radis.io package

Submodules

Module contents

Parsers for various databases

fetch_astroquery(molecule, isotope, wmin, wmax, verbose=True, cache=True, expected_metadata={}, engine='pytables-fixed', output='pandas')[source]

Download a HITRAN line database to a Pandas DataFrame.

Wrapper to the fetch function of Astroquery [1]_ (itself based on [HAPI])

Note

if using, cite [HAPI] and [HITRAN-2020]

Parameters:

  • molecule (str, or int) – molecule name or identifier

  • isotope (int) – isotope number

  • wmin, wmax (float (cm-1)) – wavenumber min and max

Other Parameters:

  • verbose (boolean) – Default True

  • cache (boolean or 'regen') – if True, tries to find a .h5 cache file in the Astroquery cache_location, that would match the requirements. If not found, downloads it and saves the line dataframe as a .h5 file in the Astroquery. If 'regen', delete existing cache file to regenerate it.

  • expected_metadata (dict) – if cache=True, check that the metadata in the cache file correspond to these attributes. Arguments molecule, isotope, wmin, wmax are already added by default.

  • output (str) – specifies the type of returned data

References

See also

astroquery.hitran.core.Hitran.query_lines_async(), astroquery.query.BaseQuery.cache_location

fetch_exomol(molecule, database=None, local_databases=None, databank_name='EXOMOL-{molecule}', isotope='1', load_wavenum_min=None, load_wavenum_max=None, columns=None, cache=True, verbose=True, clean_cache_files=True, return_local_path=False, return_partition_function=False, engine='default', output='pandas', skip_optional_data=True, **kwargs)[source]

Stream ExoMol file from EXOMOL website. Unzip and build a HDF5 file directly.

Returns a Pandas DataFrame containing all lines.

Parameters:

  • molecule (str) – ExoMol molecule

  • database (str) – database name. Ex: POKAZATEL or BT2 for H2O. See KNOWN_EXOMOL_DATABASE_NAMES. If None and there is only one database available, use it.

  • local_databases (str) – where to create the RADIS HDF5 files. Default "~/.radisdb/exomol". Can be changed in radis.config["DEFAULT_DOWNLOAD_PATH"] or in ~/radis.json config file

  • databank_name (str) – name of the databank in RADIS Configuration file Default "EXOMOL-{molecule}"

  • isotope (str or int) – load only certain isotopes, sorted by terrestrial abundances : '1', '2', etc. Default 1.

    Note

    In RADIS, isotope abundance is included in the line intensity calculation. However, the terrestrial abundances used may not be relevant to non-terrestrial applications. By default, the abundance is given reading HITRAN data. If the molecule does not exist in the HITRAN database, the abundance is read from the radis/radis_default.json configuration file, which can be modified by editing radis.config after import or directly by editing the user ~/radis.json user configuration file (overwrites radis_default.json). In the radis/radis_default.json file, values were calculated with a simple model based on the terrestrial isotopic abundance of each element.

  • load_wavenum_min, load_wavenum_max (float (cm-1)) – load only specific wavenumbers.

  • columns (list of str) – list of columns to load. If None, returns all columns in the file.

Other Parameters:

  • cache (bool, or 'regen' or 'force') – if True, use existing HDF5 file. If False or 'regen', rebuild it. If 'force', crash if not cache file found. Default True.

  • verbose (bool)

  • clean_cache_files (bool) – if True clean downloaded cache files after HDF5 are created.

  • return_local_path (bool) – if True, also returns the path of the local database file.

  • return_partition_function (bool) – if True, also returns a PartFuncExoMol object.

  • engine (‘vaex’, ‘feather’) – which memory-mapping library to use. If ‘default’ use the value from ~/radis.json

  • output (‘pandas’, ‘vaex’, ‘jax’) – format of the output DataFrame. If 'jax', returns a dictionary of jax arrays. If 'vaex', output is a vaex.dataframe.DataFrameLocal

    Note

    Vaex DataFrames are memory-mapped. They do not take any space in RAM and are extremely useful to deal with the largest databases.

  • skip_optional_data (bool) – If False, fetch all fields which are marked as available in the ExoMol definition file. If True, load only the first 4 columns of the states file (“i”, “E”, “g”, “J”). The structure of the columns above 5 depend on the the definitions file (*.def) and the Exomol version. If skip_optional_data=False, two errors may occur:

Returns:

  • df (pd.DataFrame or vaex.dataframe.DataFrameLocal) – Line list A HDF5 file is also created in local_databases and referenced in the RADIS config file with name databank_name

  • local_path (str) – path of local database file if return_local_path

Examples

Calculate a spectrum from ExoMol

Calculate a spectrum from ExoMol

Notes

if using load_only_wavenum_above/below or isotope, the whole database is anyway downloaded and uncompressed to local_databases fast access .HDF5 files (which will take a long time on first call). Only the expected wavenumber range & isotopes are returned. The .HFD5 parsing uses hdf2df()

References

See also

fetch_hitran(), fetch_hitemp(), fetch_kurucz(), hdf2df()

fetch_geisa(molecule, local_databases=None, databank_name='GEISA-{molecule}', isotope=None, load_wavenum_min=None, load_wavenum_max=None, columns=None, cache=True, verbose=True, chunksize=100000, clean_cache_files=True, return_local_path=False, engine='default', output='pandas', parallel=True)[source]

Stream GEISA file from GEISA website. Unzip and build a HDF5 file directly.

Returns a Pandas DataFrame containing all lines.

Parameters:

  • molecule (all 58 GEISA 2020 molecules. See here https://geisa.aeris-data.fr/interactive-access/?db=2020&info=ftp)

  • local_databases (str) – where to create the RADIS HDF5 files. Default "~/.radisdb/geisa". Can be changed in radis.config["DEFAULT_DOWNLOAD_PATH"] or in ~/radis.json config file

  • databank_name (str) – name of the databank in RADIS Configuration file Default "GEISA-{molecule}"

  • isotope (str, int or None) – load only certain isotopes : '2', '1,2', etc. If None, loads everything. Default None.

  • load_wavenum_min, load_wavenum_max (float (cm-1)) – load only specific wavenumbers.

  • columns (list of str) – list of columns to load. If None, returns all columns in the file.

Other Parameters:

  • cache (True, False, 'regen' or 'force') – if True, use existing HDF5 file. If False or 'regen', rebuild it. If 'force', raise an error if cache file cannot be used (useful for debugging). Default True.

  • verbose (bool)

  • chunksize (int) – number of lines to process at a same time. Higher is usually faster but can create Memory problems and keep the user uninformed of the progress.

  • clean_cache_files (bool) – if True clean downloaded cache files after HDF5 are created.

  • return_local_path (bool) – if True, also returns the path of the local database file.

  • engine (‘pytables’, ‘vaex’, ‘default’) – which HDF5 library to use to parse local files. If ‘default’ use the value from ~/radis.json

  • output (‘pandas’, ‘vaex’, ‘jax’) – format of the output DataFrame. If 'jax', returns a dictionary of jax arrays.

  • parallel (bool) – if True, uses joblib.parallel to load database with multiple processes

Returns:

  • df (pd.DataFrame or vaex.dataframe.DataFrameLocal) – Line list A HDF5 file is also created in local_databases and referenced in the RADIS config file with name databank_name

  • local_path (str) – path of local database file if return_local_path

Examples

from radis import fetch_geisa
df = fetch_geisa("CO")
print(df.columns)
>>> Index(['wav', 'int', 'airbrd', 'El', 'globu', 'globl', 'locu', 'locl',
    'Tdpgair', 'isoG', 'mol', 'idG', 'id', 'iso', 'A', 'selbrd', 'Pshft',
    'Tdpair', 'ierrA', 'ierrB', 'ierrC', 'ierrF', 'ierrO', 'ierrR', 'ierrN',
    'Tdpgself', 'ierrS', 'Pshfts', 'ierrT', 'Tdppself', 'ierrU'],
    dtype='object')

Notes

if using load_only_wavenum_above/below or isotope, the whole database is anyway downloaded and uncompressed to local_databases fast access .HDF5 files (which will take a long time on first call). Only the expected wavenumber range & isotopes are returned. The .HFD5 parsing uses hdf2df()

if a registered entry already exists and radis.config["ALLOW_OVERWRITE"] is True: - if any situation arises where the databank needs to be re-downloaded, the possible urls are attempted in their usual order of preference, as if the databank hadn’t been registered, rather than directly re-downloading from the same url that was previously registered, in case e.g. a new linelist has been uploaded since the databank was previously registered - If no partition function file is registered, e.g because one wasn’t available server-side when the databank was last registered, an attempt is still made again to download it, to account for e.g. the case where one has since been uploaded

See also

fetch_hitran(), fetch_exomol(), fetch_hitemp(), fetch_kurucz(), hdf2df(), fetch_databank()

fetch_hitemp(molecule, local_databases=None, databank_name='HITEMP-{molecule}', isotope=None, load_wavenum_min=None, load_wavenum_max=None, columns=None, cache=True, verbose=True, chunksize=100000, clean_cache_files=True, return_local_path=False, engine='default', output='pandas', parallel=True, database='most_recent')[source]

Stream HITEMP file from HITRAN website. Unzip and build a HDF5 file directly.

Returns a Pandas DataFrame containing all lines.

Parameters:

  • molecule ("H2O", "CO2", "N2O", "CO", "CH4", "NO", "NO2", "OH") – HITEMP molecule. See https://hitran.org/hitemp/

  • local_databases (str) – where to create the RADIS HDF5 files. Default "~/.radisdb/hitemp". Can be changed in radis.config["DEFAULT_DOWNLOAD_PATH"] or in ~/radis.json config file

  • databank_name (str) – name of the databank in RADIS Configuration file Default "HITEMP-{molecule}"

  • isotope (str, int or None) – load only certain isotopes : '2', '1,2', etc. If None, loads everything. Default None.

  • load_wavenum_min, load_wavenum_max (float (cm-1)) – load only specific wavenumbers.

  • columns (list of str) – list of columns to load. If None, returns all columns in the file.

Other Parameters:

  • cache (True, False, 'regen' or 'force') – if True, use existing HDF5 file. If False or 'regen', rebuild it. If 'force', raise an error if cache file cannot be used (useful for debugging). Default True.

  • verbose (bool)

  • chunksize (int) – number of lines to process at a same time. Higher is usually faster but can create Memory problems and keep the user uninformed of the progress.

  • clean_cache_files (bool) – if True clean downloaded cache files after HDF5 are created.

  • return_local_path (bool) – if True, also returns the path of the local database file.

  • engine (‘pytables’, ‘vaex’, ‘default’) – which HDF5 library to use to parse local files. If ‘default’ use the value from ~/radis.json

  • output (‘pandas’, ‘vaex’, ‘jax’) – format of the output DataFrame. If 'jax', returns a dictionary of jax arrays. If 'vaex', output is a vaex.dataframe.DataFrameLocal

    Note

    Vaex DataFrames are memory-mapped. They do not take any space in RAM and are extremely useful to deal with the largest databases.

  • parallel (bool) – if True, uses joblib.parallel to load database with multiple processes

  • database (str) – The database version to retrieve. Options include: - "most_recent": Fetches the latest available database version. - A four-digit year (e.g., "2010"): Selects a specific version, such as the 2010 or 2019 database for CO.

    If not provided, the default is "most_recent".

Returns:

  • df (pd.DataFrame) – Line list A HDF5 file is also created in local_databases and referenced in the RADIS config file with name databank_name

  • local_path (str) – path of local database file if return_local_path

Examples

from radis import fetch_hitemp
df = fetch_hitemp("CO")
print(df.columns)
>>> Index(['id', 'iso', 'wav', 'int', 'A', 'airbrd', 'selbrd', 'El', 'Tdpair',
    'Pshft', 'ierr', 'iref', 'lmix', 'gp', 'gpp', 'Fu', 'branch', 'jl',
    'syml', 'Fl', 'vu', 'vl'],
    dtype='object')

Download the HITRAN database

Download the HITRAN database

Scale Linestrengths of carbon-monoxide

Scale Linestrengths of carbon-monoxide

Notes

if using load_only_wavenum_above/below or isotope, the whole database is anyway downloaded and uncompressed to local_databases fast access .HDF5 files (which will take a long time on first call). Only the expected wavenumber range & isotopes are returned. The .HFD5 parsing uses hdf2df()

if a registered entry already exists and radis.config["ALLOW_OVERWRITE"] is True: - if any situation arises where the databank needs to be re-downloaded, the possible urls are attempted in their usual order of preference, as if the databank hadn’t been registered, rather than directly re-downloading from the same url that was previously registered, in case e.g. a new linelist has been uploaded since the databank was previously registered - If no partition function file is registered, e.g because one wasn’t available server-side when the databank was last registered, an attempt is still made again to download it, to account for e.g. the case where one has since been uploaded

See also

fetch_hitran(), fetch_exomol(), fetch_geisa(), fetch_kurucz(), hdf2df(), fetch_databank()

fetch_hitran(molecule, extra_params=None, local_databases=None, databank_name='HITRAN-{molecule}', isotope=None, load_wavenum_min=None, load_wavenum_max=None, columns=None, cache=True, verbose=True, clean_cache_files=True, return_local_path=False, engine='default', output='pandas', parallel=True, parse_quanta=True)[source]

Download all HITRAN lines from HITRAN website. Unzip and build a HDF5 file directly.

Returns a Pandas DataFrame containing all lines.

Parameters:

  • molecule (str) – one specific molecule name, listed in HITRAN molecule metadata. See https://hitran.org/docs/molec-meta/ Example: “H2O”, “CO2”, etc.

  • local_databases (str) – where to create the RADIS HDF5 files. Default "~/.radisdb/hitran". Can be changed in radis.config["DEFAULT_DOWNLOAD_PATH"] or in ~/radis.json config file

  • databank_name (str) – name of the databank in RADIS Configuration file Default "HITRAN-{molecule}"

  • isotope (str) – load only certain isotopes : '2', '1,2', etc. If None, loads everything. Default None.

  • load_wavenum_min, load_wavenum_max (float (cm-1)) – load only specific wavenumbers.

  • columns (list of str) – list of columns to load. If None, returns all columns in the file.

  • extra_params (‘all’ or None) – Downloads all additional columns available in the HAPI database for the molecule including parameters like gamma_co2, n_co2 that are required to calculate spectrum in co2 diluent. For eg:

    from radis.io.hitran import fetch_hitran
df = fetch_hitran('CO', extra_params='all', cache='regen') # cache='regen' to regenerate new database with additional columns
Other Parameters:

  • cache (True, False, 'regen' or 'force') – if True, use existing HDF5 file. If False or 'regen', rebuild it. If 'force', raise an error if cache file cannot be used (useful for debugging). Default True.

  • verbose (bool)

  • clean_cache_files (bool) – if True clean downloaded cache files after HDF5 are created.

  • return_local_path (bool) – if True, also returns the path of the local database file.

  • engine (‘pytables’, ‘vaex’, ‘default’) – which HDF5 library to use. If ‘default’ use the value from ~/radis.json

  • output (‘pandas’, ‘vaex’, ‘jax’) – format of the output DataFrame. If 'jax', returns a dictionary of jax arrays. If 'vaex', output is a vaex.dataframe.DataFrameLocal

    Note

    Vaex DataFrames are memory-mapped. They do not take any space in RAM and are extremely useful to deal with the largest databases.

  • parallel (bool) – if True, uses joblib.parallel to load database with multiple processes

  • parse_quanta (bool) – if True, parse local & global quanta (required to identify lines for non-LTE calculations ; but sometimes lines are not labelled.)

Returns:

  • df (pd.DataFrame or vaex.dataframe.DataFrameLocal) – Line list A HDF5 file is also created in local_databases and referenced in the RADIS config file with name databank_name

  • local_path (str) – path of local database file if return_local_path

Examples

from radis.io.hitran import fetch_hitran
df = fetch_hitran("CO")
print(df.columns)
>>> Index(['id', 'iso', 'wav', 'int', 'A', 'airbrd', 'selbrd', 'El', 'Tdpair',
    'Pshft', 'gp', 'gpp', 'branch', 'jl', 'vu', 'vl'],
    dtype='object')

Explore Line Database Parameters

Explore Line Database Parameters

Download the HITRAN database

Download the HITRAN database

Notes

if using load_only_wavenum_above/below or isotope, the whole database is anyway downloaded and uncompressed to local_databases fast access .HDF5 files (which will take a long time on first call). Only the expected wavenumber range & isotopes are returned. The .HFD5 parsing uses hdf2df()

if a registered entry already exists and radis.config["ALLOW_OVERWRITE"] is True: - if any situation arises where the databank needs to be re-downloaded, the possible urls are attempted in their usual order of preference, as if the databank hadn’t been registered, rather than directly re-downloading from the same url that was previously registered, in case e.g. a new linelist has been uploaded since the databank was previously registered - If no partition function file is registered, e.g because one wasn’t available server-side when the databank was last registered, an attempt is still made again to download it, to account for e.g. the case where one has since been uploaded

See also

fetch_hitemp(), fetch_exomol(), fetch_geisa(), fetch_kurucz(), hdf2df(), fetch_databank()