finished test_weather_factory.py

city_model_structure/building.py

@@ -47,15 +47,10 @@ class Building(CityObject):
     self._m_cooling = pd.DataFrame()
     self._h_cooling = pd.DataFrame()
     self._cooling = pd.DataFrame()
-    self._m_external_temperature = pd.DataFrame()
-    self._h_external_temperature = pd.DataFrame()
-    self._external_temperature = pd.DataFrame()
-    self._h_global_horizontal = pd.DataFrame()
-    self._global_horizontal = pd.DataFrame()
-    self._h_diffuse = pd.DataFrame()
-    self._diffuse = pd.DataFrame()
-    self._h_beam = pd.DataFrame()
-    self._beam = pd.DataFrame()
+    self._external_temperature = dict()
+    self._global_horizontal = dict()
+    self._diffuse = dict()
+    self._beam = dict()
 
     # ToDo: Check this for LOD4
     self._thermal_zones = []
@@ -392,147 +387,65 @@ class Building(CityObject):
     return self._cooling
 
   @property
-  def _monthly_external_temperature(self) -> pd.DataFrame:
+  def external_temperature(self) -> dict:
     """
-    external temperature surrounding the building in grads Celsius monthly based
-    :return: DataFrame with 12 values and a header with the source of those
+    external temperature surrounding the building in grads Celsius
+    :return: dict{DataFrame(float)}
     """
-    return self._m_external_temperature
-
-  @_monthly_external_temperature.setter
-  def _monthly_external_temperature(self, value):
-    """
-    external temperature surrounding the building in grads Celsius monthly based
-    :param value: DataFrame(external temperature)
-    """
-    if self._m_external_temperature.empty:
-      self._m_external_temperature = value
-    else:
-      self._m_external_temperature = pd.concat([self._m_external_temperature, value], axis=1)
-
-  @property
-  def _hourly_external_temperature(self) -> pd.DataFrame:
-    """
-    external temperature surrounding the building in grads Celsius hourly based
-    :return: DataFrame with 8760 values and a header with the source of those
-    """
-    return self._h_external_temperature
-
-  @_hourly_external_temperature.setter
-  def _hourly_external_temperature(self, value):
-    """
-    external temperature surrounding the building in grads Celsius hourly based
-    :param value: DataFrame(external temperature)
-    """
-    if self._h_external_temperature.empty:
-      self._h_external_temperature = value
-    else:
-      self._h_external_temperature = pd.concat([self._h_external_temperature, value], axis=1)
-
-  def external_temperature(self, time_scale) -> pd.DataFrame:
-    """
-    Get external temperature surrounding the building in grads Celsius in a defined time_scale
-    :param time_scale: string.
-    :return: DataFrame(float)
-    """
-    if time_scale == cte.time_scale['hour']:
-      self._external_temperature = self._hourly_external_temperature
-    elif time_scale == cte.time_scale['month']:
-      self._external_temperature = self._monthly_external_temperature
-    else:
-      raise NotImplementedError
     return self._external_temperature
 
+  @external_temperature.setter
+  def external_temperature(self, value):
+    """
+    external temperature surrounding the building in grads Celsius
+    :param value: dict{DataFrame(external temperature)}
+    """
+    self._external_temperature = value
+
   @property
-  def _hourly_global_horizontal(self) -> pd.DataFrame:
+  def global_horizontal(self) -> dict:
     """
-    global horizontal radiation surrounding the building in W/m2 hourly based
-    :return: DataFrame with 8760 values and a header with the source of those
+    global horizontal radiation surrounding the building in W/m2
+    :return: dict{DataFrame(float)}
     """
-    return self._h_global_horizontal
-
-  @_hourly_global_horizontal.setter
-  def _hourly_global_horizontal(self, value):
-    """
-    global horizontal radiation surrounding the building in W/m2 hourly based
-    :param value: DataFrame(external temperature)
-    """
-    if self._h_global_horizontal.empty:
-      self._h_global_horizontal = value
-    else:
-      self._h_global_horizontal = pd.concat([self._h_global_horizontal, value], axis=1)
-
-  def global_horizontal(self, time_scale) -> pd.DataFrame:
-    """
-    Get global horizontal radiation surrounding the building in W/m2 in a defined time_scale
-    :param time_scale: string.
-    :return: DataFrame(float)
-    """
-    if time_scale == cte.time_scale['hour']:
-      self._global_horizontal = self._hourly_global_horizontal
-    else:
-      raise NotImplementedError
     return self._global_horizontal
 
+  @global_horizontal.setter
+  def global_horizontal(self, value):
+    """
+    global horizontal radiation surrounding the building in W/m2
+    :param value: dict{DataFrame(global horizontal radiation)}
+    """
+    self._global_horizontal = value
+
   @property
-  def _hourly_diffuse(self) -> pd.DataFrame:
+  def diffuse(self) -> dict:
     """
-    diffuse radiation surrounding the building in W/m2 hourly based
-    :return: DataFrame with 8760 values and a header with the source of those
+    diffuse radiation surrounding the building in W/m2
+    :return: dict{DataFrame(float)}
     """
-    return self._h_diffuse
-
-  @_hourly_diffuse.setter
-  def _hourly_diffuse(self, value):
-    """
-    diffuse radiation surrounding the building in W/m2 hourly based
-    :param value: DataFrame(external temperature)
-    """
-    if self._h_diffuse.empty:
-      self._h_diffuse = value
-    else:
-      self._h_diffuse = pd.concat([self._h_diffuse, value], axis=1)
-
-  def diffuse(self, time_scale) -> pd.DataFrame:
-    """
-    Get diffuse radiation surrounding the building in W/m2 in a defined time_scale
-    :param time_scale: string.
-    :return: DataFrame(float)
-    """
-    if time_scale == cte.time_scale['hour']:
-      self._diffuse = self._hourly_diffuse
-    else:
-      raise NotImplementedError
     return self._diffuse
 
+  @diffuse.setter
+  def diffuse(self, value):
+    """
+    diffuse radiation surrounding the building in W/m2
+    :param value: dict{DataFrame(diffuse radiation)}
+    """
+    self._diffuse = value
+
   @property
-  def _hourly_beam(self) -> pd.DataFrame:
+  def beam(self) -> dict:
     """
-    beam radiation surrounding the building in W/m2 hourly based
-    :return: DataFrame with 8760 values and a header with the source of those
+    beam radiation surrounding the building in W/m2
+    :return: dict{DataFrame(float)}
     """
-    return self._h_beam
-
-  @_hourly_beam.setter
-  def _hourly_beam(self, value):
-    """
-    beam radiation surrounding the building in W/m2 hourly based
-    :param value: DataFrame(external temperature)
-    """
-    if self._h_beam.empty:
-      self._h_beam = value
-    else:
-      self._h_beam = pd.concat([self._h_beam, value], axis=1)
-
-  def beam(self, time_scale) -> pd.DataFrame:
-    """
-    Get beam radiation surrounding the building in W/m2 in a defined time_scale
-    :param time_scale: string.
-    :return: DataFrame(float)
-    """
-    if time_scale == cte.time_scale['hour']:
-      self._beam = self._hourly_beam
-    else:
-      raise NotImplementedError
     return self._beam
 
+  @beam.setter
+  def beam(self, value):
+    """
+    beam radiation surrounding the building in W/m2
+    :param value: dict{DataFrame(beam radiation)}
+    """
+    self._beam = value

factories/weather_feeders/dat_weather_parameters.py

@@ -24,8 +24,26 @@ class DatWeatherParameters:
       self._weather_values = pd.read_csv(self._path, sep='\s+', header=None,
                                          names=['hour', 'global_horiz', 'temperature', 'diffuse', 'beam', 'empty'])
     for building in self._city.buildings:
-      building._hourly_external_temperature = pd.DataFrame(self._weather_values[['temperature']].to_numpy(), columns=['inseldb'])
-      building._hourly_global_horizontal = pd.DataFrame(self._weather_values[['global_horiz']].to_numpy(), columns=['inseldb'])
-      building._hourly_diffuse = pd.DataFrame(self._weather_values[['diffuse']].to_numpy(), columns=['inseldb'])
-      building._hourly_beam = pd.DataFrame(self._weather_values[['beam']].to_numpy(), columns=['inseldb'])
+      new_value = pd.DataFrame(self._weather_values[['temperature']].to_numpy(), columns=['inseldb'])
+      if 'hour' not in building.external_temperature:
+        building.external_temperature['hour'] = new_value
+      else:
+        pd.concat([building.external_temperature['hour'], new_value], axis=1)
 
+      new_value = pd.DataFrame(self._weather_values[['global_horiz']].to_numpy(), columns=['inseldb'])
+      if 'hour' not in building.global_horizontal:
+        building.global_horizontal['hour'] = new_value
+      else:
+        pd.concat([building.global_horizontal['hour'], new_value], axis=1)
+
+      new_value = pd.DataFrame(self._weather_values[['diffuse']].to_numpy(), columns=['inseldb'])
+      if 'hour' not in building.diffuse:
+        building.diffuse['hour'] = new_value
+      else:
+        pd.concat([building.diffuse['hour'], new_value], axis=1)
+
+      new_value = pd.DataFrame(self._weather_values[['beam']].to_numpy(), columns=['inseldb'])
+      if 'hour' not in building.beam:
+        building.beam['hour'] = new_value
+      else:
+        pd.concat([building.beam['hour'], new_value], axis=1)

tests/test_weather_factory.py

@@ -5,6 +5,7 @@ Copyright © 2020 Project Author Pilar Monsalvete pilar_monsalvete@yahoo.es
 """
 from pathlib import Path
 from unittest import TestCase
+import numpy as np
 
 from factories.geometry_factory import GeometryFactory
 from factories.weather_factory import WeatherFactory
@@ -43,15 +44,11 @@ class TestWeatherFactory(TestCase):
     """
     city = self._get_city_with_weather()
     for building in city.buildings:
-      values = building.external_temperature('hour')[['inseldb']].to_numpy()
-      print(values[8])
-      self.assertEqual(values[8], [-1.4109149], 'wrong value external_temperature')
-      values = building.diffuse('hour')[['inseldb']].to_numpy()
-      print(values[8])
-      self.assertEqual(values[8], [40.0263214], 'wrong value diffuse')
-      values = building.beam('hour')[['inseldb']].to_numpy()
-      print(values[8])
-      self.assertEqual(values[8], [402.954041], 'wrong value beam')
-      values = building.global_horizontal('hour')[['inseldb']].to_numpy()
-      print(values[8])
-      self.assertEqual(values[8], [79.9888763], 'wrong value global horizontal')
+      values = building.external_temperature['hour'][['inseldb']].to_numpy()
+      self.assertEqual([-1.41], np.around(values[8], decimals=2), 'wrong value external_temperature')
+      values = building.global_horizontal['hour'][['inseldb']].to_numpy()
+      self.assertEqual([79.99],  np.around(values[8], decimals=2), 'wrong value global horizontal')
+      values = building.diffuse['hour'][['inseldb']].to_numpy()
+      self.assertEqual([40.03],  np.around(values[8], decimals=2), 'wrong value diffuse')
+      values = building.beam['hour'][['inseldb']].to_numpy()
+      self.assertEqual([402.95],  np.around(values[8], decimals=2), 'wrong value beam')