X-Git-Url: https://bilbo.iut-bm.univ-fcomte.fr/and/gitweb/predictops.git/blobdiff_plain/288baa6ff06c1b815ec24d164770acc93ac80499..90e69cb2125d4bae76a27b9c38defb4f70bf2ca6:/predictops/source/meteofrance.py?ds=sidebyside diff --git a/predictops/source/meteofrance.py b/predictops/source/meteofrance.py index b26c6bf..0edd49f 100644 --- a/predictops/source/meteofrance.py +++ b/predictops/source/meteofrance.py @@ -1,5 +1,3 @@ -from .source import Source - from configparser import ConfigParser from csv import DictReader from datetime import datetime @@ -18,10 +16,8 @@ import gzip fileConfig((Path.cwd() / 'config') / 'logging.cfg') logger = getLogger() -CSV_FILE = Path.cwd() / 'config' / 'features' / 'meteofrance_features.csv' - -class MeteoFrance(Source): +class MeteoFrance: _latitude = None _longitude = None @@ -33,28 +29,7 @@ class MeteoFrance(Source): def __init__(self, config_file): ''' Constructor of the MeteoFrance source of feature. - - - It will reinitiate the data directory, if asked in the config - features.cfg file. - - It searches for the nb_stations meteo stations closest to the provided - point (longitude and latitude) - - For more information about this source of feature, see: - https://donneespubliques.meteofrance.fr/?fond=produit&id_produit=90&id_rubrique=32 - - Parameters: - - in config file: - latitude (float): The latitude from which we want the meteo features. - longitude (float): The longitude from which we want the meteo features. - nb_stations (int): Number of closest stations to consider. - - provided to the constructor - features (list): Weather features that have to be integrated, according - to their names in meteofrance_features.csv (cf. config directory) - ''' - # Check for the integrity of feature names - Source.__init__(self) - self._config = ConfigParser() self._config.read(config_file) @@ -74,10 +49,11 @@ class MeteoFrance(Source): self._stations = self._get_stations() # Collecting meteofrance features - with open(CSV_FILE, "r") as f: - reader = DictReader(f, delimiter=',') - self._features = [row['name'] for row in reader - if self._config['FEATURES'].getboolean(row['name'])] + self._features = [section for section in self._config + if self._config.has_option(section, 'numerical') + and (self._config[section]['numerical'] or + self._config[section]['categorical'])] + @property @@ -255,26 +231,23 @@ class MeteoFrance(Source): dict: the dictionary of features per datestamp ''' if self._dated_features == None: - logger.info(f'Collecting meteo feature information from {CSV_FILE}') + logger.info('Collecting meteofrance feature information') # A dictionary for the features - with open(CSV_FILE, "r") as f: - reader = DictReader(f, delimiter=',') - dico_features = {row["abbreviation"]: - { - 'name': row['name'], # feature name - 'type': row['type'] # qualitative (2) or quantitative (1) - } - for row in reader if row['name'] in self._features} - #print([row for row in reader]) - #print([row for row in reader if row['name'] in self._features]) + dico_features = {self._config[section]["abbreviation"]: + { + 'name': section, # feature name + 'numerical': self._config[section]['numerical'], + 'categorical': self._config[section]['categorical'] + } + for section in self._features} dir_data = Path.cwd() / 'data' / 'features' / 'meteo_france' / 'historical' self._dated_features = {} - for csv_meteo in listdir(dir_data): + for csv_meteo in sorted(listdir(dir_data)): date = datetime.strptime(csv_meteo.split('.')[1], '%Y%m') if (date >= self._start and date <= self._end)\ or (date.year == self._start.year and date.month == self._start.month)\ or (date.year == self._end.year and date.month == self._end.month): - logger.info(f'Inserting {csv_meteo} in intervention dictionary') + logger.info(f'Adding meteofrance features from {csv_meteo}') with open(dir_data / csv_meteo, "r") as f: reader = DictReader(f, delimiter=';') for row in reader: