-from .source import Source
-
from configparser import ConfigParser
from csv import DictReader
from datetime import datetime
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
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)
+ self._latitude = self._config['POSITION'].getfloat('latitude')
+ self._longitude = self._config['POSITION'].getfloat('longitude')
+
self._data_directory = (Path.cwd() / 'data') / 'features' / 'meteo_france'
self._dated_features = None
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
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:
