XGBoost integrated

[predictops.git] / predictops / engine.py

diff --git a/predictops/engine.py b/predictops/engine.py
index 8ba5043ebfdec4ef386aef2cf223b7cb52407d0a..f87e82e833fbd87bcc091f4dc568108a9bf86a21 100644 (file)
--- a/predictops/engine.py
+++ b/predictops/engine.py
@@ -7,6 +7,9 @@ from shutil import rmtree
 
 from .source.ephemeris import Ephemeris
 from .source.meteofrance import MeteoFrance
+from .learn.learning import Learning
+from .learn.preprocessing import Preprocessing
+from .target.target import Target
 
 fileConfig((Path.cwd() / 'config') / 'logging.cfg')
 logger = getLogger()
@@ -26,7 +29,6 @@ class Engine:
                                    self._config['DATETIME'].getfloat('hourStep'))
 
         self._X = {}
-        self._Y = {}
 
 
 
@@ -65,10 +67,37 @@ class Engine:
                 self._X.setdefault(date,{}).update(dated_features[date])
 
 
+    def add_target(self):
+        self._target = Target(config_file = eval(self._config['TARGET']['config']),
+                              start = self._start, end = self._end,
+                              timestep = self._timestep)
+
+
+    def add_preprocessing(self):
+        self._preproc = Preprocessing(config_file = self._config,
+                                      dict_features = self.X,
+                                      dict_target = self.y)
+
+
+    def learn(self):
+        history = self._config['HISTORY_KNOWLEDGE'].getint('nb_lines')
+        self._learner = Learning(config_file = eval(self._config['LEARNER']['config']),
+                                 X = self._preproc.dataframe, y = list(self.y.values())[history:])
+
+
     @property
     def X(self):
         return self._X
 
     @X.setter
     def X(self, x):
-        self._X = x
\ No newline at end of file
+        self._X = x
+
+
+    @property
+    def y(self):
+        return self._target.y
+
+    @y.setter
+    def end(self, y):
+        self._target.y = y