def get_value(self, t):
params = deepcopy(original_params)
a_rs, inc = duration_to_otherparams(params.per,
self.duration, self.b,
np.sqrt(self.depth),
params.ecc, params.w)
params.rp = self.depth**0.5
params.t0 = self.t0 + mid_transit_answer
params.inc = inc
params.a = a_rs
return self.amp * transit_model(t + mid_transit_answer, params)
def get_value(self, t):
params = deepcopy(original_params)
params.rp = self.depth**0.5
params.t0 = self.t0
return self.amp * transit_model(t, params)
def get_value(self, t):
params = deepcopy(trappist1('b'))
params.rp = self.depth**0.5
return self.amp * transit_model(t, params)
skip = 1
mu, var = gp.predict(obs_flux, obs_time, return_var=True)
std = np.sqrt(var)
# samples = np.vstack([obs_planet.samples_amp, obs_planet.samples_depth,
# obs_planet.samples_t0, obs_planet.samples_log_omega0, obs_planet.samples_log_S0])
#
# from corner import corner
# corner(samples.T, labels=['amp', 'depth', 't0', 'log_omega0', 'log_S0'])
# plt.show()
transit_params = params(planet)
transit_params.rp = np.sqrt(np.median(obs_planet.samples_depth))
transit_params.t0 = np.median(obs_planet.samples_t0)
amp = np.median(obs_planet.samples_amp)
best_transit_model = amp * transit_model(obs_time, transit_params)
transitless_gp_mean = mu - best_transit_model
transitless_obs_flux = obs_flux - best_transit_model
# fig, ax = plt.subplots(2, 1, figsize=(5, 8))
# ax[0].errorbar(obs_time, obs_flux, obs_err, fmt='.', color='k', ecolor='silver', ms=2, alpha=0.5)
# ax[0].plot(obs_time, mu, 'r', zorder=10)
# ax[0].fill_between(obs_time, mu-std, mu+std, color='r', alpha=0.5, zorder=10)
# ax[0].set_title(Time((obs_time + original_params.t0).min(), format='jd').datetime.date())
# ax[0].set_ylabel('NIRSpec Counts')
# ax[0].set_xlabel('Time [d]')
# model_residual = amp * (obs_planet.fluxes[mask] + obs_planet.spitzer_var[mask] - 2)
# model_residual -= np.median(model_residual)
# ax[1].plot(obs_time, model_residual, 'r', lw=2, zorder=10, label='microvar + spots')
del obs.archive[planet]
group = obs.archive.create_group(planet)
u1, u2 = params.u
#duration = transit_duration(transit_params(planet))
spectrum_photo = IRTFTemplate(sptype_phot)
spectrum_spots = IRTFTemplate(sptype_spot)
print('midtransit', midtransit)
times = np.arange(midtransit - (8 * np.random.rand() + 2) * duration,
midtransit + (8 * np.random.rand() + 2) * duration,
exptime.to(u.day).value)
# times = np.arange(midtransit - 1*duration, midtransit, exptime.to(u.day).value)
transit = transit_model(times, params) #all_transits(times)
subgroup = group.create_group("{0}".format(
Time(midtransit, format='jd').isot))
star = Star.with_k296_spot_distribution()
star.rotation_period = rotation_period * u.day
area = star.spotted_area(times)
fluxes = star.fractional_flux(times)
spitzer_var = spitzer_variability(times)[:, np.newaxis]
spectrum_photo_flux = spectrum_photo.interp_flux(wl)
spectrum_spots_flux = spectrum_spots.interp_flux(wl)
combined_spectra = (
(transit[:, np.newaxis] - area[:, np.newaxis]) * spectrum_photo_flux +
