complete refactor

costs/README.md

@@ -1,3 +1,4 @@
-# costs_workflow
+# Cerc costs 
 
-This workflow is a test to check that the process of calculating costs is correct before creating the API.
+Uses the cerc-hub as a base for cost calculation, it's intended to be used after executing the complete monthly energy
+balance workflow called building by building

costs/__main__.py

@@ -4,4 +4,3 @@ SPDX - License - Identifier: LGPL - 3.0 - or -later
 Copyright © 2022 Project Author Pilar Monsalvete Alvarez de Uribarri pilar.monsalvete@concordia.ca
 Code contributor Oriol Gavalda Torrellas oriol.gavalda@concordia.ca
 """
-

costs/capital_costs.py

@@ -9,32 +9,17 @@ from hub.city_model_structure.building import Building
 import hub.helpers.constants as cte
 from configuration import Configuration
 from costs import SKIN_RETROFIT, SKIN_RETROFIT_AND_SYSTEM_RETROFIT_AND_PV, SYSTEM_RETROFIT_AND_PV
+from costs.cost_base import CostBase
 
 
-class CapitalCosts:
+class CapitalCosts(CostBase):
   """
   Capital costs class
   """
   def __init__(self, building: Building, configuration: Configuration):
-    self._building = building
-    self._configuration = configuration
-    self._total_floor_area = 0
-    for internal_zone in building.internal_zones:
-      for thermal_zone in internal_zone.thermal_zones:
-        self._total_floor_area += thermal_zone.total_floor_area
-    self._archetype = None
-    for archetype in self._configuration.cost_catalog.entries('archetypes').archetype:
-      if str(building.function) == str(archetype.function):
-        self._archetype = archetype
-        self._capital_costs_chapter = self._archetype.capital_cost
-        break
-    if not self._archetype:
-      raise KeyError('archetype not found')
-
-    self._capital_costs_chapter = None
-    rng = range(configuration.number_of_years)
+    super().__init__(building, configuration)
     self._yearly_capital_costs = pd.DataFrame(
-      index=rng,
+      index=self._rng,
       columns=[
         'B2010_opaque_walls',
         'B2020_transparent',
@@ -60,7 +45,7 @@ class CapitalCosts:
     self._yearly_capital_costs.loc[0, 'D5020_lighting_and_branch_wiring'] = 0
 
     self._yearly_capital_incomes = pd.DataFrame(
-      index=rng,
+      index=self._rng,
       columns=[
         'Subsidies construction',
         'Subsidies HVAC',
@@ -111,7 +96,7 @@ class CapitalCosts:
       surface_pv += roof.solid_polygon.area * roof.solar_collectors_area_reduction_factor
 
     self._yearly_capital_costs.fillna(0, inplace=True)
-    own_capital = (1 - self._configuration.percentage_credit)
+    own_capital = 1 - self._configuration.percentage_credit
     if self._configuration.retrofit_scenario in (SKIN_RETROFIT, SKIN_RETROFIT_AND_SYSTEM_RETROFIT_AND_PV):
       chapter = self._capital_costs_chapter.chapter('B_shell')
       capital_cost_opaque = surface_opaque * chapter.item('B2010_opaque_walls').refurbishment[0]

costs/configuration.py

@@ -203,8 +203,14 @@ class Configuration:
 
   @property
   def retrofit_scenario(self):
+    """
+    Get retrofit scenario
+    """
     return self._retrofit_scenario
 
   @property
   def fuel_type(self):
+    """
+    Get fuel type (0: Electricity, 1: Gas)
+    """
     return self._fuel_type

costs/cost.py

@@ -46,6 +46,20 @@ class Cost:
                                         retrofit_scenario,
                                         fuel_type)
 
+  @property
+  def building(self) -> Building:
+    """
+    Get current building.
+    """
+    return self._building
+
+  @building.setter
+  def building(self, value: Building):
+    """
+    Set current building.
+    """
+    self._building = value
+
   def _npv_from_list(self, list_cashflow):
     return npf.npv(self._configuration.discount_rate, list_cashflow)
 

costs/cost_base.py

@@ -0,0 +1,37 @@
+"""
+Cost base module
+"""
+
+from hub.city_model_structure.building import Building
+
+from configuration import Configuration
+
+
+class CostBase:
+  """
+  Abstract base class for the costs
+  """
+  def __init__(self, building: Building, configuration: Configuration):
+    self._building = building
+    self._configuration = configuration
+    self._total_floor_area = 0
+    for internal_zone in building.internal_zones:
+      for thermal_zone in internal_zone.thermal_zones:
+        self._total_floor_area += thermal_zone.total_floor_area
+    self._archetype = None
+    for archetype in self._configuration.cost_catalog.entries('archetypes').archetype:
+      if str(building.function) == str(archetype.function):
+        self._archetype = archetype
+        self._capital_costs_chapter = self._archetype.capital_cost
+        break
+    if not self._archetype:
+      raise KeyError('archetype not found')
+
+    self._capital_costs_chapter = None
+    self._rng = range(configuration.number_of_years)
+
+  def calculate(self):
+    """
+    Raises not implemented exception
+    """
+    raise NotImplementedError()

costs/end_of_life_costs.py

@@ -6,30 +6,16 @@ import pandas as pd
 from hub.city_model_structure.building import Building
 
 from configuration import Configuration
+from costs.cost_base import CostBase
 
 
-class EndOfLifeCosts:
+class EndOfLifeCosts(CostBase):
   """
   End of life costs class
   """
   def __init__(self, building: Building, configuration: Configuration):
-    self._building = building
-    self._configuration = configuration
-    self._total_floor_area = 0
-    for internal_zone in building.internal_zones:
-      for thermal_zone in internal_zone.thermal_zones:
-        self._total_floor_area += thermal_zone.total_floor_area
-    self._archetype = None
-    for archetype in self._configuration.cost_catalog.entries('archetypes').archetype:
-      if str(building.function) == str(archetype.function):
-        self._archetype = archetype
-        self._capital_costs_chapter = self._archetype.capital_cost
-        break
-    if not self._archetype:
-      raise KeyError('archetype not found')
-
-    rng = range(configuration.number_of_years)
-    self._yearly_end_of_life_costs = pd.DataFrame(index=rng, columns=['End_of_life_costs'], dtype='float')
+    super().__init__(building, configuration)
+    self._yearly_end_of_life_costs = pd.DataFrame(index=self._rng, columns=['End_of_life_costs'], dtype='float')
 
   def calculate(self):
     """

costs/total_maintenance_costs.py

@@ -7,31 +7,17 @@ from hub.city_model_structure.building import Building
 import hub.helpers.constants as cte
 
 from configuration import Configuration
+from costs.cost_base import CostBase
 
 
-class TotalMaintenanceCosts:
+class TotalMaintenanceCosts(CostBase):
   """
   Total maintenance costs class
   """
   def __init__(self, building: Building, configuration: Configuration):
-    self._building = building
-    self._configuration = configuration
-    self._total_floor_area = 0
-    for internal_zone in building.internal_zones:
-      for thermal_zone in internal_zone.thermal_zones:
-        self._total_floor_area += thermal_zone.total_floor_area
-    self._archetype = None
-    for archetype in self._configuration.cost_catalog.entries('archetypes').archetype:
-      if str(building.function) == str(archetype.function):
-        self._archetype = archetype
-        self._capital_costs_chapter = self._archetype.capital_cost
-        break
-    if not self._archetype:
-      raise KeyError('archetype not found')
-
-    rng = range(configuration.number_of_years)
+    super().__init__(building, configuration)
     self._yearly_maintenance_costs = pd.DataFrame(
-      index=rng,
+      index=self._rng,
       columns=[
         'Heating_maintenance',
         'Cooling_maintenance',

costs/total_operational_costs.py

@@ -8,31 +8,17 @@ from hub.city_model_structure.building import Building
 import hub.helpers.constants as cte
 
 from configuration import Configuration
+from costs.cost_base import CostBase
 
 
-class TotalOperationalCosts:
+class TotalOperationalCosts(CostBase):
   """
   End of life costs class
   """
   def __init__(self, building: Building, configuration: Configuration):
-    self._building = building
-    self._configuration = configuration
-    self._total_floor_area = 0
-    for internal_zone in building.internal_zones:
-      for thermal_zone in internal_zone.thermal_zones:
-        self._total_floor_area += thermal_zone.total_floor_area
-    self._archetype = None
-    for archetype in self._configuration.cost_catalog.entries('archetypes').archetype:
-      if str(building.function) == str(archetype.function):
-        self._archetype = archetype
-        self._capital_costs_chapter = self._archetype.capital_cost
-        break
-    if not self._archetype:
-      raise KeyError('archetype not found')
-
-    rng = range(configuration.number_of_years)
+    super().__init__(building, configuration)
     self._yearly_operational_costs = pd.DataFrame(
-      index=rng,
+      index=self._rng,
       columns=[
         'Fixed_costs_electricity_peak',
         'Fixed_costs_electricity_monthly',

costs/total_operational_incomes.py

@@ -7,30 +7,16 @@ from hub.city_model_structure.building import Building
 import hub.helpers.constants as cte
 
 from configuration import Configuration
+from costs.cost_base import CostBase
 
 
-class TotalOperationalIncomes:
+class TotalOperationalIncomes(CostBase):
   """
   Total operational incomes class
   """
   def __init__(self, building: Building, configuration: Configuration):
-    self._building = building
-    self._configuration = configuration
-    self._total_floor_area = 0
-    for internal_zone in building.internal_zones:
-      for thermal_zone in internal_zone.thermal_zones:
-        self._total_floor_area += thermal_zone.total_floor_area
-    self._archetype = None
-    for archetype in self._configuration.cost_catalog.entries('archetypes').archetype:
-      if str(building.function) == str(archetype.function):
-        self._archetype = archetype
-        self._capital_costs_chapter = self._archetype.capital_cost
-        break
-    if not self._archetype:
-      raise KeyError('archetype not found')
-
-    rng = range(configuration.number_of_years)
-    self._yearly_operational_incomes = pd.DataFrame(index=rng, columns=['Incomes electricity'], dtype='float')
+    super().__init__(building, configuration)
+    self._yearly_operational_incomes = pd.DataFrame(index=self._rng, columns=['Incomes electricity'], dtype='float')
 
   def calculate(self) -> pd.DataFrame:
     """