# -*- coding: utf-8 -*-
"""
@author: jeremy leconte
"""
import numpy as np
from .atm import Atm
from .gas_mix import Gas_mix
from .util.cst import PI, SIG_SB
from .util.radiation import Bnu_integral_num, rad_prop_corrk, rad_prop_xsec
from .two_stream import two_stream_toon as toon
from .two_stream import two_stream_lmdz as lmdz
from .util.spectrum import Spectrum
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class Atm_2band(Atm):
"""Class based on :class:`Atm` that handles radiative trasnfer calculations
when we want to use different radiative data to treat
stellar absorption/scattering and the atmospheric emission.
Only the method that change are overloaded.
"""
def __init__(self, k_database_stellar=None, cia_database_stellar=None, **kwargs):
"""Initialization method that calls Atm_Profile().__init__() and links
to Kdatabase and other radiative data.
"""
super().__init__(**kwargs)
self.set_k_database_stellar(k_database_stellar)
self.set_cia_database_stellar(cia_database_stellar)
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def set_k_database_stellar(self, k_database=None):
"""Change the radiative database used by the
:class:`Gas_mix` object handling opacities inside
:class:`Atm`.
See :any:`gas_mix.Gas_mix.set_k_database` for details.
Parameters
----------
k_database: :class:`Kdatabase` object
New Kdatabase to use.
"""
self.gas_mix_stellar.set_k_database(k_database=k_database)
self.kdatabase_stellar=self.gas_mix_stellar.kdatabase
self.Ng_stellar=self.gas_mix_stellar.Ng
# to know whether we are dealing with corr-k or not and access some attributes.
if self.kdatabase_stellar is not None:
self.Nw_stellar=self.kdatabase_stellar.Nw
self.flux_top_dw_nu_stellar = np.zeros((self.Nw_stellar))
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def set_cia_database_stellar(self, cia_database=None):
"""Change the CIA database used by the
:class:`Gas_mix` object handling opacities inside
:class:`Atm`.
See :any:`gas_mix.Gas_mix.set_cia_database` for details.
Parameters
----------
cia_database: :class:`CIAdatabase` object
New CIAdatabase to use.
"""
self.gas_mix_stellar.set_cia_database(cia_database=cia_database)
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def set_gas(self, composition_dict, Mgas=None, compute_Mgas=True):
"""Sets the composition of the atmosphere.
"""
for mol, vmr in composition_dict.items():
if isinstance(vmr,(np.ndarray, list)):
tmp_vmr=np.array(vmr)
#geometrical average:
composition_dict[mol]=np.sqrt(tmp_vmr[1:]*tmp_vmr[:-1])
if self.gas_mix is None:
self.gas_mix=Gas_mix(composition_dict)
self.gas_mix_stellar=Gas_mix(composition_dict)
else:
self.gas_mix.set_composition(composition_dict)
self.gas_mix_stellar.set_composition(composition_dict)
if compute_Mgas: self.set_Mgas(Mgas=Mgas)
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def set_T_profile(self, tlay):
"""Reset the temperature profile without changing the pressure levels
"""
tlay=np.array(tlay, dtype=float)
if tlay.shape != self.logplay.shape:
raise RuntimeError('tlay and logplay should have the same size.')
self.tlay=tlay
self.t_opac=(self.tlay[:-1]+self.tlay[1:])*0.5
self.gas_mix.set_logPT(logp_array=self.logp_opac, t_array=self.t_opac)
self.gas_mix_stellar.set_logPT(logp_array=self.logp_opac, t_array=self.t_opac)
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def set_adiab_profile(self, Tsurf=None, Tstrat=None):
"""Initializes the logP-T atmospheric profile with an adiabat with index R/cp=rcp
Parameters
----------
Tsurf: float
Surface temperature.
Tstrat: float, optional
Temperature of the stratosphere. If None is given,
an isothermal atmosphere with T=Tsurf is returned.
"""
if Tstrat is None: Tstrat=Tsurf
self.tlay=Tsurf*self.exner
self.tlay=np.where(self.tlay<Tstrat,Tstrat,self.tlay)
self.t_opac=(self.tlay[:-1]+self.tlay[1:])*0.5
self.gas_mix.set_logPT(logp_array=self.logp_opac, t_array=self.t_opac)
self.gas_mix_stellar.set_logPT(logp_array=self.logp_opac, t_array=self.t_opac)
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def spectral_integration_stellar(self, spectral_var):
"""Spectrally integrate an array, taking care of whether
we are dealing with corr-k or xsec data.
Parameters
----------
spectral_var: array, np.ndarray
array to integrate
Returns
-------
var: array, np.ndarray
array integrated over wavenumber (and g-space if relevant)
"""
if self.Ng_stellar is None:
var=np.sum(spectral_var*self.dwnedges_stellar,axis=-1)
else:
var=np.sum(np.sum(spectral_var*self.weights_stellar,axis=-1)*self.dwnedges_stellar,axis=-1)
return var
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def opacity_stellar(self, rayleigh = False, **kwargs):
"""Computes the opacity of each of the radiative layers (m^2/molecule).
Parameters
----------
rayleigh: bool
If true, the rayleigh cross section is computed in
self.kdata_scat and added to kdata(total extinction cross section)
See :any:`gas_mix.Gas_mix.cross_section` for details.
"""
self.kdata_stellar = self.gas_mix_stellar.cross_section(rayleigh=rayleigh, **kwargs)
if rayleigh: self.kdata_scat_stellar=self.gas_mix_stellar.kdata_scat
self.Nw_stellar=self.gas_mix_stellar.Nw
self.wns_stellar=self.gas_mix_stellar.wns
self.wnedges_stellar=self.gas_mix_stellar.wnedges
self.dwnedges_stellar=self.gas_mix_stellar.dwnedges
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def source_function_stellar(self, **kwargs):
"""Dummy function to have zero source in stellar channel
"""
piBatm=np.zeros((self.Nlay,self.Nw_stellar))
return piBatm
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def set_incoming_stellar_flux(self, flux=0., Tstar=5778., **kwargs):
"""Sets the stellar incoming flux integrated in each wavenumber
channel.
.. important::
If your simulated range does not include the whole spectral range
where the star emits, the flux seen by the model will be smaller
than the input one.
Parameters
----------
flux: float
Bolometric Incoming flux (in W/m^2).
Tstar: float
Stellar temperature (in K) used to compute the spectral distribution
of incoming flux using a blackbody.
"""
self.flux_top_dw_nu_stellar = Bnu_integral_num(self.wnedges_stellar, Tstar)
factor = flux * PI / (SIG_SB*Tstar**4 * self.dwnedges_stellar)
self.flux_top_dw_nu_stellar = self.flux_top_dw_nu_stellar * factor
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def setup_emission_caculation_stellar(self, mu_eff=0.5, rayleigh=False,
**kwargs):
"""Computes all necessary quantities for emission calculations
(opacity, source, etc.)
"""
# no need to change composition as it has been done in emission channel
# but that won't work if you are not using both channels.
self.opacity_stellar(rayleigh=rayleigh, **kwargs)
self.piBatm_stellar = self.source_function_stellar()
self.compute_layer_col_density() #done twice
if self.Ng_stellar is None:
self.tau_stellar, self.dtau_stellar=rad_prop_xsec(self.dcol_density_rad,
self.kdata_stellar, mu_eff)
else:
self.tau_stellar, self.dtau_stellar=rad_prop_corrk(self.dcol_density_rad,
self.kdata_stellar, mu_eff)
self.weights_stellar=self.kdatabase_stellar.weights
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def reflexion_spectrum_2stream(self, integral=True, mu0_stellar=0.5,
method='toon', dtau_min=1.e-10, flux_at_level=False, rayleigh=False,
flux_top_dw=None, **kwargs):
"""Returns the reflexion flux at the top of the atmosphere (in W/m^2/cm^-1)
Parameters
----------
integral: boolean, optional
* If true, the black body is integrated within each wavenumber bin.
* If not, only the central value is used.
False is faster and should be ok for small bins,
but True is the correct version.
Other Parameters
----------------
mu0_stellar: float
Cosine of the quadrature angle use to compute output flux
dtau_min: float
If the optical depth in a layer is smaller than dtau_min,
dtau_min is used in that layer instead. Important as too
transparent layers can cause important numerical rounding errors.
Returns
-------
Spectrum object
A spectrum with the Spectral flux at the top of the atmosphere (in W/m^2/cm^-1)
"""
self.setup_emission_caculation_stellar(mu_eff=1., rayleigh=rayleigh, integral=integral,
flux_top_dw=flux_top_dw, **kwargs)
# mu_eff=1. because the mu effect is taken into account in solve_2stream_nu
# we must compute the vertical optical depth here.
self.dtau_stellar=np.where(self.dtau_stellar<dtau_min,dtau_min,self.dtau_stellar)
module_to_use=globals()[method]
# globals()[method] converts the method string into a module name
# if the module has been loaded
if self.Ng_stellar is None:
solve_2stream_nu=module_to_use.solve_2stream_nu_xsec
else:
solve_2stream_nu=module_to_use.solve_2stream_nu_corrk
if rayleigh:
if self.Ng_stellar is None:
self.single_scat_albedo_stellar = self.kdata_scat_stellar / self.kdata_stellar
else:
self.single_scat_albedo_stellar = self.kdata_scat_stellar[:,:,None] / self.kdata_stellar
else:
self.single_scat_albedo_stellar = np.zeros_like(self.dtau)
self.single_scat_albedo_stellar=np.core.umath.minimum(self.single_scat_albedo_stellar,0.9999999999999)
self.asym_param_stellar = np.zeros_like(self.dtau_stellar)
if flux_top_dw is not None:
self.set_incoming_stellar_flux(flux=flux_top_dw, **kwargs)
self.flux_up_nu_stellar, self.flux_down_nu_stellar, self.flux_net_nu_stellar = \
solve_2stream_nu(self.piBatm_stellar, self.dtau_stellar,
self.single_scat_albedo_stellar, self.asym_param_stellar,
self.flux_top_dw_nu_stellar, mu0 = mu0_stellar, flux_at_level=flux_at_level)
if self.Ng_stellar is None:
return Spectrum(self.flux_up_nu_stellar[0],self.wns_stellar,self.wnedges_stellar)
else:
return Spectrum(np.sum(self.flux_up_nu_stellar[0]*self.weights_stellar,axis=1),
self.wns_stellar,self.wnedges_stellar)
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def flux_divergence_stellar(self, per_unit_mass = True, **kwargs):
"""Computes the divergence of the net flux in the layers
(used to compute heating rates).
:func:`emission_spectrum_2stream` needs to be ran first.
Parameters
----------
per_unit_mass: bool
If True, the heating rates are normalized by the
mass of each layer (result in W/kg).
Returns
-------
H: array, np.ndarray
Heating rate in each layer (Difference of the net fluxes). Positive means heating.
The last value is the net flux impinging on the surface.
net: array, np.ndarray
Net fluxes at level surfaces
"""
if self.flux_net_nu_stellar is None:
raise RuntimeError('should have ran reflexion_spectrum_2stream.')
net=self.spectral_integration_stellar(self.flux_net_nu_stellar)
H=-np.copy(net)
#print(H)
H[:-1]-=H[1:]
if per_unit_mass: H*=self.inv_dmass
return H, net
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def heating_rate(self, compute_kernel=False, dTmax_use_kernel=None,
flux_top_dw=None, **kwargs):
if (not compute_kernel) and (dTmax_use_kernel is not None):
dT=self.tlay-self.tlay_kernel
if np.amax(np.abs(dT)) < dTmax_use_kernel:
try:
H = self.H_kernel + np.dot(dT,self.kernel)
except:
raise RuntimeError("Kernel has not been precomputed")
net = np.zeros_like(H)
return H, net
_ = self.emission_spectrum_2stream(flux_at_level=True, integral=True,
compute_kernel=compute_kernel, flux_top_dw=None, **kwargs)
H, net = self.flux_divergence(compute_kernel=compute_kernel, **kwargs)
_ = self.reflexion_spectrum_2stream(flux_at_level=True, integral=True,
flux_top_dw=flux_top_dw, **kwargs)
H_stellar, net_stellar = self.flux_divergence_stellar(**kwargs)
#print(H, H_stellar)
if compute_kernel:
self.H_kernel = H + H_stellar
self.tau_rad = 1./np.amax(np.abs(self.kernel.diagonal()))
return H+H_stellar, net+net_stellar
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def bolometric_fluxes_stellar(self, per_unit_mass = True):
"""Computes the bolometric fluxes at levels and the divergence of the net flux in the layers
(used to compute heating rates).
:func:`emission_spectrum_2stream` needs to be ran first.
Parameters
----------
per_unit_mass: bool
If True, the heating rates are normalized by the
mass of each layer (result in W/kg).
Returns
-------
up: array, np.ndarray
Upward fluxes at level surfaces
dw: array, np.ndarray
Downward fluxes at level surfaces
net: array, np.ndarray
Net fluxes at level surfaces
H: array, np.ndarray
Heating rate in each layer (Difference of the net fluxes). Positive means heating.
The last value is the net flux impinging on the surface.
"""
H, net = self.flux_divergence_stellar(per_unit_mass = per_unit_mass)
up=self.spectral_integration_stellar(self.flux_up_nu_stellar)
dw=self.spectral_integration_stellar(self.flux_down_nu_stellar)
return up, dw, net, H
def __repr__(self):
"""Method to output header
"""
output=super().__repr__()
output+="""
k_database_ste :
{kdatab}
cia_database_ste:
{cdatab}""".format(kdatab=self.kdatabase, cdatab=self.gas_mix.cia_database)
if self.gas_mix._wn_range is not None:
output+=' wn range : '+ self.gas_mix._wn_range +'\n'
return output