logoutput improved

pvpower/forecast.py

@@ -4,7 +4,7 @@
 from pvpower.weather_forecast import WeatherStation, WeatherForecast
 from pvpower.traindata import LabelledWeatherForecast, TrainSampleLog
 from pvpower.estimator import Estimator
-from pvpower.persistent_estimator import PersistentEstimator
+from pvpower.refreshing_estimator import AutoRefreshingEstimator
 
 
 class ValueRecorder:
@@ -42,7 +42,7 @@ def __init__(self, station_id: str, pv_forecast_dir: None, estimator: Estimator
         self.__train_value_recorder = ValueRecorder()
         self.weather_forecast_service = WeatherStation(station_id)
         self.train_log = TrainSampleLog(pv_forecast_dir)
-        self.__estimator = estimator if estimator is not None else PersistentEstimator(self.train_log)
+        self.__estimator = estimator if estimator is not None else AutoRefreshingEstimator(self.train_log)
 
     def add_current_power_reading(self, real_power: int):
         if self.__train_value_recorder.is_expired():

pvpower/persistent_estimator.py → pvpower/refreshing_estimator.py

@@ -11,18 +11,18 @@
 from pvpower.trainingcenter import TrainingCenter
 
 
-class PersistentEstimator(DelegatingEstimator):
+class AutoRefreshingEstimator(DelegatingEstimator):
 
     def __init__(self, train_log: TrainSampleLog):
         self.__train_log = train_log
         self.__lock = Lock()
         self.__training_center = TrainingCenter()
         self.__date_last_retrain_initiated = datetime.fromtimestamp(0)
-        super(PersistentEstimator, self).__init__(PersistentEstimator.__load())
+        super().__init__(AutoRefreshingEstimator.__load())
 
     def predict(self, sample: WeatherForecast) -> int:
         try:
-            return super(PersistentEstimator, self).predict(sample)
+            return super().predict(sample)
         finally:
             try:
                 retrain_period_days = 1 + (self.duration_sec_last_train() * 7 * 24)  # min 1 day + 7 days per 1 sec traintime
@@ -41,19 +41,19 @@ def retrain(self, train_data: TrainData):
     @staticmethod
     def __store(estimator: Estimator):
         try:
-            with open(PersistentEstimator.__filename(), 'wb') as file:
+            with open(AutoRefreshingEstimator.__filename(), 'wb') as file:
                 pickle.dump(estimator, file)
         except Exception as e:
             logging.warning("error occurred storing pickled estimator " + str(e))
 
     @staticmethod
     def __load() -> Estimator:
         estimator = SVMEstimator(FullVectorizer())
-        if exists(PersistentEstimator.__filename()):
+        if exists(AutoRefreshingEstimator.__filename()):
             try:
-                with open(PersistentEstimator.__filename(), 'rb') as file:
+                with open(AutoRefreshingEstimator.__filename(), 'rb') as file:
                     estimator = pickle.load(file)
-                    logging.debug("estimator " + str(estimator) + " loaded from pickle file (" + PersistentEstimator.__filename() + ")")
+                    logging.debug("estimator " + str(estimator) + " loaded from pickle file (" + AutoRefreshingEstimator.__filename() + ")")
             except Exception as e:
                 logging.warning("error occurred loading estimator " + str(e))
         return estimator

pvpower/weather_forecast.py

@@ -35,7 +35,8 @@ def with_time(self, dt: datetime):
                                self.visibility)
 
     def __str__(self):
-        return self.time_utc.strftime("%H") + ":00-" + (self.time_utc + timedelta(hours=1)).strftime("%H") + ":00 (utc)" + \
+        return self.time.strftime("%H") + ":00-" + (self.time + timedelta(hours=1)).strftime("%H") + ":00 " + \
+               "(" + self.time_utc.strftime("%H") + ":00-" + (self.time_utc + timedelta(hours=1)).strftime("%H") + ":00 utc)" + \
                ", irradiance=" + str(round(self.irradiance)) + \
                ", sunshine=" + str(round(self.sunshine)) + \
                ", cloud_cover_effective=" + str(round(self.cloud_cover_effective)) + \