radis.io.hitran module

RADIS Hitran Functions; based on Common API hitranapi.py

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')

Compare CO spectrum from the GEISA and HITRAN database

Compare CO spectrum from the GEISA and 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()

See also

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