0.001, 'c',
'First channel contamination')), ## 5
pr.get('T3', UP(2000, 6000, 'T3', 'Third source temperature',
'K')), ## 6
pr.get('e', UP(0, 0.001, 'e', 'Eccentricity')), ## 7
pr.get('w', UP(0, 0.001, 'w', 'Argument of periastron'))
] ## 8
[
self.priors.extend([
UP(0, 1.3, 'u',
'Linear limb darkening coefficient'), ## 9 + 2*i_c
UP(-0.3, 0.7, 'v', 'Quadratic limb darkening coefficient')
] ## 10 + 2*i_c
) for i in range(self.n_colors)
]
self.priors.extend([
UP(0.1 * e, 10 * e, 'e', 'Mean error') for e in self.flux_e
]) ## 9 + 2*n_c + i_c
self.priors.extend([
UP(1 - 1e-3, 1 + 1e-3, 'zp', 'Zeropoint')
for i in range(self.n_colors)
]) ## 9 + 3*n_c + i_c
self.priors
self.ps = PriorSet(self.priors)
## Add extra priors
## ================
self.prior_t14 = priors.get('T14', None)
self.prior_rho = priors.get('rho', None)
self.prior_logg = priors.get('logg', None)
self.upd = [True] + (self.n_colors - 1) * [False]
self.cid = range(self.n_colors)
self.ld_start = 9
self.ep_start = self.ld_start + 2 * self.n_colors
self.zp_start = self.ep_start + self.n_colors
self.ld_sl = [
np.s_[self.ld_start + 2 * ic:self.ld_start + 2 * (ic + 1)]
for ic in self.cid
]
self.er_sl = np.s_[self.ep_start:self.ep_start + self.n_colors]
def __init__(self,
lc_data,
priors,
filter_names,
filter_centers,
nwalkers=150,
npol=100,
nthreads=2):
super(MCLogPosteriorFunction, self).__init__(lc_data, nwalkers, npol,
nthreads)
self.n_colors = len(lc_data)
self.filter_names = filter_names
self.filter_centers = filter_centers
pr = priors
self.priors = [
pr.get('tc'), ## 0 - Transit center
pr.get('p'), ## 1 - Period
pr.get(
'k2',
UP(0.07**2, 0.16**2, 'k2', 'Squared radius ratio',
'sqrt(1/Rs)')), ## 2 - Squared radius ratio
pr.get('it',
UP(10, 50, 'it', '2 / transit duration',
'1/d')), ## 3 - Reciprocal of half transit duration
pr.get('b', UP(0, 0.99, 'b',
'impact parameter')), ## 4 - Impact parameter
pr.get('c',
UP(0, 0.001, 'c',
'Contamination')), ## 5 - Monochromatic contamination
pr.get('e', UP(0, 0.001, 'e',
'Eccentricity')), ## 6 - Eccentricity
pr.get('w', UP(0, 0.001, 'w', 'Argument of periastron'))
] ## 7 - Argument of periastron
for i in range(self.n_colors):
self.priors.append(
pr.get('u{:d}'.format(i),
UP(0.0, 1.3, 'u',
'Linear limb darkening coefficient'))) ## 8 + 2*i_c
self.priors.append(
pr.get('v{:d}'.format(i),
UP(-0.3, 0.7, 'v',
'Linear limb darkening coefficient'))) ## 9 + 2*i_c
#[self.priors.extend([UP( 0, 1.3, 'u', 'Linear limb darkening coefficient'), ## 8 + 2*i_c
# UP( -0.3, 0.7, 'v', 'Quadratic limb darkening coefficient')] ## 9 + 2*i_c
# ) for i in range(self.n_colors)]
self.priors.extend([
UP(0.1 * e, 10 * e, 'e', 'Mean error') for e in self.flux_e
]) ## 8 + 2*n_c + i_c
self.priors.extend([
UP(1 - 1e-2, 1 + 1e-2, 'zp', 'Zeropoint')
for i in range(self.n_colors)
]) ## 8 + 3*n_c + i_c
self.ps = PriorSet(self.priors)
## Add extra priors
## ================
self.prior_t14 = priors.get('T14', None)
self.prior_rho = priors.get('rho', None)
self.prior_logg = priors.get('logg', None)
self.upd = [True] + (self.n_colors - 1) * [False]
self.cid = range(self.n_colors)
self.ld_start = 8
self.ep_start = self.ld_start + 2 * self.n_colors
self.zp_start = self.ep_start + self.n_colors
self.ld_sl = [
np.s_[self.ld_start + 2 * ic:self.ld_start + 2 * (ic + 1)]
for ic in self.cid
]
self.er_sl = np.s_[self.ep_start:self.ep_start + self.n_colors]
