radis.io.geisa module

Summary

GEISA database parser

Defines fetch_geisa() based on GEISADatabaseManager

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()