`petitRADTRANS.containers.spectral_model`

SpectralModel object and related.

Module Contents

Classes

`RetrievalParameter`
`BaseSpectralModel`
`SpectralModel`

class petitRADTRANS.containers.spectral_model.RetrievalParameter(name, prior_parameters, prior_type='uniform', custom_prior=None)

available_priors = ['log', 'uniform', 'gaussian', 'log_gaussian', 'delta', 'custom']

classmethod from_dict(dictionary)

Convert a dictionary into a list of RetrievalParameter. The keys of the dictionary are the names of the RetrievalParameter. The values of the dictionary must be dictionaries with keys ‘prior_parameters’ and ‘prior_type’.

Args:: dictionary: a dictionary
Returns:: A list of RetrievalParameter.

put_into_dict(dictionary=None)

Convert a RetrievalParameter into a dictionary.

Args:: dictionary: a dictionary; if None, a new dictionary is created
Returns:: A dictionary.

class petitRADTRANS.containers.spectral_model.BaseSpectralModel(pressures, line_species=None, rayleigh_species=None, continuum_opacities=None, cloud_species=None, opacity_mode='lbl', do_scat_emis=True, lbl_opacity_sampling=1, temperatures=None, mass_mixing_ratios=None, mean_molar_masses=None, wavelengths_boundaries=None, wavelengths=None, transit_radii=None, spectral_radiosities=None, times=None, **model_parameters)

static __init_velocities(radial_velocity_amplitude_function, planet_radial_velocities_function, relative_velocities_function, relative_velocities=None, system_observer_radial_velocities=None, planet_radial_velocity_amplitude=None, planet_radial_velocities=None, planet_rest_frame_velocity_shift=0.0, orbital_longitudes=None, orbital_phases=None, is_orbiting=None, **kwargs)

static __convolve_wrap(wavelengths, convolve_function, spectrum, **kwargs)

static __rebin_wrap(wavelengths, spectrum, rebin_spectrum_function, **kwargs)

static _calculate_relative_velocities_wrap(radial_velocity_amplitude_function, planet_radial_velocities_function, relative_velocities_function, system_observer_radial_velocities, planet_rest_frame_velocity_shift, is_orbiting=False, orbital_longitudes=None, planet_radial_velocity_amplitude=None, planet_radial_velocities=None, **kwargs)

static _check_missing_model_parameters(model_parameters, explanation_message_=None, *args)

static _check_none_model_parameters(explanation_message_=None, **kwargs)

static _explained_error(base_error_message, explanation_message)

static calculate_bins_resolving_power(wavelengths)

Calculate the resolving power of wavelengths bins. The “resolving power” of the bins is defined here as:

R = wavelengths / wavelength_steps

This is different from the “true” (/spectral) resolving power:: R = wavelengths / FWHM_LSF

where FWHM_LSF is the full width half maximum of the line spread function (aka Delta lambda)

Args:: wavelengths: wavelengths at the center of the bins
Returns:: The resolving power for each bins

static calculate_mass_mixing_ratios(pressures, **kwargs)

Template for mass mixing ratio profile function. Here, generate iso-abundant mass mixing ratios profiles.

Args:: pressures: (bar) pressures of the temperature profile **kwargs: other parameters needed to generate the temperature profile
Returns:: A 1D-array containing the temperatures as a function of pressures

static calculate_radial_velocity_amplitude(star_mass, semi_major_axis, **kwargs)

Calculate the planet orbital radial velocity semi-amplitude (aka K_p).

Args:: star_mass: (g) mass of the star semi_major_axis: (cm) orbit semi major axis **kwargs: used to store unnecessary parameters
Returns:: (cm.s-1) the planet orbital radial velocity semi-amplitude

static calculate_mean_molar_masses(mass_mixing_ratios, **kwargs)

Calculate the mean molar masses.

Args:: mass_mixing_ratios: dictionary of the mass mixing ratios of the model **kwargs: used to store unnecessary parameters

Returns:

static calculate_optimal_wavelengths_boundaries(output_wavelengths, shift_wavelengths_function, relative_velocities=None, rebin_range_margin_power=6, **kwargs)

static calculate_planet_radial_velocities(orbital_longitudes, planet_radial_velocity_amplitude, planet_orbital_inclination=90.0, **kwargs)

static calculate_relative_velocities(planet_radial_velocities, system_observer_radial_velocities=0.0, planet_rest_frame_velocity_shift=0.0, **kwargs)

static calculate_spectral_parameters(temperature_profile_function, mass_mixing_ratios_function, mean_molar_masses_function, star_spectral_radiosities_function, planet_star_spectral_radiances_function, radial_velocity_amplitude_function, planet_radial_velocities_function, relative_velocities_function, **kwargs)

Calculate the temperature profile, the mass mixing ratios, the mean molar masses and other parameters required for spectral calculation.

This function define how these parameters are calculated and how they are combined.

Args:: temperature_profile_function: mass_mixing_ratios_function: mean_molar_masses_function: star_spectral_radiosities_function: planet_star_spectral_radiances_function: radial_velocity_amplitude_function: planet_radial_velocities_function: relative_velocities_function: **kwargs:

Returns:

static calculate_spectral_radiosity_spectrum(radtrans: petitRADTRANS.radtrans.Radtrans, temperatures, mass_mixing_ratios, planet_surface_gravity, mean_molar_mass, planet_star_spectral_radiances=None, star_effective_temperature=None, star_radius=None, semi_major_axis=None, cloud_pressure=None, cloud_sigma=None, cloud_sedimentation_factor=None, cloud_particle_radii=None, cloud_particle_size_distribution='lognormal', cloud_hansen_a=None, cloud_hansen_b=None, eddy_diffusion_coefficient=None, scattering_opacity_350nm=None, scattering_opacity_coefficient=None, cloud_photospheric_optical_depth=None, cloud_photospheric_wavelengths_boundaries=None, uniform_gray_opacity=None, irradiation_geometry='dayside_ave', irradiation_inclination=0.0, planet_radius=None, system_distance=None, is_observed=False, calculate_contribution=False, add_cloud_scattering_as_absorption=False, absorption_opacity_function=None, scattering_opacity_function=None, **kwargs)

Wrapper of Radtrans.calc_flux that output wavelengths in um and spectral radiosity in W.m-2/um. Args:

radtrans: temperatures: mass_mixing_ratios: planet_surface_gravity: mean_molar_mass: star_effective_temperature: star_radius: semi_major_axis: planet_star_spectral_radiances: cloud_pressure: cloud_sigma: cloud_sedimentation_factor: cloud_particle_radii: cloud_particle_size_distribution: cloud_hansen_a: cloud_hansen_b: eddy_diffusion_coefficient: scattering_opacity_350nm: scattering_opacity_coefficient: cloud_photospheric_optical_depth: cloud_photospheric_wavelengths_boundaries: uniform_gray_opacity: irradiation_geometry: irradiation_inclination: planet_radius: system_distance: is_observed: calculate_contribution: add_cloud_scattering_as_absorption: absorption_opacity_function: scattering_opacity_function:

Returns:

static calculate_star_spectral_radiosities(star_effective_temperature, **kwargs)

static calculate_planet_star_spectral_radiances(star_spectral_radiosities, star_radius, semi_major_axis, star_spectrum_wavelengths=None, wavelengths=None, **kwargs)

static calculate_temperature_profile(pressures, **kwargs)

Template for temperature profile function. Here, generate an isothermal temperature profile.

Args:: pressures: (bar) pressures of the temperature profile **kwargs: other parameters needed to generate the temperature profile
Returns:: A 1D-array containing the temperatures as a function of pressures

static calculate_transit_spectrum(radtrans: petitRADTRANS.radtrans.Radtrans, temperatures, mass_mixing_ratios, mean_molar_masses, planet_surface_gravity, reference_pressure, planet_radius, cloud_pressure=None, haze_factor=None, cloud_particle_size_distribution='lognormal', cloud_particle_radii=None, cloud_particle_log_normal_width=None, cloud_hansen_a=None, cloud_hansen_b=None, cloud_sedimentation_factor=None, eddy_diffusion_coefficient=None, scattering_opacity_350nm=None, scattering_opacity_coefficient=None, uniform_gray_opacity=None, absorption_opacity_function=None, scattering_opacity_function=None, gravity_is_variable=True, calculate_contribution=False, **kwargs)

Wrapper of Radtrans.calc_transm that output wavelengths in um and transit radius in cm. # TODO move to Radtrans or outside of object

Args:: radtrans: temperatures: mass_mixing_ratios: planet_surface_gravity: mean_molar_masses: reference_pressure: planet_radius: cloud_pressure: haze_factor: cloud_particle_size_distribution: cloud_particle_radii: cloud_particle_log_normal_width: cloud_hansen_a: cloud_hansen_b: cloud_sedimentation_factor: eddy_diffusion_coefficient: scattering_opacity_350nm: scattering_opacity_coefficient: uniform_gray_opacity: absorption_opacity_function: scattering_opacity_function: gravity_is_variable: calculate_contribution:

Returns:

static convolve(input_wavelengths, input_spectrum, new_resolving_power, **kwargs)

Convolve a spectrum to a new resolving power with a Gaussian filter. The original spectrum must have a resolving power very large compared to the target resolving power. The new resolving power is given in that case by:

new_resolving_power = input_wavelengths / FWHM_LSF (FWHM_LSF <=> “Delta_lambda” in Wikipedia)

Therefore, the full width half maximum (FWHM) of the target line spread function (LSF) is given by:: FWHM_LSF = input_wavelengths / new_resolving_power
This FWHM is converted in terms of wavelength steps by:: FWHM_LSF_Delta = FWHM_LSF / Delta_input_wavelengths

where Delta_input_wavelengths is the difference between the edges of the bin. And converted into a Gaussian standard deviation by:

sigma = FWHM_LSF_Delta / 2 * sqrt(2 * ln(2))

Args:: input_wavelengths: (cm) wavelengths of the input spectrum input_spectrum: input spectrum new_resolving_power: resolving power of output spectrum
Returns:: convolved_spectrum: the convolved spectrum at the new resolving power

get_optimal_wavelength_boundaries(output_wavelengths=None, relative_velocities=None)

Return the optimal wavelength boundaries for rebin on output wavelengths. This minimises the number of wavelengths to load and over which to calculate the spectra. Doppler shifting is also taken into account.

The SpectralModel must have in its model_parameters keys:

‘output_wavelengths’: (um) the wavelengths to rebin to

# TODO complete docstring

The SpectralModel can have in its model_parameters keys:

‘relative_velocities’ (cm.s-1) the velocities of the source relative to the observer, in that case the
wavelength range is increased to take into account Doppler shifting

Returns:

optimal_wavelengths_boundaries: (um) the optimal wavelengths boundaries for the spectrum

get_radtrans(): Return the Radtrans object corresponding to this SpectrumModel.

get_reprocessed_spectrum(spectrum, **kwargs)

get_relative_velocities(system_observer_radial_velocities=None, planet_radial_velocity_amplitude=None, planet_rest_frame_velocity_shift=None, orbital_longitudes=None, is_orbiting=None, planet_orbital_inclination=None, planet_radial_velocities=None, full=False, **kwargs)

get_retrieval_velocities(planet_radial_velocity_amplitude_range=None, planet_rest_frame_velocity_shift_range=None, system_observer_radial_velocities=None, orbital_longitudes=None, planet_orbital_inclination=None, **kwargs)

get_spectral_calculation_parameters(pressures=None, wavelengths=None, **kwargs)

get_spectral_radiosity_spectrum_model(radtrans: petitRADTRANS.radtrans.Radtrans, parameters)

get_spectrum_model(radtrans: petitRADTRANS.radtrans.Radtrans, mode='emission', parameters=None, update_parameters=False, telluric_transmittances_wavelengths=None, telluric_transmittances=None, instrumental_deformations=None, noise_matrix=None, scale=False, shift=False, convolve=False, rebin=False, reduce=False)

get_transit_spectrum_model(radtrans: petitRADTRANS.radtrans.Radtrans, parameters)

get_telluric_transmittances(file, relative_velocities=None, rewrite=False, tellurics_resolving_power=1000000.0, **kwargs)

get_volume_mixing_ratios()

static init_radtrans(wavelengths_boundaries, pressures, line_species=None, rayleigh_species=None, continuum_opacities=None, cloud_species=None, opacity_mode='lbl', do_scat_emis=True, lbl_opacity_sampling=1)

init_retrieval(radtrans: petitRADTRANS.radtrans.Radtrans, data, data_wavelengths, data_uncertainties, retrieval_directory, retrieved_parameters, model_parameters=None, retrieval_name='retrieval', mode='emission', update_parameters=False, telluric_transmittances=None, instrumental_deformations=None, noise_matrix=None, scale=False, shift=False, convolve=False, rebin=False, reduce=False, run_mode='retrieval', amr=False, scattering=False, distribution='lognormal', pressures=None, write_out_spec_sample=False, dataset_name='data', **kwargs)

classmethod load(filename)

static modify_spectrum(wavelengths, spectrum, mode, scale=False, shift=False, convolve=False, rebin=False, telluric_transmittances_wavelengths=None, telluric_transmittances=None, airmass=None, instrumental_deformations=None, noise_matrix=None, output_wavelengths=None, relative_velocities=None, planet_radial_velocities=None, star_spectrum_wavelengths=None, star_spectral_radiosities=None, star_observed_spectrum=None, is_observed=False, star_radius=None, system_distance=None, scale_function=None, shift_wavelengths_function=None, convolve_function=None, rebin_spectrum_function=None, **kwargs)

static pipeline(spectrum, **kwargs)

Simplistic pipeline model. Do nothing. To be updated when initializing an instance of retrieval model.

Args:: spectrum: a spectrum
Returns:: spectrum: the spectrum reduced by the pipeline

static rebin_spectrum(input_wavelengths, input_spectrum, output_wavelengths, **kwargs)

static remove_mask(data, data_uncertainties)

static retrieval_model_generating_function(prt_object: petitRADTRANS.radtrans.Radtrans, parameters, pt_plot_mode=None, AMR=False, spectrum_model=None, mode='emission', update_parameters=False, telluric_transmittances_wavelengths=None, telluric_transmittances=None, instrumental_deformations=None, noise_matrix=None, scale=False, shift=False, convolve=False, rebin=False, reduce=False)

static run_retrieval(retrieval: petitRADTRANS.retrieval.Retrieval, n_live_points=100, resume=False, sampling_efficiency=0.8, const_efficiency_mode=False, log_z_convergence=0.5, n_iter_before_update=50, max_iterations=0, save=True, filename='retrieval_parameters', rank=None, **kwargs)

save(file)

static save_parameters(file, **kwargs)

static scale_spectrum(spectrum, star_radius, star_observed_spectrum=None, mode='emission', **kwargs)

static shift_wavelengths(wavelengths_rest, relative_velocities, **kwargs)

static um2hz(wavelength)

update_spectral_calculation_parameters(radtrans: petitRADTRANS.radtrans.Radtrans, **kwargs)

class petitRADTRANS.containers.spectral_model.SpectralModel(pressures, line_species=None, rayleigh_species=None, continuum_opacities=None, cloud_species=None, opacity_mode='lbl', do_scat_emis=True, lbl_opacity_sampling=1, temperatures=None, mass_mixing_ratios=None, mean_molar_masses=None, wavelengths_boundaries=None, wavelengths=None, transit_radii=None, spectral_radiosities=None, times=None, **model_parameters)

Bases: BaseSpectralModel

default_line_species = ['CH4_main_iso', 'CO_all_iso', 'CO2_main_iso', 'H2O_main_iso', 'HCN_main_iso', 'K', 'Na_allard',...

default_rayleigh_species = ['H2', 'He']

default_continuum_opacities = ['H2-H2', 'H2-He']

static _calculate_metallicity_wrap(planet_mass=None, star_metallicity=1.0, atmospheric_mixing=1.0, alpha=-0.68, beta=7.2, verbose=False, **kwargs)

static _calculate_equilibrium_mass_mixing_ratios(pressures, temperatures, co_ratio, metallicity, line_species, included_line_species, carbon_pressure_quench=None, imposed_mass_mixing_ratios=None)

static _convolve_constant(input_wavelengths, input_spectrum, new_resolving_power, input_resolving_power=None, **kwargs)

Convolve a spectrum to a new resolving power with a Gaussian filter. The original spectrum must have a resolving power very large compared to the target resolving power. The new resolving power is given in that case by:

new_resolving_power = input_wavelengths / FWHM_LSF (FWHM_LSF <=> “Delta_lambda” in Wikipedia)

Therefore, the full width half maximum (FWHM) of the target line spread function (LSF) is given by:: FWHM_LSF = input_wavelengths / new_resolving_power
This FWHM is converted in terms of wavelength steps by:: FWHM_LSF_Delta = FWHM_LSF / Delta_input_wavelengths

where Delta_input_wavelengths is the difference between the edges of the bin. And converted into a Gaussian standard deviation by:

sigma = FWHM_LSF_Delta / 2 * sqrt(2 * ln(2))

Args:: input_wavelengths: (cm) wavelengths of the input spectrum input_spectrum: input spectrum new_resolving_power: resolving power of output spectrum
Returns:: convolved_spectrum: the convolved spectrum at the new resolving power

static _convolve_running(input_wavelengths, input_spectrum, new_resolving_power, input_resolving_power=None, **kwargs)

Convolve a spectrum to a new resolving power. The spectrum is convolved using Gaussian filters with a standard deviation

std_dev = R_in(lambda) / R_new(lambda) * input_wavelengths_bins.

Both the input resolving power and output resolving power can vary with wavelength. The input resolving power is given by:

lambda / Delta_lambda

where lambda is the center of a wavelength bin and Delta_lambda is the difference between the edges of the bin.

The weights of the convolution are stored in a (N, M) matrix, with N being the size of the input, and M the size of the convolution kernels. To speed-up calculations, a matrix A of shape (N, M) is built from the inputs such as:

A[i, :] = s[i - M/2], s[i - M/2 + 1], …, s[i - M/2 + M],

with s the input spectrum. The definition of the convolution C of s by constant weights with wavelength is:

C[i] = sum_{j=0}^{j=M-1} s[i - M/2 + j] * weights[j].

Thus, the convolution of s by weights at index i is:: C[i] = sum_{j=0}^{j=M-1} A[i, j] * weights[i, j].
Args:: input_wavelengths: (cm) wavelengths of the input spectrum input_spectrum: input spectrum new_resolving_power: resolving power of output spectrum input_resolving_power: if not None, skip its calculation using input_wavelengths
Returns:: convolved_spectrum: the convolved spectrum at the new resolving power

static calculate_mass_mixing_ratios(pressures, line_species=None, included_line_species='all', temperatures=None, co_ratio=0.55, metallicity=None, carbon_pressure_quench=None, imposed_mass_mixing_ratios=None, heh2_ratio=12 / 37, c13c12_ratio=0.01, planet_mass=None, planet_radius=None, planet_surface_gravity=None, star_metallicity=1.0, atmospheric_mixing=1.0, alpha=-0.68, beta=7.2, use_equilibrium_chemistry=False, fill_atmosphere=False, verbose=False, **kwargs)

Initialize a model mass mixing ratios. Ensure that in any case, the sum of mass mixing ratios is equal to 1. Imposed mass mixing ratios are kept to their imposed value as long as the sum of the imposed values is lower or equal to 1. H2 and He are used as filling gases. The different possible cases are dealt with as follows:

Sum of imposed mass mixing ratios > 1: the mass mixing ratios are scaled down, conserving the ratio

between them. Non-imposed mass mixing ratios are set to 0. - Sum of imposed mass mixing ratio of all imposed species < 1: if equilibrium chemistry is used or if H2 and He are imposed species, the atmosphere will be filled with H2 and He respecting the imposed H2/He ratio. Otherwise, the heh2_ratio parameter is used. - Sum of imposed and non-imposed mass mixing ratios > 1: the non-imposed mass mixing ratios are scaled down, conserving the ratios between them. Imposed mass mixing ratios are unchanged. - Sum of imposed and non-imposed mass mixing ratios < 1: if equilibrium chemistry is used or if H2 and He are imposed species, the atmosphere will be filled with H2 and He respecting the imposed H2/He ratio. Otherwise, the heh2_ratio parameter is used.

When using equilibrium chemistry with imposed mass mixing ratios, imposed mass mixing ratios are set to their imposed value regardless of chemical equilibrium consistency.

Args:

pressures: (bar) pressures of the mass mixing ratios line_species: list of line species, required to manage naming differences between opacities and chemistry included_line_species: which line species of the list to include, mass mixing ratio set to 0 otherwise temperatures: (K) temperatures of the mass mixing ratios, used with equilibrium chemistry co_ratio: carbon over oxygen ratios of the model, used with equilibrium chemistry metallicity: ratio between heavy elements and H2 + He compared to solar, used with equilibrium chemistry carbon_pressure_quench: (bar) pressure where the carbon species are quenched, used with equilibrium

chemistry

imposed_mass_mixing_ratios: imposed mass mixing ratios heh2_ratio: H2 over He mass mixing ratio c13c12_ratio: 13C over 12C mass mixing ratio in equilibrium chemistry planet_mass: (g) mass of the planet; if None, planet mass is calculated from planet radius and surface

gravity, used to calulate metallicity

planet_radius: (cm) radius of the planet, used to calculate the mass planet_surface_gravity: (cm.s-2) surface gravity of the planet, used to calculate the mass star_metallicity: (solar metallicity) metallicity of the planet’s star, used to calulate metallicity atmospheric_mixing: scaling factor [0, 1] representing how well metals are mixed in the atmosphere, used to

calulate metallicity

alpha: power of the mass-metallicity relation beta: scaling factor of the mass-metallicity relation use_equilibrium_chemistry: if True, use pRT equilibrium chemistry module fill_atmosphere: if True, the atmosphere will be filled with H2 and He (using h2h2_ratio)

if the sum of MMR is < 1 TODO use None and a dict of species instead of a flag

verbose: if True, print additional information

Returns:

A dictionary containing the mass mixing ratios.

static calculate_scaled_metallicity(planet_mass, star_metallicity=1.0, atmospheric_mixing=1.0, alpha=-0.68, beta=7.2)

Calculate the scaled metallicity of a planet. The relation used is a power law. Default parameters come from the source.

Source: Mordasini et al. 2014 (https://www.aanda.org/articles/aa/pdf/2014/06/aa21479-13.pdf)

Args:: planet_mass: (g) mass of the planet star_metallicity: metallicity of the planet in solar metallicity atmospheric_mixing: scaling factor [0, 1] representing how well metals are mixed in the atmosphere alpha: power of the relation beta: scaling factor of the relation
Returns:: An estimation of the planet atmospheric metallicity in solar metallicity.

static calculate_spectral_parameters(temperature_profile_function, mass_mixing_ratios_function, mean_molar_masses_function, star_spectral_radiosities_function, planet_star_spectral_radiances_function, radial_velocity_amplitude_function, planet_radial_velocities_function, relative_velocities_function, wavelengths=None, pressures=None, line_species=None, metallicity_function=None, mass2surface_gravity_function=None, surface_gravity2mass_function=None, **kwargs)

Calculate the temperature profile, the mass mixing ratios, the mean molar masses and other parameters required for spectral calculation.

This function define how these parameters are calculated and how they are combined.

Args:: temperature_profile_function: mass_mixing_ratios_function: mean_molar_masses_function: star_spectral_radiosities_function: planet_star_spectral_radiances_function: radial_velocity_amplitude_function: planet_radial_velocities_function: relative_velocities_function: **kwargs:

Returns:

static calculate_temperature_profile(pressures, temperature_profile_mode='isothermal', temperature=None, intrinsic_temperature=None, planet_surface_gravity=None, metallicity=None, guillot_temperature_profile_gamma=0.4, guillot_temperature_profile_kappa_ir_z0=0.01, **kwargs)

Template for temperature profile function. Here, generate an isothermal temperature profile.

Args:: pressures: (bar) pressures of the temperature profile **kwargs: other parameters needed to generate the temperature profile
Returns:: A 1D-array containing the temperatures as a function of pressures

static convolve(input_wavelengths, input_spectrum, new_resolving_power, constance_tolerance=1e-06, **kwargs)

Args:: input_wavelengths: (cm) wavelengths of the input spectrum input_spectrum: input spectrum new_resolving_power: resolving power of output spectrum constance_tolerance: relative tolerance on input resolving power to apply constant or running convolutions
Returns:: convolved_spectrum: the convolved spectrum at the new resolving power

get_orbital_phases(phase_start, orbital_period)

get_spectral_calculation_parameters(pressures=None, wavelengths=None, line_species=None, **kwargs)

Initialize the temperature profile, mass mixing ratios and mean molar mass of a model.

Args:: pressures: wavelengths: line_species:

Returns:

static mass2surface_gravity(planet_mass, planet_radius, verbose=False, **kwargs)

static pipeline(spectrum, **kwargs)

Interface with simple_pipeline.

Args:: spectrum: spectrum to reduce **kwargs: simple_pipeline arguments
Returns:: The reduced spectrum, matrix, and uncertainties

static surface_gravity2mass(planet_surface_gravity, planet_radius, verbose=False, **kwargs)

update_spectral_calculation_parameters(radtrans: petitRADTRANS.radtrans.Radtrans, **parameters)

petitRADTRANS.containers.spectral_model

Module Contents

Classes

`petitRADTRANS.containers.spectral_model`