# -*- coding: utf-8 -*- """ Summary ----------------------- GEISA database parser Defines :py:func:`~radis.io.fetch_geisa` based on :py:class:`~radis.api.geisaapi.GEISADatabaseManager` """ from os.path import abspath, exists, expanduser, join from radis import config from radis.api.geisaapi import GEISADatabaseManager from radis.api.hdf5 import DataFileManager from radis.misc.config import getDatabankEntries from radis.misc.database_progress import DatabaseProgressPrinter def 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, ): """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 :ref:`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 :ref:`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') .. minigallery:: radis.fetch_geisa 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 :py:func:`~radis.api.hdf5.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 -------- :py:func:`~radis.io.hitran.fetch_hitran`, :py:func:`~radis.io.exomol.fetch_exomol` :py:func:`~radis.io.hitemp.fetch_hitemp`, :py:func:`~radis.io.kurucz.fetch_kurucz` :py:func:`~radis.api.hdf5.hdf2df` :py:meth:`~radis.lbl.loader.DatabankLoader.fetch_databank` """ if r"{molecule}" in databank_name: databank_name = databank_name.format(**{"molecule": molecule}) if local_databases is None: local_databases = join(config["DEFAULT_DOWNLOAD_PATH"], "geisa") local_databases = abspath(expanduser(local_databases)) ldb = GEISADatabaseManager( databank_name, molecule=molecule, local_databases=local_databases, verbose=verbose, chunksize=chunksize, parallel=parallel, engine=engine, ) # Check if the database is registered in radis.json local_files, urlnames = [], [] if ldb.is_registered(): entries = getDatabankEntries(ldb.name) local_files, urlnames = entries["path"], entries["download_url"] if ldb.is_registered() and not config["ALLOW_OVERWRITE"]: error = False if cache == "regen" or not local_files: error = True files_to_check = local_files if ldb.get_missing_files(files_to_check): error = True if error: raise Exception( 'Changes are required to the local database, and hence updating the registered entry, but "ALLOW_OVERWRITE" is False. Set `radis.config["ALLOW_OVERWRITE"]=True` to allow the changes to be made and config file to be automatically updated accordingly.' ) # Delete files if needed: if cache == "regen": ldb.remove_local_files(local_files) ldb.check_deprecated_files( ldb.get_existing_files(local_files), auto_remove=True if cache != "force" else False, ) if len(local_files) > 1 or len(urlnames) > 1: raise Exception( f"Found the following files {local_files} but only 1 is expected" if len(local_files) > 1 else f"Found the following urls {urlnames} but only 1 is expected" ) # Check if local files are available so we don't have to download download_files = True if local_files and not ldb.get_missing_files(local_files): download_files = False ldb.actual_file = local_files[0] # for ldb.load below # Initialize progress printer if verbose: printer = DatabaseProgressPrinter( database_name="GEISA", molecule=molecule, verbose=verbose, version="2020", ) printer.header("Fetching database") printer.section("Download") # Download files if download_files: main_files, main_urls = ldb.get_filenames(return_reg_urls=True) for i in range(len(main_urls)): url = main_urls[i] file = main_files[i] if verbose: printer.info(f"Attempting to download {url}", indent=1) try: ldb.download_and_parse([url], [file], 1) except OSError as err: if i == len(main_urls) - 1: # all possible urls exhausted if verbose: printer.warning(f"Error downloading {url}: {err}") printer.warning(f"No source found for {ldb.molecule}") raise else: if verbose: printer.warning(f"Error downloading {url}: {err}") continue else: if verbose: printer.success(f"Successfully downloaded {url}") ldb.actual_file = file ldb.actual_url = url break # no need to search any further else: if verbose: printer.info("All files already downloaded.", indent=1) if verbose: printer.section("Caching to HDF5/H5 format") # Check if cache exists fcache = DataFileManager(engine).cache_file(ldb.actual_file) if exists(fcache): printer.info("All files already cached.", indent=1) # Register if download_files or not ldb.is_registered(): ldb.register(download_files) if download_files and clean_cache_files: ldb.clean_download_files() if isotope and type(isotope) == int: isotope = str(isotope) # Load and return df = ldb.load( [ldb.actual_file], # filter other files, columns=columns, within=[("iso", isotope)] if isotope is not None else [], # for relevant files, get only the right range : lower_bound=[("wav", load_wavenum_min)] if load_wavenum_min is not None else [], upper_bound=[("wav", load_wavenum_max)] if load_wavenum_max is not None else [], output=output, ) return (df, local_files) if return_local_path else df # %% if __name__ == "__main__": import pytest print("Testing factory:", pytest.main(["../test/io/test_geisa.py"]))