"""
Total operational costs module
SPDX - License - Identifier: LGPL - 3.0 - or -later
Copyright © 2024 Project Coder Saeed Ranjbar saeed.ranjbar@mail.concordia.ca
Code contributor Oriol Gavalda Torrellas oriol.gavalda@concordia.ca
"""
import math
import pandas as pd

from hub.city_model_structure.building import Building
import hub.helpers.constants as cte

from scripts.costs.configuration import Configuration
from scripts.costs.cost_base import CostBase
from scripts.costs.peak_load import PeakLoad


class TotalOperationalCosts(CostBase):
  """
  Total Operational costs class
  """

  def __init__(self, building: Building, configuration: Configuration):
    super().__init__(building, configuration)
    columns_list = self.columns()
    self._yearly_operational_costs = pd.DataFrame(
      index=self._rng,
      columns=columns_list,
      dtype='float'
    )

  def calculate(self) -> pd.DataFrame:
    """
    Calculate total operational costs
    :return: pd.DataFrame
    """
    building = self._building
    fuel_consumption_breakdown = building.energy_consumption_breakdown
    archetype = self._archetype
    total_floor_area = self._total_floor_area
    if archetype.function == 'residential':
      factor = total_floor_area / 80
    else:
      factor = 1
    total_electricity_consumption = sum(self._building.energy_consumption_breakdown[cte.ELECTRICITY].values())
    peak_electricity_load = PeakLoad(self._building).electricity_peak_load
    peak_load_value = peak_electricity_load.max(axis=1)
    peak_electricity_demand = peak_load_value[1] / 1000  # self._peak_electricity_demand adapted to kW
    fuels = archetype.operational_cost.fuels
    for fuel in fuels:
      if fuel.type in fuel_consumption_breakdown.keys():
        if fuel.type == cte.ELECTRICITY:
          variable_electricity_cost_year_0 = (
              total_electricity_consumption * fuel.variable[0] / 1000
          )
          peak_electricity_cost_year_0 = peak_electricity_demand * fuel.fixed_power * 12
          monthly_electricity_cost_year_0 = fuel.fixed_monthly * 12 * factor
          for year in range(1, self._configuration.number_of_years + 1):
            price_increase_electricity = math.pow(1 + self._configuration.electricity_price_index, year)
            price_increase_peak_electricity = math.pow(1 + self._configuration.electricity_peak_index, year)
            self._yearly_operational_costs.at[year, 'Fixed Costs Electricity Peak'] = (
                peak_electricity_cost_year_0 * price_increase_peak_electricity
            )
            self._yearly_operational_costs.at[year, 'Fixed Costs Electricity Monthly'] = (
                monthly_electricity_cost_year_0 * price_increase_peak_electricity
            )
            if not isinstance(variable_electricity_cost_year_0, pd.DataFrame):
              variable_costs_electricity = variable_electricity_cost_year_0 * price_increase_electricity
            else:
              variable_costs_electricity = float(variable_electricity_cost_year_0.iloc[0] * price_increase_electricity)
            self._yearly_operational_costs.at[year, 'Variable Costs Electricity'] = (
              variable_costs_electricity
            )
        else:
          fuel_fixed_cost = fuel.fixed_monthly * 12 * factor
          if fuel.type == cte.BIOMASS:
            conversion_factor = 1
          else:
            conversion_factor = fuel.density[0]
          variable_cost_fuel = (
            ((sum(fuel_consumption_breakdown[fuel.type].values()) * 3600)/(1e6*fuel.lower_heating_value[0] * conversion_factor)) * fuel.variable[0])
          for year in range(1, self._configuration.number_of_years + 1):
            price_increase_gas = math.pow(1 + self._configuration.gas_price_index, year)
            self._yearly_operational_costs.at[year, f'Fixed Costs {fuel.type}'] = fuel_fixed_cost * price_increase_gas
            self._yearly_operational_costs.at[year, f'Variable Costs {fuel.type}'] = (
                variable_cost_fuel * price_increase_gas)
    self._yearly_operational_costs.fillna(0, inplace=True)

    return self._yearly_operational_costs

  def columns(self):
    columns_list = []
    fuels = [key for key in self._building.energy_consumption_breakdown.keys()]
    for fuel in fuels:
      if fuel == cte.ELECTRICITY:
        columns_list.append('Fixed Costs Electricity Peak')
        columns_list.append('Fixed Costs Electricity Monthly')
        columns_list.append('Variable Costs Electricity')
      else:
        columns_list.append(f'Fixed Costs {fuel}')
        columns_list.append(f'Variable Costs {fuel}')

    return columns_list