def test_compare_starmodels(props=props):
m1 = StarModel(mist, **props)
m2 = BasicStarModel(mist, **props)
# Ensure priors are identical
for k in ["mass", "feh", "age", "distance", "AV", "eep"]:
m2.set_prior(**{k: m1._priors[k]})
pars = [300, 9.8, 0.01, 100, 0.1]
assert np.isclose(m1.lnlike(pars), m2.lnlike(pars))
assert np.isclose(m1.lnprior(pars), m2.lnprior(pars))
assert np.isclose(m1.lnpost(pars), m2.lnpost(pars))
m1_bin = StarModel(mist, **props, N=2)
m2_bin = BasicStarModel(mist, **props, N=2)
# Ensure priors are identical
for k in ["mass", "feh", "age", "distance", "AV", "eep"]:
m2_bin.set_prior(**{k: m1_bin._priors[k]})
pars = [300, 280, 9.8, 0.01, 100, 0.1]
assert np.isclose(m1_bin.lnlike(pars), m2_bin.lnlike(pars))
assert np.isclose(m1_bin.lnprior(pars), m2_bin.lnprior(pars))
assert np.isclose(m1_bin.lnpost(pars), m2_bin.lnpost(pars))
m1_trip = StarModel(mist, **props, N=3)
m2_trip = BasicStarModel(mist, **props, N=3)
# Ensure priors are identical
for k in ["mass", "feh", "age", "distance", "AV", "eep"]:
m2_trip.set_prior(**{k: m1_trip._priors[k]})
pars = [300, 280, 260.0, 9.8, 0.01, 100, 0.1]
assert np.isclose(m1_trip.lnlike(pars), m2_trip.lnlike(pars))
assert np.isclose(m1_trip.lnprior(pars), m2_trip.lnprior(pars))
assert np.isclose(m1_trip.lnpost(pars), m2_trip.lnpost(pars))
def __init__(self,
koi,
recalc=False,
use_JRowe=True,
trsig_kws=None,
tag=None,
starmodel_mcmc_kws=None,
**kwargs):
koi = koiname(koi)
#if saved popset exists, load
folder = os.path.join(KOI_FPPDIR, koi)
if tag is not None:
folder += '_{}'.format(tag)
if not os.path.exists(folder):
os.makedirs(folder)
if trsig_kws is None:
trsig_kws = {}
#first check if pickled signal is there to be loaded
trsigfile = os.path.join(folder, 'trsig.pkl')
if os.path.exists(trsigfile):
trsig = pickle.load(open(trsigfile, 'rb'))
else:
if use_JRowe:
trsig = JRowe_KeplerTransitSignal(koi, **trsig_kws)
else:
trsig = KeplerTransitSignal(koi, **trsig_kws)
popsetfile = os.path.join(folder, 'popset.h5')
if os.path.exists(popsetfile) and not recalc:
popset = PopulationSet(popsetfile, **kwargs)
else:
koinum = koiname(koi, koinum=True)
kepid = ku.DATA.ix[koi, 'kepid']
if 'mass' not in kwargs:
kwargs['mass'] = koi_propdist(koi, 'mass')
if 'radius' not in kwargs:
kwargs['radius'] = koi_propdist(koi, 'radius')
if 'feh' not in kwargs:
kwargs['feh'] = koi_propdist(koi, 'feh')
if 'age' not in kwargs:
try:
kwargs['age'] = koi_propdist(koi, 'age')
except:
kwargs['age'] = (9.7, 0.1) #default age
if 'Teff' not in kwargs:
kwargs['Teff'] = kicu.DATA.ix[kepid, 'teff']
if 'logg' not in kwargs:
kwargs['logg'] = kicu.DATA.ix[kepid, 'logg']
if 'rprs' not in kwargs:
if use_JRowe:
kwargs['rprs'] = trsig.rowefit.ix['RD1', 'val']
else:
kwargs['rprs'] = ku.DATA.ix[koi, 'koi_ror']
#if stellar properties are determined spectroscopically,
# fit stellar model
if 'starmodel' not in kwargs:
if re.match('SPE', kicu.DATA.ix[kepid, 'teff_prov']):
logging.info(
'Spectroscopically determined stellar properties.')
#first, see if there already is a starmodel to load
#fit star model
Teff = kicu.DATA.ix[kepid, 'teff']
e_Teff = kicu.DATA.ix[kepid, 'teff_err1']
logg = kicu.DATA.ix[kepid, 'logg']
e_logg = kicu.DATA.ix[kepid, 'logg_err1']
feh = kicu.DATA.ix[kepid, 'feh']
e_feh = kicu.DATA.ix[kepid, 'feh_err1']
logging.info(
'fitting StarModel (Teff=({},{}), logg=({},{}), feh=({},{}))...'
.format(Teff, e_Teff, logg, e_logg, feh, e_feh))
dar = Dartmouth_Isochrone()
starmodel = StarModel(dar,
Teff=(Teff, e_Teff),
logg=(logg, e_logg),
feh=(feh, e_feh))
if starmodel_mcmc_kws is None:
starmodel_mcmc_kws = {}
starmodel.fit_mcmc(**starmodel_mcmc_kws)
logging.info('Done.')
kwargs['starmodel'] = starmodel
if 'mags' not in kwargs:
kwargs['mags'] = ku.KICmags(koi)
if 'ra' not in kwargs:
kwargs['ra'], kwargs['dec'] = ku.radec(koi)
if 'period' not in kwargs:
kwargs['period'] = ku.DATA.ix[koi, 'koi_period']
if 'pl_kws' not in kwargs:
kwargs['pl_kws'] = {}
if 'fp_specific' not in kwargs['pl_kws']:
rp = kwargs['radius'].mu * kwargs['rprs'] * RSUN / REARTH
kwargs['pl_kws']['fp_specific'] = fp_fressin(rp)
#trilegal_filename = os.path.join(folder,'starfield.h5')
trilegal_filename = kepler_starfield_file(koi)
popset = PopulationSet(trilegal_filename=trilegal_filename,
**kwargs)
#popset.save_hdf('{}/popset.h5'.format(folder), overwrite=True)
lhoodcachefile = os.path.join(folder, 'lhoodcache.dat')
self.koi = koi
FPPCalculation.__init__(self, trsig, popset, folder=folder)
self.save()
self.apply_default_constraints()
