small changes to fit weather_factory idea

city_model_structure/building.py

@@ -4,6 +4,7 @@ SPDX - License - Identifier: LGPL - 3.0 - or -later
 Copyright © 2020 Project Author Guille Gutierrez guillermo.gutierrezmorote@concordia.ca
 contributors: Pilar Monsalvete pilar_monsalvete@yahoo.es
 """
+
 from typing import List
 
 import matplotlib.patches as patches
@@ -322,7 +323,7 @@ class Building(CityObject):
   def external_temperature(self, value):
     """
     external temperature surrounding the building in grads Celsius
-    :param value: dict{DataFrame(external temperature)}
+    :param value: dict{DataFrame(float)}
     """
     self._external_temperature = value
 
@@ -338,7 +339,7 @@ class Building(CityObject):
   def global_horizontal(self, value):
     """
     global horizontal radiation surrounding the building in W/m2
-    :param value: dict{DataFrame(global horizontal radiation)}
+    :param value: dict{DataFrame(float)}
     """
     self._global_horizontal = value
 
@@ -354,7 +355,7 @@ class Building(CityObject):
   def diffuse(self, value):
     """
     diffuse radiation surrounding the building in W/m2
-    :param value: dict{DataFrame(diffuse radiation)}
+    :param value: dict{DataFrame(float)}
     """
     self._diffuse = value
 
@@ -370,6 +371,6 @@ class Building(CityObject):
   def beam(self, value):
     """
     beam radiation surrounding the building in W/m2
-    :param value: dict{DataFrame(beam radiation)}
+    :param value: dict{DataFrame(float)}
     """
     self._beam = value

factories/weather_feeders/helpers/weather.py

@@ -10,10 +10,9 @@ class Weather(object):
     # Swinbank - Fuentes sky model approximation(1963) based on cloudiness statistics(32 %) in United States
     # ambient temperatures( in °C)
     # sky temperatures( in °C)
-    _ambient_temperature = ambient_temperature[['temperature']].to_numpy()
     values = []
-    for temperature in _ambient_temperature:
+    for temperature in ambient_temperature:
       value = 0.037536 * math.pow((temperature + cte.celsius_to_kelvin), 1.5) \
               + 0.32 * (temperature + cte.celsius_to_kelvin) - cte.celsius_to_kelvin
       values.append(value)
-    return pd.DataFrame(values, columns=['sky temperature'])
+    return values