-from extomeAI.source import MeteoFrance
+from predictops.source.ephemeris import Ephemeris
+from predictops.source.meteofrance import MeteoFrance
+from predictops.learn.preprocessing import Preprocessing
+from predictops.target.toarea import ToArea
-from celery import Celery
-from configparser import ConfigParser
-from logging.config import fileConfig
+from datetime import datetime, timedelta
from logging import getLogger
+from logging.config import fileConfig
from pathlib import Path
from shutil import rmtree
-from subprocess import Popen, PIPE
+import geopandas as gpd
fileConfig((Path.cwd() / 'config') / 'logging.cfg')
logger = getLogger()
-class ExtomeEngine:
- def __init__(self, clean = False):
- logger.info("Extome-IA engine launched")
- if clean:
- self.clean()
- print("Ne pas oublier d'exporter la BDD dans pgModeler")
- print("Ni de copier l'archive dans la data")
-
+class Engine:
+ def __init__(self, start = None, end = None, time_step = None):
+ self._X = {}
+ self._Y = {}
+
+
def clean(self):
# Cleaning the data directory
logger.info("Cleaning and restoring data directory")
rmtree(directory)
p = Path(Path.cwd() / 'data')
p.mkdir()
-
- # Cleaning the postgresql database
- config = ConfigParser()
- config.read((Path.cwd() / 'config') / 'main.cfg')
-
- host = config['postgresql']['host']
- user = config['postgresql']['user']
- port = config['postgresql']['port']
- dbname = config['postgresql']['dbname']
-
- logger.info("PostgreSQL database deletion")
- command = ['dropdb', '-h', host, '-U', user, '-p', port, dbname]
- process = Popen(command, stdout=PIPE, stderr=PIPE)
- process.communicate()
-
- logger.info("PostgreSQL database creation")
- command = ['createdb', '-h', host, '-U', user, '-p', port, dbname]
- process = Popen(command, stdout=PIPE, stderr=PIPE)
- process.communicate()
-
- def add_meteofrance(self):
- self.meteofrance = MeteoFrance()
-
-
-
-engine = ExtomeEngine(clean = False)
-engine.add_meteofrance()
\ No newline at end of file
+
+
+ def add_feature(self, name, **kw):
+
+ if name == 'meteofrance':
+ meteofeature = MeteoFrance(**kw)
+ meteofeature.update()
+ dated_features = meteofeature.dated_features
+ for date in dated_features:
+ self._X.setdefault(date,{}).update(dated_features[date])
+ elif name == 'ephemeris':
+ ephemerides = Ephemeris(**kw)
+ dated_features = ephemerides.dated_features
+ for date in dated_features:
+ self._X.setdefault(date,{}).update(dated_features[date])
+
+
+ @property
+ def X(self):
+ return self._X
+
+ @X.setter
+ def X(self, x):
+ self._X = x
+
+
+start = datetime.strptime('01/01/2010 01:00:00', '%m/%d/%Y %H:%M:%S')
+end = datetime.strptime('12/31/2010 23:00:00', '%m/%d/%Y %H:%M:%S')
+
+engine = Engine()
+engine.add_feature(name = 'meteofrance',
+ start = start, end = end,
+ latitude = 47.25, longitude = 6.0333, nb_stations = 3,
+ features = ['temperature', 'pressure'])
+
+
+engine.add_feature(name = 'ephemeris',
+ start = start, end = end,
+ features = ['hour', 'dayInWeek', 'dayInMonth', 'dayInYear',
+ 'weekInYear', 'month', 'year'])
+
+
+process = Preprocessing(dict_features = engine.X,
+ start = start, end = end, timestep = timedelta(hours=6))
+
+
+df = process.dataframe.head(n=20)
+#print(engine.X[datetime.strptime('06/30/2010 21:00:00', '%m/%d/%Y %H:%M:%S')])
+print(df)
+exit()
+
+depts = gpd.read_file( Path.cwd() / 'data' / 'targets' / 'departments' / "departements-20180101.shp")
+Doubs = depts.loc[depts['nom'] == 'Doubs'].iloc[0]
+
+ToArea(area=Doubs.geometry,
+ start = start, end = end,
+ csv_file = Path.cwd() / 'data' / 'targets' / 'sdis25' / 'interventions.csv')
+
