X-Git-Url: https://bilbo.iut-bm.univ-fcomte.fr/and/gitweb/predictops.git/blobdiff_plain/d6469a787c80df2c938f21d4ae107b84213e238f..90e69cb2125d4bae76a27b9c38defb4f70bf2ca6:/predictops/source/meteofrance.py

diff --git a/predictops/source/meteofrance.py b/predictops/source/meteofrance.py
index 5a885ee..0edd49f 100644
--- a/predictops/source/meteofrance.py
+++ b/predictops/source/meteofrance.py
@@ -16,51 +16,89 @@ import gzip
 fileConfig((Path.cwd() / 'config') / 'logging.cfg')
 logger = getLogger()
 
+
 class MeteoFrance:
 
-    def __init__(self, latitude = 47.25, longitude = 6.0333, nb_stations = 3,
-                 start = datetime.strptime('19960101000000', '%Y%m%d%H%M%S'),
-                 end = datetime.now(),
-                 features = []):
+    _latitude    = None
+    _longitude   = None
+    _nb_stations = None
+    _start       = None
+    _end         = None
+    _features    = 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:
-            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.
-            features (list): Weather features that have to be integrated, according
-                  to their names in meteofrance_features.csv (cf. config directory)
-
         '''
-        self._latitude = latitude
-        self._longitude = longitude
-        self._nb_stations = nb_stations
-        self._start = start
-        self._end = end
-        self._features = features
+        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
 
         # Re-creating data directory architecture for MeteoFrance, if asked
-        config = ConfigParser()
-        config.read((Path.cwd() / 'config') / 'features.cfg')
-        if eval(config['meteofrance']['regenerate']):
+        if self._config['GENERAL'].getboolean('regenerate'):
             self._regenerate_directory()
 
         # Collecting the closest meteo station
+        self._nb_stations = self._config['STATIONS'].getint('nb_stations')
         self._stations = self._get_stations()
 
+        # Collecting meteofrance features
+        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
+    def start(self):
+        return self._start
+
+    @start.setter
+    def start(self, x):
+        self._start = x
+
+
+    @property
+    def end(self):
+        return self._end
+
+    @end.setter
+    def end(self, x):
+        self._end = x
+
+
+    @property
+    def latitude(self):
+        return self._latitude
+
+    @latitude.setter
+    def latitude(self, x):
+        self._latitude = x
+
+
+    @property
+    def longitude(self):
+        return self._longitude
+
+    @longitude.setter
+    def longitude(self, x):
+        self._longitude = x
+
+
+    @property
+    def nb_stations(self):
+        return self._nb_stations
+
+    @nb_stations.setter
+    def nb_stations(self, x):
+        self._nb_stations = x
 
 
     def _regenerate_directory(self):
@@ -193,25 +231,23 @@ class MeteoFrance:
             dict: the dictionary of features per datestamp
         '''
         if self._dated_features == None:
-            csv_file = Path.cwd() / 'config' / 'features' / 'meteofrance_features.csv'
-            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}
+            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: