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.)
output (str) – output format of data as pandas Dataformat or vaex Dataformat
Returns:
df – dataframe containing all lines and 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.
engine (str) – pandas or vaex
Returns:
df – dataframe containing all lines and parameters