def log_likelihood_h2o(theta, y, fixed_parameters):
# retrieve the global variables
global pixel_bins
global transit_data
global err
# only 'y' changes on the fly
x = pixel_bins
yerr = err
_, model = transit_model_H2O(x, theta, fixed_parameters, p0=p0)
sigma = yerr**2
return -0.5 * np.sum((y - model)**2 / sigma + np.log(sigma))
theta_h2och4 = (rad_planet,
T,
log_fh2o,
log_fch4)
theta_null = (rad_planet,
T)
fixed_null = (fine_wavelengths,
h2_cross_sections,
g_planet,
rad_star,
R)
# generate spectrum
pixel_wavelengths_h2o, pixel_transit_depth_h2o = transit_model_H2O(pixel_bins, theta_h2o, fixed_h2o, p0=p0)
pixel_wavelengths_ch4, pixel_transit_depth_ch4 = transit_model_CH4(pixel_bins, theta_ch4, fixed_ch4, p0=p0)
pixel_wavelengths_null, pixel_transit_depth_null = transit_model_NULL(pixel_bins, theta_null, fixed_null, p0=p0)
if plot:
# compare the spectrums, to check
fig, ax = plt.subplots(figsize=(8, 6))
ax.plot(pixel_wavelengths_h2o, pixel_transit_depth_h2o * 1e6, 'o', label='H2O')
ax.plot(pixel_wavelengths_ch4, pixel_transit_depth_ch4 * 1e6, 'o', label='CH4')
ax.plot(pixel_wavelengths_null, pixel_transit_depth_null * 1e6, 'o', label='H2 only')
ax.set_xlabel('Wavelength (μm)')
ax.set_ylabel('transit depth (ppm)')
ax.legend()