Cost now returns all the needed outputs and a small performance improvement done.
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@ -136,15 +136,29 @@ class Cost:
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life_cycle_operational_costs,
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life_cycle_operational_costs,
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life_cycle_maintenance_costs,
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life_cycle_maintenance_costs,
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life_cycle_operational_incomes,
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life_cycle_operational_incomes,
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life_cycle_capital_incomes
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life_cycle_capital_incomes,
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global_capital_costs,
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global_capital_incomes,
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global_end_of_life_costs,
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global_operational_costs,
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global_maintenance_costs,
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global_operational_incomes
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]
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]
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results.index = ['total_capital_costs_skin',
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results.index = [
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'total_capital_costs_systems',
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'total_capital_costs_skin',
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'end_of_life_costs',
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'total_capital_costs_systems',
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'total_operational_costs',
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'end_of_life_costs',
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'total_maintenance_costs',
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'total_operational_costs',
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'operational_incomes',
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'total_maintenance_costs',
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'capital_incomes']
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'operational_incomes',
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'capital_incomes',
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'global_capital_costs',
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'global_capital_incomes',
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'global_end_of_life_costs',
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'global_operational_costs',
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'global_maintenance_costs',
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'global_operational_incomes'
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]
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return results
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return results
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@ -39,15 +39,14 @@ class PeakLoad:
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for thermal_zone in self._building.internal_zones[0].thermal_zones:
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for thermal_zone in self._building.internal_zones[0].thermal_zones:
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lighting = thermal_zone.lighting
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lighting = thermal_zone.lighting
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for schedule in lighting.schedules:
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for schedule in lighting.schedules:
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for value in schedule.values:
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peak = max(schedule.values) * lighting.density * thermal_zone.total_floor_area
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if value * lighting.density * thermal_zone.total_floor_area > peak_lighting:
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if peak > peak_lighting:
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peak_lighting = value * lighting.density * thermal_zone.total_floor_area
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peak_lighting = peak
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appliances = thermal_zone.appliances
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appliances = thermal_zone.appliances
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for schedule in appliances.schedules:
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for schedule in appliances.schedules:
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for value in schedule.values:
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peak = max(schedule.values) * appliances.density * thermal_zone.total_floor_area
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if value * appliances.density * thermal_zone.total_floor_area > peak_appliances:
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if peak > peak_appliances:
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peak_appliances = value * appliances.density * thermal_zone.total_floor_area
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peak_appliances = peak
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monthly_electricity_peak = [0.9 * peak_lighting + 0.7 * peak_appliances] * 12
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monthly_electricity_peak = [0.9 * peak_lighting + 0.7 * peak_appliances] * 12
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conditioning_peak = []
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conditioning_peak = []
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for i, value in enumerate(self._building.heating_peak_load[cte.MONTH]):
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for i, value in enumerate(self._building.heating_peak_load[cte.MONTH]):
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@ -1,3 +1,4 @@
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import datetime
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import glob
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import glob
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import os
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import os
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import subprocess
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import subprocess
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@ -25,6 +26,7 @@ class Initialize:
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@property
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@property
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def city(self):
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def city(self):
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if self._city is None:
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if self._city is None:
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start = datetime.datetime.now()
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print('init tests')
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print('init tests')
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city_file = (Path(__file__).parent / 'data/test.geojson').resolve()
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city_file = (Path(__file__).parent / 'data/test.geojson').resolve()
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output_path = (Path(__file__).parent / 'output').resolve()
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output_path = (Path(__file__).parent / 'output').resolve()
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@ -50,7 +52,7 @@ class Initialize:
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subprocess.run(['insel', str(insel_file)], stdout=subprocess.DEVNULL)
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subprocess.run(['insel', str(insel_file)], stdout=subprocess.DEVNULL)
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ResultFactory('insel_monthly_energy_balance', city, output_path).enrich()
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ResultFactory('insel_monthly_energy_balance', city, output_path).enrich()
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self._city = city
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self._city = city
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print('init completed')
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print(f'init completed {datetime.datetime.now() - start}')
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return self._city
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return self._city
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