def __init__(self, lcdata, tmodel=None, **kwargs):
self.tmodel = tmodel or Gimenez()
self.lcdata = lcdata
self.group = None
self.pid_ar = None
self.pid_ld = None
self.pid_private = None
## Precalculate the likelihood constants
## =====================================
self.lln = -0.5 * self.lcdata.npt * m.log(2 * m.pi)
## Define priors
## =============
pr = kwargs.get('priors', {})
self.priors = []
self.priors.extend([
UP(0.2, 5.0, 'e', 'Error multiplier')
for i in range(self.lcdata.npb)
])
self.priors.extend([
UP(0.0, 0.01, 'c', 'Contamination') for i in range(self.lcdata.npb)
])
self.ps = PriorSet(self.priors)
self.np = len(self.priors)
self.pv_start_idx = None
def __init__(self, npop=70, orbit_priors={}, ar_priors={}, ld_priors={}):
self.npop = npop
self.lc_lpfunctions = []
self.rv_lpfunctions = []
self.lclp = self.lc_lpfunctions
self.rvlp = self.rv_lpfunctions
self.ar_pdef = ar_priors
self.ld_pdef = ld_priors
pr = orbit_priors
self.orbit_priors = [pr.get( 'tc'), ## 0 - Transit center
pr.get( 'p'), ## 1 - Period
pr.get('rho', UP( 0.5, 2.0, 'rho', 'stellar density', 'g/cm^3')), ## 2 - Stellar density
pr.get( 'b', UP( 0, 0.99, 'b', 'impact parameter')), ## 3 - Impact parameter
pr.get( 'e', UP( 0, 0.001, 'e', 'Eccentricity')), ## 4 - Eccentricity
pr.get( 'w', UP( 0, 0.001, 'w', 'Argument of periastron'))] ## 5 - Argument of periastron
self.orbit_ps = PriorSet(self.orbit_priors)
self.lc_passbands = []
self.nor = 6
self.nar = None
self.nld = None
self.nlc = None
self.nrv = None
self.ar_start_idx = self.nor
self.ld_start_idx = None
self.lc_start_idx = None
self.rv_start_idx = None
def __init__(self, lcdata, tmodel=None, **kwargs):
self.tmodel = tmodel or Gimenez()
self.lcdata = lcdata
self.group = None
self.pid_ar = None
self.pid_ld = None
self.pid_private = None
## Precalculate the likelihood constants
## =====================================
self.lln = -0.5*self.lcdata.npt * m.log(2*m.pi)
## Define priors
## =============
pr = kwargs.get('priors', {})
self.priors = []
self.priors.extend([UP(0.2, 5.0, 'e', 'Error multiplier') for i in range(self.lcdata.npb)])
self.priors.extend([UP(0.0, 0.01, 'c', 'Contamination') for i in range(self.lcdata.npb)])
self.ps = PriorSet(self.priors)
self.np = len(self.priors)
self.pv_start_idx = None
class LCLogPosteriorFunction(object):
def __init__(self, lcdata, tmodel=None, **kwargs):
self.tmodel = tmodel or Gimenez()
self.lcdata = lcdata
self.group = None
self.pid_ar = None
self.pid_ld = None
self.pid_private = None
## Precalculate the likelihood constants
## =====================================
self.lln = -0.5 * self.lcdata.npt * m.log(2 * m.pi)
## Define priors
## =============
pr = kwargs.get('priors', {})
self.priors = []
self.priors.extend([
UP(0.2, 5.0, 'e', 'Error multiplier')
for i in range(self.lcdata.npb)
])
self.priors.extend([
UP(0.0, 0.01, 'c', 'Contamination') for i in range(self.lcdata.npb)
])
self.ps = PriorSet(self.priors)
self.np = len(self.priors)
self.pv_start_idx = None
def compute_continuum(self, pv):
raise NotImplementedError
def compute_transit(self, pv):
print(self.group._pv_o_physical)
z = of.z_eccentric(self.lcdata.time,
*self.group._pv_o_physical,
nthreads=0)
f = self.tmodel(z, m.sqrt(pv[self.pid_ar[0]]), pv[self.pid_ld], 0.0)
return f
def compute_lc_model(self, pv):
return self.compute_transit(pv)
def log_posterior(self, pv):
log_prior = self.ps.c_log_prior(pv[self.pid_private])
flux_m = self.compute_lc_model(pv)
err = self.lcdata.errors * pv[self.pid_err]
chisqr = (((self.lcdata.fluxes - flux_m) / err)**2).sum()
log_likelihood = self.lln - 0.5 * (np.log(err)).sum() - 0.5 * chisqr
return log_prior + log_likelihood
class LCLogPosteriorFunction(object):
def __init__(self, lcdata, tmodel=None, **kwargs):
self.tmodel = tmodel or Gimenez()
self.lcdata = lcdata
self.group = None
self.pid_ar = None
self.pid_ld = None
self.pid_private = None
## Precalculate the likelihood constants
## =====================================
self.lln = -0.5*self.lcdata.npt * m.log(2*m.pi)
## Define priors
## =============
pr = kwargs.get('priors', {})
self.priors = []
self.priors.extend([UP(0.2, 5.0, 'e', 'Error multiplier') for i in range(self.lcdata.npb)])
self.priors.extend([UP(0.0, 0.01, 'c', 'Contamination') for i in range(self.lcdata.npb)])
self.ps = PriorSet(self.priors)
self.np = len(self.priors)
self.pv_start_idx = None
def compute_continuum(self, pv):
raise NotImplementedError
def compute_transit(self, pv):
print (self.group._pv_o_physical)
z = of.z_eccentric(self.lcdata.time, *self.group._pv_o_physical, nthreads=0)
f = self.tmodel(z, m.sqrt(pv[self.pid_ar[0]]), pv[self.pid_ld], 0.0)
return f
def compute_lc_model(self, pv):
return self.compute_transit(pv)
def log_posterior(self, pv):
log_prior = self.ps.c_log_prior(pv[self.pid_private])
flux_m = self.compute_lc_model(pv)
err = self.lcdata.errors*pv[self.pid_err]
chisqr = (((self.lcdata.fluxes - flux_m)/err)**2).sum()
log_likelihood = self.lln - 0.5*(np.log(err)).sum() -0.5*chisqr
return log_prior + log_likelihood
class LPFGroup(object):
def __init__(self, npop=70, orbit_priors={}, ar_priors={}, ld_priors={}):
self.npop = npop
self.lc_lpfunctions = []
self.rv_lpfunctions = []
self.lclp = self.lc_lpfunctions
self.rvlp = self.rv_lpfunctions
self.ar_pdef = ar_priors
self.ld_pdef = ld_priors
pr = orbit_priors
self.orbit_priors = [pr.get( 'tc'), ## 0 - Transit center
pr.get( 'p'), ## 1 - Period
pr.get('rho', UP( 0.5, 2.0, 'rho', 'stellar density', 'g/cm^3')), ## 2 - Stellar density
pr.get( 'b', UP( 0, 0.99, 'b', 'impact parameter')), ## 3 - Impact parameter
pr.get( 'e', UP( 0, 0.001, 'e', 'Eccentricity')), ## 4 - Eccentricity
pr.get( 'w', UP( 0, 0.001, 'w', 'Argument of periastron'))] ## 5 - Argument of periastron
self.orbit_ps = PriorSet(self.orbit_priors)
self.lc_passbands = []
self.nor = 6
self.nar = None
self.nld = None
self.nlc = None
self.nrv = None
self.ar_start_idx = self.nor
self.ld_start_idx = None
self.lc_start_idx = None
self.rv_start_idx = None
def add_lpfunction(self, lpfunction):
lpfunction.group = self
if isinstance(lpfunction, LCLogPosteriorFunction):
self.lc_lpfunctions.append(lpfunction)
self.lc_passbands.extend(lpfunction.lcdata.passbands)
elif isinstance(lpfunction, RVLogPosteriorFunction):
self.rv_lpfunctions.append(lpfunction)
else:
raise NotImplementedError
def finalize(self):
## Optimise the area ratio access
## ==============================
ar_groups = list(np.unique(np.concatenate([[pb.kgroup for pb in lpf.lcdata.passbands] for lpf in self.lclp])))
for lpf in self.lclp:
lpf.pid_ar = [self.ar_start_idx + ar_groups.index(pb.kgroup) for pb in lpf.lcdata.passbands]
self.nar = len(ar_groups)
self.ld_start_idx = self.ar_start_idx + self.nar
## Optimise the limb darkening coefficient access
## ==============================================
lds = self.ld_start_idx
self.lclp[0].pid_ld = np.s_[lds:lds+2*self.lclp[0].lcdata.npb]
final_pb_set = self.lc_passbands[:self.lclp[0].lcdata.npb]
for i,lpf in enumerate(self.lc_lpfunctions[1:]):
lp_indices = []
for j,pb in enumerate(lpf.lcdata.passbands):
try:
lp_indices.append(final_pb_set.index(pb))
except ValueError:
final_pb_set.append(pb)
lp_indices.append(len(final_pb_set)-1)
if np.all(np.diff(lp_indices) == 1):
lpf.pid_lc = np.s_[lds+lp_indices[0] : lds+2*(lp_indices[-1]+1)]
else:
lpf.pid_lc = np.concatenate([(lds+2*li, lds+2*li+1) for li in lp_indices])
self.lc_passbands = final_pb_set
self.nld = 2*len(self.lc_passbands)
## Setup the private space for log-posterior functions
## ===================================================
self.lc_start_idx = self.ld_start_idx+self.nld+np.cumsum([0]+[lpf.np for lpf in self.lclp[:-1]])
for i,lpf in enumerate(self.lclp):
lpf.pv_start_idx = self.lc_start_idx[i]
self.nlc = sum([lpf.np for lpf in self.lclp])
## Generate rest of the prior sets
## ===============================
self.ar_priors = [self.ar_pdef.get('ar {:d}'.format(ai), UP(0.05**2, 0.15**2, 'ar', 'area ratio', '1/As')) for ai in ar_groups]
self.ar_pset = PriorSet(self.ar_priors)
self.ld_priors = []
for pb in self.lc_passbands:
self.ld_priors.append(self.ld_pdef.get('u {:s}'.format(pb.name), UP( 0.0,1.3, 'u {:s}'.format(pb.name), 'Linear limb darkening coefficient')))
self.ld_priors.append(self.ld_pdef.get('v {:s}'.format(pb.name), UP(-0.3,0.7, 'v {:s}'.format(pb.name), 'Quadratic limb darkening coefficient')))
self.ld_pset = PriorSet(self.ld_priors)
pv0_basic = np.hstack([ps.generate_pv_population(self.npop) for ps in [self.orbit_ps, self.ar_pset, self.ld_pset]])
pv0_lc_private = np.hstack([lpf.ps.generate_pv_population(self.npop) for lpf in self.lclp])
self.pv0 = np.hstack([pv0_basic, pv0_lc_private])
def map_orbit(self, pv):
a = AC*((pv[1]*DTOS)**2 * 1e3*pv[2])**(1/3)
i = math.acos(pv[4]/a)
self._pv_o_physical = pv[:6].copy()
self._pv_o_physical[2] = a
self._pv_o_physical[3] = i
return self._pv_o_physical
def __call__(self, pv):
self.map_orbit(pv)
return self.orbit_ps.c_log_prior(pv[0:7])
