petitRADTRANS.__file_conversion

Stores functions that convert files from a format to another.

The functions in this module are stored for the sake of keeping trace of changes made to files. They are intended to be used only once.

Attributes

prt_emcee_mode
load_mpi
load_mpi
MPI
rank
comm
comm

Functions

__get_prt2_input_data_subpaths(→ dict[str, str])
__remove_files(old_files)
_clean_input_data_mac_junk_files([path_input_data])
__print_missing_data_file_message(obj, object_name, ...)
__print_skipping_message(hdf5_opacity_file)
_chemical_table_dat2h5([path_input_data, rewrite, ...])
_continuum_cia_dat2h5([path_input_data, rewrite, ...])	Using ExoMol units for HDF5 files.
_continuum_clouds_opacities_dat2h5([path_input_data, ...])	Using ExoMol units for HDF5 files.
_correlated_k_opacities_dat2h5([path_input_data, ...])
_correlated_k_opacities_dat2h5_external_species(...[, ...])
_get_base_cia_names()
_get_base_cloud_names()
_get_base_correlated_k_names()	Only used for file conversion from pRT2 to pRT3.
_get_base_line_by_line_names()	Only used for file conversion from pRT2 to pRT3.
_get_default_rebinning_wavelength_range()
_get_prt2_cia_names()
_get_prt2_cloud_names()
_get_prt2_correlated_k_names()
_get_prt2_line_by_line_names()
_line_by_line_opacities_dat2h5([path_input_data, ...])	Using ExoMol units for HDF5 files.
_phoenix_spec_dat2h5([path_input_data, rewrite, ...])	Convert a PHOENIX stellar spectrum in .dat format to HDF5 format.
_refactor_input_data_folder([path_input_data])
_sort_pressure_temperature_grid(...)
bin_species_exok(species, resolution)	This function uses exo-k to bin the c-k table of a
continuum_clouds_opacities_dat2h5(input_directory, ...)	Using ExoMol units for HDF5 files.
continuum_clouds_opacities_dat2h5_external_species(...)
fits_output(wavelength, spectrum, covariance, object_name)	Generate a fits file that can be used as an input to a pRT retrieval.
format2petitradtrans(load_function, ...[, charge, ...])	Convert opacities loaded with the specified load function into petitRADTRANS line-by-line and correlated-k
get_opacity_filename(resolving_power, ...[, ...])
line_by_line_opacities_dat2h5(directory, output_name, ...)	Using ExoMol units for HDF5 files.
load_dace(file, file_extension, molmass[, ...])	Read a DACE opacity file.
load_exocross(file, file_extension[, molmass, ...])
rebin_ck_line_opacities(input_file, target_resolving_power)
rebin_multiple_ck_line_opacities(target_resolving_power)
write_cia_opacities(hdf5_cia_file, molecules, ...[, ...])
write_cloud_opacities(hdf5_opacity_file, ...[, doi, ...])
write_correlated_k(file, doi, wavenumbers, ...[, ...])
write_line_by_line(file, doi, wavenumbers, opacities, ...)
convert_all([path_input_data, memory_map_mode, ...])

Module Contents

petitRADTRANS.__file_conversion.prt_emcee_mode

petitRADTRANS.__file_conversion.load_mpi = True

petitRADTRANS.__file_conversion.load_mpi = False

petitRADTRANS.__file_conversion.MPI = None

petitRADTRANS.__file_conversion.rank = 0

petitRADTRANS.__file_conversion.comm = None

petitRADTRANS.__file_conversion.comm

petitRADTRANS.__file_conversion.__get_prt2_input_data_subpaths() → dict[str, str]

petitRADTRANS.__file_conversion.__remove_files(old_files)

petitRADTRANS.__file_conversion._clean_input_data_mac_junk_files(path_input_data=petitradtrans_config_parser.get_input_data_path())

petitRADTRANS.__file_conversion.__print_missing_data_file_message(obj, object_name, directory)

petitRADTRANS.__file_conversion.__print_skipping_message(hdf5_opacity_file)

petitRADTRANS.__file_conversion._chemical_table_dat2h5(path_input_data=petitradtrans_config_parser.get_input_data_path(), rewrite=False, old_paths=False, clean=False)

petitRADTRANS.__file_conversion._continuum_cia_dat2h5(path_input_data=petitradtrans_config_parser.get_input_data_path(), rewrite=False, output_directory=None, old_paths=False, clean=False)

Using ExoMol units for HDF5 files.

petitRADTRANS.__file_conversion._continuum_clouds_opacities_dat2h5(path_input_data=petitradtrans_config_parser.get_input_data_path(), rewrite=False, old_paths=False, clean=False)

Using ExoMol units for HDF5 files.

petitRADTRANS.__file_conversion._correlated_k_opacities_dat2h5(path_input_data=petitradtrans_config_parser.get_input_data_path(), rewrite=False, old_paths=False, clean=False, external_single_species=False, path_to_external_species_opacity_folder=None, external_species_longname=None, external_species_doi=None, external_species_contributor=None, external_species_description=None, external_species_molmass=None)

petitRADTRANS.__file_conversion._correlated_k_opacities_dat2h5_external_species(path_to_species_opacity_folder, path_prt2_input_data, longname, doi=None, contributor=None, description=None, molmass=None)

petitRADTRANS.__file_conversion._get_base_cia_names()

petitRADTRANS.__file_conversion._get_base_cloud_names()

petitRADTRANS.__file_conversion._get_base_correlated_k_names()

Only used for file conversion from pRT2 to pRT3.

petitRADTRANS.__file_conversion._get_base_line_by_line_names()

Only used for file conversion from pRT2 to pRT3.

petitRADTRANS.__file_conversion._get_default_rebinning_wavelength_range()

petitRADTRANS.__file_conversion._get_prt2_cia_names()

petitRADTRANS.__file_conversion._get_prt2_cloud_names()

petitRADTRANS.__file_conversion._get_prt2_correlated_k_names()

petitRADTRANS.__file_conversion._get_prt2_line_by_line_names()

petitRADTRANS.__file_conversion._line_by_line_opacities_dat2h5(path_input_data=petitradtrans_config_parser.get_input_data_path(), memory_map_mode=False, rewrite=False, old_paths=False, clean=False)

Using ExoMol units for HDF5 files.

petitRADTRANS.__file_conversion._phoenix_spec_dat2h5(path_input_data=petitradtrans_config_parser.get_input_data_path(), rewrite=False, old_paths=False, clean=False)

Convert a PHOENIX stellar spectrum in .dat format to HDF5 format.

petitRADTRANS.__file_conversion._refactor_input_data_folder(path_input_data=petitradtrans_config_parser.get_input_data_path())

petitRADTRANS.__file_conversion._sort_pressure_temperature_grid(pressure_temperature_grid_file)

petitRADTRANS.__file_conversion.bin_species_exok(species: list[str], resolution: float)

This function uses exo-k to bin the c-k table of a multiple species to a desired (lower) spectral resolution.

Args:

speciesstring

The name of the species

resolutionint

The desired spectral resolving power.

petitRADTRANS.__file_conversion.continuum_clouds_opacities_dat2h5(input_directory, output_name, cloud_species, doi, cloud_species_mode=None, path_input_data=petitradtrans_config_parser.get_input_data_path(), description=None, cloud_path=None, path_input_files=None, path_reference_files=None, rewrite=False, clean=False)

Using ExoMol units for HDF5 files.

petitRADTRANS.__file_conversion.continuum_clouds_opacities_dat2h5_external_species(path_to_species_opacity_folder, longname, cloud_material_density, save_folder='converted_cloud_opacities', doi=None, description=None, wavelength_limit=None)

petitRADTRANS.__file_conversion.fits_output(wavelength, spectrum, covariance, object_name, output_dir='', correlation=None)

Generate a fits file that can be used as an input to a pRT retrieval.

Args:

wavelengthnumpy.ndarray

The wavelength bin centers in micron. dim(N)

spectrumnumpy.ndarray

The flux density in W/m2/micron at each wavelength bin. dim(N)

covariancenumpy.ndarray

The covariance of the flux in (W/m2/micron)^2 dim(N,N)

object_namestring

The name of the object, used for file naming.

output_dirstring

The parent directory of the output file.

correlationnumpy.ndarray

The correlation matrix of the flux points (See Brogi & Line 2018, https://arxiv.org/pdf/1811.01681.pdf)

Returns:

hdulastropy.fits.HDUlist

The HDUlist object storing the spectrum.

petitRADTRANS.__file_conversion.format2petitradtrans(load_function, opacities_directory: str, natural_abundance: bool, source: str, doi: str, species: str, charge: str = '', cloud_info: str = '', contributor: str = None, description: str = None, opacity_files_extension: str = None, spectral_dimension_file: str = None, path_input_data: str = petitradtrans_config_parser.get_input_data_path(), rebin: bool = True, save_correlated_k: bool = True, correlated_k_resolving_power: float = 1000, samples: numpy.ndarray = None, weights: numpy.ndarray = None, save_line_by_line: bool = True, line_by_line_wavelength_boundaries: numpy.ndarray = None, standard_line_by_line_wavelength_boundaries: numpy.ndarray = None, rewrite: bool = False, use_legacy_correlated_k_wavenumbers_sampling: bool = False)

Convert opacities loaded with the specified load function into petitRADTRANS line-by-line and correlated-k opacities.

Args:

load_function:

String (‘dace’ or ‘exocross’), or function loading the opacities. If ‘dace’, the DACE (https://dace.unige.ch/opacityDatabase/) opacity built-in loading function is used. If ‘exocross’, the ExoCross (Trovemaster/exocross) opacity built-in loading function is used. If a function is used, it must have the following arguments, in that order:

• file: the file name of a file containing the opacities (automatically taken from opacities_directory)

• file_extension: see opacity_files_extension below

• molmass: molar mass of the species (automatically set)

• wavelength_file: see spectral_dimension_file below

• wavenumbers_petitradtrans_line_by_line: the petitRADTRANS wavenumber grid for line-by-line opacities (automatically set)

• save_line_by_line: see save_line_by_line below

• rebin: see rebin below

• selection: indices corresponding to the wavenumbers to be extracted

Not all of the above arguments have to be used. The function must output the following, in that order:

• cross_sections: (cm2/molecule) the cross-sections

• cross_sections_line_by_line: (cm2/molecule), the cross-sections,

  interpolated to wavenumbers_petitradtrans_line_by_line

• wavenumbers: (cm-1) the wavenumbers corresponding to cross-sections

• pressure: (bar) the pressure of the cross-sections

• temperature: (K) the temperature of the cross-sections

The cross_sections, cross_sections_line_by_line and wavenumbers must be returned in increasing wavenumber order.

opacities_directory:

Directory in which the opacity files are stored.

natural_abundance:

If True, the opacities are considered coming from the natural (Earth’s) occurring isotopologue mix, instead of from a single isotope.

source:

Name of the opacities’ source (e.g., ‘POKAZATEL’).

doi:

DOI of the opacities’ source

species:

Chemical formula of the species (e.g. ‘H2O’)

charge:

Charge of the species (e.g. ‘2+’)

cloud_info:

Cloud additional info (physical state, internal structure, space group). See the petitRADTRANS cloud filename convention for more information.

contributor:

Contributor that helped obtained the opacities.

description:

Additional description on the opacities.

opacity_files_extension:

The extension of the opacity files.

spectral_dimension_file:

File containing the opacities’ wavelengths.

path_input_data:

Path to the input data directory.

rebin:

If true, rebin the opacities to the petitRADTRANS standard wavenumber grid. Should be True in most cases.

save_correlated_k:

If True, convert and save the opacities in correlated-k (‘c-k’) format.

correlated_k_resolving_power:

Resolving power at which to convert the opacities, for the correlated-k case.

samples:

Array containing the correlated-k samples.

weights:

Array containing the correlated-k weights.

save_line_by_line:

If True, convert and save the opacities in line-by-line (‘lbl’) format.

line_by_line_wavelength_boundaries:

Wavelength boundaries to use for the line-by-line conversion.

standard_line_by_line_wavelength_boundaries:

Wavelength boundaries to use when generating the lbl standard petitRADTRANS wavelengths.

rewrite:

if True, rewrite existing converted files

use_legacy_correlated_k_wavenumbers_sampling:

If True, use the legacy (pRT2) way to sample the correlated-k wavenumbers.

petitRADTRANS.__file_conversion.get_opacity_filename(resolving_power, wavelength_boundaries, species_isotopologue_name, source, natural_abundance='', charge='', cloud_info='')

petitRADTRANS.__file_conversion.line_by_line_opacities_dat2h5(directory, output_name, molmass, doi, path_input_data=petitradtrans_config_parser.get_input_data_path(), contributor=None, description=None, opacities_pressures=None, opacities_temperatures=None, line_paths=None, memory_map_mode=False, rewrite=False, clean=False)

Using ExoMol units for HDF5 files.

petitRADTRANS.__file_conversion.load_dace(file, file_extension, molmass, wavelength_file=None, wavenumbers_petitradtrans_line_by_line=None, save_line_by_line=False, rebin=True, selection=None)

Read a DACE opacity file.

petitRADTRANS.__file_conversion.load_exocross(file, file_extension, molmass=None, wavelength_file=None, wavenumbers_petitradtrans_line_by_line=None, save_line_by_line=False, rebin=True, selection=None)

petitRADTRANS.__file_conversion.rebin_ck_line_opacities(input_file, target_resolving_power, wavenumber_grid=None, rewrite=False)

petitRADTRANS.__file_conversion.rebin_multiple_ck_line_opacities(target_resolving_power, paths=None, species=None, rewrite=False)

petitRADTRANS.__file_conversion.write_cia_opacities(hdf5_cia_file, molecules, wavenumbers, wavelengths, alpha, temperatures, doi='', description='')

petitRADTRANS.__file_conversion.write_cloud_opacities(hdf5_opacity_file, cloud_species, wavenumbers, cloud_wavelengths, cloud_absorption_opacities, cloud_scattering_opacities, cloud_asymmetry_parameter, cloud_particles_densities, cloud_particles_radii, cloud_particles_radius_bins, doi='', description='')

petitRADTRANS.__file_conversion.write_correlated_k(file, doi, wavenumbers, wavenumbers_bins_edges, cross_sections, mol_mass, species, opacities_pressures, opacities_temperatures, g_gauss, weights_gauss, wavelengths=None, n_g=None, contributor=None, description=None)

petitRADTRANS.__file_conversion.write_line_by_line(file, doi, wavenumbers, opacities, mol_mass, species, opacities_pressures, opacities_temperatures, wavelengths=None, contributor=None, description=None)

petitRADTRANS.__file_conversion.convert_all(path_input_data=petitradtrans_config_parser.get_input_data_path(), memory_map_mode=False, rewrite=False, old_paths=False, clean=False)