def calc_thermal_structure(temp_params):
# calculate thermal structure
pressures = np.logspace(-6, temp_params['P0'], 100)
temperatures = nc.guillot_global(pressures,
1e1**temp_params['log_kappa_IR'],
1e1**temp_params['log_gamma'],
1e1**temp_params['log_gravity'],
temp_params['t_int'],
temp_params['t_equ'])
return pressures, temperatures
def calc_spectrum(self,
metal_params,
temps_params,
clouds_params,
external_metal_profile=None,
converting_units=True):
external_profile = None
if self.external_pt_profile is not None:
pressures, temperatures = self.external_pt_profile
external_profile = [
pressures, temperatures, external_metal_profile
]
else:
pressures = np.logspace(-6, temps_params['P0'], 100)
temperatures = nc.guillot_global(pressures,
1e1**temps_params['log_kappa_IR'],
1e1**temps_params['log_gamma'],
1e1**temps_params['log_gravity'],
temps_params['t_int'],
temps_params['t_equ'])
self.rt_obj.setup_opa_structure(pressures)
wlen, flux = retrieval_model_initial(self.rt_obj,
temps_params,
metal_params,
clouds_params,
mode=self.mode,
external_profile=external_profile)
if converting_units:
wlen_temp, flux_temp = convert_units(wlen,
flux,
temps_params['log_R'],
distance=DISTANCE)
else:
wlen_temp = 1e4 * wlen
flux_temp = flux
return wlen_temp, flux_temp
atmosphere.setup_opa_structure(pressures)
import petitRADTRANS.nat_cst as nc
R_pl = 1.838*nc.r_jup_mean
gravity = 1.e5
P0 = 0.01
kappa_IR = 0.01
gamma = 0.4
T_int = 200.
T_equ = 1500.
temperature = nc.guillot_global(pressures, kappa_IR, gamma, gravity, T_int, T_equ)
print(len(temperature))
data = open('../co_exojax/Gl229/MMR/eq.dat', 'r')
a = 0
MMW_k = np.ones_like(temperature)
MMR = [[0] * len(pressures) for j in range(160)]
for line in data:
if line[0]=='#':
continue
lines = line.rstrip('\n').split()
MMW_k[a] = lines[2]
for i in range(0,160):
MMR[i][a] = lines[i+3]
a = a + 1
def calculate_model(loc):
'''
Description: main wrapper function to run petitRADTRANS to calculate atmosphere model
'''
WLEN = [loc['WL0'] / 1000., loc['WLF'] / 1000.]
loc["WLEN_MICRONS"] = WLEN
loc["RP_CGS"] = loc[
'RP'] * nc.r_jup_mean #nominal hot Jupiter radius should be 1.25*nc.r_jup_mean
loc["MP_CGS"] = loc[
'MP'] * nc.m_jup #nominal hot Jupiter mass should be 1.81*nc.r_jup_mean
loc["GRAVITY_CGS"] = (nc.G * loc["MP_CGS"]) / (loc["RP_CGS"]**2)
loc["OPACITY_FILES"] = opacity_files(loc['SPECIES'], mode=loc['MODE'])
# Create the Ratrans object here
atmosphere = Radtrans(line_species=loc["OPACITY_FILES"], \
rayleigh_species=loc['RAYLEIGH_SPECIES'], \
continuum_opacities=loc['CONTINUUM_OPACITIES'], \
mode=loc['MODE'], \
wlen_bords_micron = loc["WLEN_MICRONS"])
# Create pressure and temperature distribution: Guillot
loc["P_SCALE"] = 'log_10'
pressures = np.logspace(loc["P_START"], loc["P_STOP"], loc["P_NSAMPLES"])
loc["P-T_Model"] = 'nc.guillot_global()'
temperature = nc.guillot_global(pressures, loc['KAPPA'], loc['GAMMA'],
loc['GRAVITY_CGS'], loc['TINT'],
loc['TEQ'])
atmosphere.setup_opa_structure(pressures)
loc_abundances = {}
# Define abundances of line species and mean molecular weight of atmosphere
for i in range(len(loc["OPACITY_FILES"])):
ab_percent = 10**(loc['ABUNDANCES'][i] + np.log10(loc['AB_H2']))
loc_abundances[loc["OPACITY_FILES"]
[i]] = ab_percent * np.ones_like(temperature)
# Define abundances of H2 and He and mean molecular weight of atmosphere
loc_abundances["He"] = loc['AB_He'] * np.ones_like(temperature)
loc_abundances["H2"] = loc['AB_H2'] * np.ones_like(temperature)
loc["loc_abundances"] = loc_abundances
MMW = 2.3 * np.ones_like(temperature)
# calculation of transmission spectrum
atmosphere.calc_transm(temperature,
loc_abundances,
loc["GRAVITY_CGS"],
MMW,
R_pl=loc["RP_CGS"],
P0_bar=loc['P0'])
# calculation of emission spectrum
atmosphere.calc_flux(temperature, loc_abundances, loc["GRAVITY_CGS"], MMW)
# create transmission data vector
loc['transmission'] = atmosphere.transm_rad / nc.r_jup_mean
# create emission data vector
loc['emission'] = atmosphere.flux / 1e-6
# create wavelength array
loc['wl'] = nc.c / atmosphere.freq / 1e-4
return loc
def calc_spectrum(self,
ab_metals,
temp_params,
clouds_params,
external_pt_profile=None,
return_profiles=False,
contribution=False,
set_mol_abund=None):
# temperature-pressure profile
if external_pt_profile is not None:
pressures, temperatures = external_pt_profile
else:
pressures = np.logspace(-6, temp_params['P0'], 100)
temperatures = nc.guillot_global(pressures,
1e1**temp_params['log_kappa_IR'],
1e1**temp_params['log_gamma'],
1e1**temp_params['log_gravity'],
temp_params['t_int'],
temp_params['t_equ'])
# setup up opacity structure if not yet done so
if not (self.opa_struct_set):
self.rt_obj.setup_opa_structure(pressures)
self.opa_struct_set = True
# translate ab_metals dictionary if we're using c-k mode
if self.mode == 'c-k':
# example: if mol = 'H2O_main_iso', then name_ck(mol) = 'H2O'
# so it changes ab_metals = {'H2O_main_iso':obj} to ab_metals = {'H2O':obj}
ab_metals_ck = {
name_ck(mol): ab_metals[mol]
for mol in ab_metals.keys()
}
ab_metals = ab_metals_ck
# calculate forward model depending on case: free or chemical equilibrium
if self.model == 'free':
wlen, flux, abundances = retrieval_model_initial(
self.rt_obj,
pressures,
temperatures,
temp_params,
ab_metals,
clouds_params,
mode=self.mode,
contribution=contribution)
elif self.model == 'chem_equ':
# 'chem_equ'
wlen, flux, abundances = retrieval_model_chem_disequ(
self.rt_obj,
temp_params,
ab_metals,
clouds_params,
mode=self.mode,
contribution=contribution,
only_include=self.only_include,
set_mol_abund=set_mol_abund)
else:
wlen, flux, abundances = calc_flux_from_model(
self.rt_obj,
temp_params,
chem_model=self.model,
chem_params=ab_metals,
clouds_params=clouds_params,
mode=self.mode,
contribution=contribution)
if self.only_include != 'all':
assert (len(abundances.keys()) == len(self.only_include) + 2)
if return_profiles:
return wlen, flux, pressures, temperatures, abundances
else:
return wlen, flux
def Simulator(params):
NaN_spectra = 0
atmosphere = Radtrans(line_species = ['H2O', 'CO_all_iso', \
'CO2', 'CH4', \
'Na', 'K'], \
rayleigh_species = ['H2', 'He'], \
continuum_opacities = ['H2-H2', 'H2-He'], \
wlen_bords_micron = WLENGTH)#, mode='c-k')
pressures = np.logspace(-6, 2, 100)
atmosphere.setup_opa_structure(pressures)
temperature = 1200. * np.ones_like(pressures)
t_int = params[0].numpy() #200.
log_kappa_IR = params[1].numpy() #-2
log_gravity = params[2].numpy() #params[5].numpy() 1e1**2.45
gravity = np.exp(log_gravity)
kappa_IR = np.exp(log_kappa_IR)
temperature = nc.guillot_global(pressures, kappa_IR, gamma, gravity, t_int, t_equ)
abundances = {}
abundances['H2'] = 0.75 * np.ones_like(temperature) #0.74 * np.ones_like(temperature) (params[3].numpy())
abundances['He'] = 0.25 * np.ones_like(temperature) #0.24 * np.ones_like(temperature) (params[4].numpy())
abundances['H2O'] = 0.001 * np.ones_like(temperature)
abundances['CO_all_iso'] = 0.01 * np.ones_like(temperature)
abundances['CO2'] = 0.00001 * np.ones_like(temperature)
abundances['CH4'] = 0.000001 * np.ones_like(temperature)
abundances['Na'] = 0.00001 * np.ones_like(temperature)
abundances['K'] = 0.000001 * np.ones_like(temperature)
MMW = rm.calc_MMW(abundances) * np.ones_like(temperature)
#print(MMW, abundances)
atmosphere.calc_flux(temperature, abundances, gravity, MMW)
wlen, flux_nu = nc.c/atmosphere.freq, atmosphere.flux/1e-6
# Just to make sure that a long chain does not die
# unexpectedly:
# Return -inf if forward model returns NaN values
if np.sum(np.isnan(flux_nu)) > 0:
print("NaN spectrum encountered")
NaN_spectra += 1
return torch.ones([1,371])* -np.inf
# Convert to observation for emission case
flux_star = fstar(wlen)
flux_sq = flux_nu/flux_star*(R_pl/R_star)**2
flux_rebinned = rgw.rebin_give_width(wlen, flux_sq, \
data_wlen['MIRI LRS'], data_wlen_bins['MIRI LRS'])
#flux_rebinned = np.reshape(flux_rebinned, (371,1))
FR= torch.Tensor(flux_rebinned)
return FR
P0_bar=P0_bar)
petit_trans = atmosphere.transm_rad / pc.rjup
pyrat = pb.run('petit_spectrum_H2O-CO.cfg')
pyrat_wl = 1 / (pyrat.spec.wn * pc.um)
pyrat_trans = np.sqrt(pyrat.spec.spectrum) * pyrat.phy.rstar / pc.rjup
# ::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::
# Emission models:
# This one requires a non-isothermal profile:
kappa_IR = 0.01
gamma = 0.4
T_int = 200.0
T_equ = 1500.0
temp2 = nc.guillot_global(pressure / pc.bar, kappa_IR, gamma, gravity, T_int,
T_equ)
atmosphere.calc_flux(temp2, abundances, gravity, mu)
petit_emission = atmosphere.flux * pc.c
pyrat.od.rt_path = 'emission'
pyrat.run(temp=temp2, radius=atmosphere.radius)
pyrat_emission = np.copy(pyrat.spec.spectrum)
# ::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::
# Additional calculation with methane opacity:
atmosphere = Radtrans(line_species=['CH4', 'Na_lor_cut', 'K_lor_cut'],
rayleigh_species=['H2'],
continuum_opacities=['H2-H2'],
wlen_bords_micron=[0.3, 10.0])
atmosphere.setup_opa_structure(pressure / pc.bar)
