radis.api.hitranapi module

Summary

HITRAN database parser

Routine Listing

class HITRANDatabaseManager(name, molecule, local_databases, engine='default', extra_params=None, verbose=True, parallel=True)[source]

Bases: DatabaseManager

download_and_parse(local_file, cache=True, parse_quanta=True, add_HITRAN_uncertainty_code=False)[source]

Download from HITRAN and parse into local_file. Also add metadata

Overwrites radis.api.dbmanager.DatabaseManager.download_and_parse() which downloads from a list of URL, because here we use [HAPI] to download the files.

Parameters:

  • opener (an opener with an .open() command)

  • gfile (file handler. Filename: for info)

get_filenames()[source]

Get names of all files in the database (even if not downloaded yet)

Parameters:

return_reg_urls ((boolean)) – When the database is registered, whether to return the registered urls (True) or None (False)

See also

get_files_to_download()

register(download_files)[source]

register in ~/radis.json

cast_all_to_int64(df, keys)[source]

converts string to int64

cast_to_int64_with_missing_values(dg, keys, dataframe_type='pandas')[source]

replace missing values of int64 columns with -1

columns_2004 = {'A': ('a10', <class 'float'>, 'Einstein A coefficient', 's-1'), 'El': ('a10', <class 'float'>, 'lower-state energy', 'cm-1'), 'Pshft': ('a8', <class 'float'>, 'air pressure-induced line shift at 296K', 'cm-1.atm-1'), 'Tdpair': ('a4', <class 'float'>, 'temperature-dependance exponent for Gamma air', ''), 'airbrd': ('a5', <class 'float'>, 'air-broadened half-width at 296K', 'cm-1.atm-1'), 'globl': ('a15', <class 'str'>, 'electronic and vibrational global lower quanta', ''), 'globu': ('a15', <class 'str'>, 'electronic and vibrational global upper quanta', ''), 'gp': ('a7', <class 'float'>, 'upper state degeneracy', ''), 'gpp': ('a7', <class 'float'>, 'lower state degeneracy', ''), 'id': ('a2', <class 'int'>, 'Molecular number', ''), 'ierr': ('a6', <class 'str'>, 'ordered list of indices corresponding to uncertainty estimates of transition parameters', ''), 'int': ('a10', <class 'float'>, 'intensity at 296K', 'cm-1/(molecule/cm-2)'), 'iref': ('a12', <class 'str'>, 'ordered list of reference identifiers for transition parameters', ''), 'iso': ('a1', <class 'int'>, 'isotope number', ''), 'lmix': ('a1', <class 'str'>, 'flag indicating the presence of additional data and code relating to line-mixing', ''), 'locl': ('a15', <class 'str'>, 'electronic and vibrational local lower quanta', ''), 'locu': ('a15', <class 'str'>, 'electronic and vibrational local upper quanta', ''), 'selbrd': ('a5', <class 'float'>, 'self-broadened half-width at 296K', 'cm-1.atm-1'), 'wav': ('a12', <class 'float'>, 'vacuum wavenumber', 'cm-1')}[source]

parsing order of HITRAN 2004 format

Type:

OrderedDict

extract_columns(df, extracted_values, columns)[source]

extracts column from extracted_values

hit2df(fname, cache=True, verbose=True, drop_non_numeric=True, load_wavenum_min=None, load_wavenum_max=None, engine='pytables', output='pandas', parse_quanta=True, cache_directory_path=None, fast_parsing=True)[source]

Convert a HITRAN/HITEMP [1]_ file to a Pandas dataframe

Parameters:

  • fname (str) – HITRAN-HITEMP file name

  • cache (boolean, or 'regen' or 'force') – if True, a pandas-readable HDF5 file is generated on first access, and later used. This saves on the datatype cast and conversion and improves performances a lot (but changes in the database are not taken into account). If False, no database is used. If 'regen', temp file are reconstructed. Default True.

Other Parameters:

  • drop_non_numeric (boolean) – if True, non numeric columns are dropped. This improves performances, but make sure all the columns you need are converted to numeric formats before hand. Default True. Note that if a cache file is loaded it will be left untouched.

  • load_wavenum_min, load_wavenum_max (float) – if not 'None', only load the cached file if it contains data for wavenumbers above/below the specified value. See :py:func`~radis.api.cache_files.load_h5_cache_file`. Default 'None'.

  • engine (‘pytables’, ‘vaex’) – format for Hdf5 cache file. Default pytables

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

  • fast_parsing (bool) – if True, uses vectorized parsing instead of regex for global quanta. Default True.

  • output (str) – output format of data as pandas Dataformat or vaex Dataformat

  • cache_directory_path (str or None, optional) – Directory to store/read cache files. If None, use the directory of fname.

Returns:

df – dataframe containing all lines and parameters

Return type:

pandas Dataframe or Vaex Dataframe

References

Notes

Performances: see CDSD-HITEMP parser

See also

cdsd2df()

hitranxsc(hitranXSC)[source]

Parse Hitran Cross-section files manually downloaded from https://hitran.org/xsc/ Returns a dictionary

Example

Read and plot a local acetone cross-section file:

datafile = ‘CH3COCH3_233.4_375.2_700.0-1780.0_13.xsc’

data = hitran_crosssection(datafile)

# %% Plot cross section: import matplotlib.pyplot as plt plt.plot(data[‘wavenumber’], data[‘spectrum’]) plt.xlabel(‘Wavenumber (cm-1)’) plt.ylabel(‘Cross section (cm2/molecule)’) # add title with molecule name, pressure and temperature: plt.title(data[‘name’] + ‘ at ‘ + str(data[‘P’]) + ‘ Torr and ‘ + str(data[‘T’]) + ‘ K’) plt.show()

Notes

Code adapted from https://fr.mathworks.com/matlabcentral/fileexchange/74716-load-hitran-absorption-cross-section by Mohammadamir Ghaderi

Under licence conditions

Copyright (c) 2020, Mohammadamir Ghaderi
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parse_global_quanta(df, mol, verbose=True, dataframe_type='pandas', fast_parsing=True)[source]
Parameters:

  • df (pandas Dataframe)

  • mol (str) – molecule name

parse_local_quanta(df, mol, verbose=True, dataframe_type='pandas', fast_parsing=True)[source]
Parameters:

  • df (pandas Dataframe)

  • mol (str) – molecule name

post_process_hitran_data(df, molecule, verbose=True, drop_non_numeric=True, parse_quanta=True, add_HITRAN_uncertainty_code=False, dataframe_type='pandas', fast_parsing=True)[source]

Parsing non-equilibrium parameters in HITRAN/HITEMP [1]_ file to and return final Pandas Dataframe

Parameters:

  • df (pandas Dataframe) – dataframe containing generic parameters

  • molecule (str) – molecule name

Other Parameters:

  • drop_non_numeric (boolean) – if True, non numeric columns are dropped. This improves performances, but make sure all the columns you need are converted to numeric formats before hand. Default True. Note that if a cache file is loaded it will be left untouched.

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

  • add_HITRAN_uncertainty_code (bool) – if True, a column which contains HITRAN uncertainty code is converted to integer and not dropped.

  • dataframe_type (str) – pandas or vaex

  • fast_parsing (bool) – if True, uses vectorized parsing instead of regex for global quanta. Default True.

Returns:

df – dataframe containing all lines and parameters

Return type:

pandas Dataframe or vaex Dataframe

References

Notes

Performances: see CDSD-HITEMP parser

See also

cdsd2df()