old_contents: # -*- coding: utf-8 -*-
  """
  This file imports the price details from the cost database as a class. This helps in preventing multiple importing
  of the corresponding values in individual files.
  """
  from __future__ import division
  import pandas as pd
  import numpy as np
  from cea.constants import HOURS_IN_YEAR
  
  __author__ = "Jimeno A. Fonseca"
  __copyright__ = "Copyright 2019, Architecture and Building Systems - ETH Zurich"
  __credits__ = ["Jimeno A. Fonseca"]
  __license__ = "MIT"
  __version__ = "0.1"
  __maintainer__ = "Daren Thomas"
  __email__ = "thomas@arch.ethz.ch"
  __status__ = "Production"
  
  
  class Prices(object):
      def __init__(self, locator, detailed_electricity_pricing):
          pricing = pd.read_excel(locator.get_database_supply_systems(sheet_name="FEEDSTOCKS"))
          self.NG_PRICE = pricing[pricing['Code'] == 'NATURALGAS'].iloc[0]['Opex_var_buy_USD2015perkWh'] / 1000 # in USD/Wh
          self.BG_PRICE = pricing[pricing['Code'] == 'BIOGAS'].iloc[0]['Opex_var_buy_USD2015perkWh']  / 1000# in USD/Wh
          self.WB_PRICE = pricing[pricing['Code'] == 'WASTE'].iloc[0]['Opex_var_buy_USD2015perkWh']  / 1000# in USD/Wh
          self.DB_PRICE = pricing[pricing['Code'] == 'WOOD'].iloc[0]['Opex_var_buy_USD2015perkWh'] / 1000 # in USD/Wh
          self.SOLAR_PRICE = pricing[pricing['Code'] == 'SOLAR'].iloc[0]['Opex_var_buy_USD2015perkWh']  / 1000# in USD/Wh
          self.SOLAR_PRICE_EXPORT = pricing[pricing['Code'] == 'SOLAR'].iloc[0]['Opex_var_sell_USD2015perkWh'] / 1000 # in USD/Wh
  
          if detailed_electricity_pricing:
              electricity_costs = pd.read_excel(locator.get_database_supply_systems(), sheet_name="DETAILED_ELEC_COSTS")
              self.ELEC_PRICE = electricity_costs['Opex_var_buy_USD2015perkWh'].values / 1000  # in USD_2015 per Wh
              self.ELEC_PRICE_EXPORT = electricity_costs['Opex_var_sell_USD2015perkWh'].values / 1000  # in USD_2015 per Wh
          else:
              average_electricity_price = pricing[pricing['Code'] == 'GRID'].iloc[0]['Opex_var_buy_USD2015perkWh'] / 1000
              average_electricity_selling_price = pricing[pricing['Code'] == 'GRID'].iloc[0]['Opex_var_sell_USD2015perkWh'] / 1000
              self.ELEC_PRICE = np.ones(HOURS_IN_YEAR) * average_electricity_price  # in USD_2015 per Wh
              self.ELEC_PRICE_EXPORT = np.ones(HOURS_IN_YEAR) * average_electricity_selling_price  # in USD_2015 per Wh
  
  
new_contents: # -*- coding: utf-8 -*-
  """
  This file imports the price details from the cost database as a class. This helps in preventing multiple importing
  of the corresponding values in individual files.
  """
  from __future__ import division
  import pandas as pd
  import numpy as np
  from cea.constants import HOURS_IN_YEAR
  
  __author__ = "Jimeno A. Fonseca"
  __copyright__ = "Copyright 2019, Architecture and Building Systems - ETH Zurich"
  __credits__ = ["Jimeno A. Fonseca"]
  __license__ = "MIT"
  __version__ = "0.1"
  __maintainer__ = "Daren Thomas"
  __email__ = "thomas@arch.ethz.ch"
  __status__ = "Production"
  
  
  class Prices(object):
      def __init__(self, locator, detailed_electricity_pricing):
          pricing = pd.read_excel(locator.get_database_supply_systems(), sheet_name="FEEDSTOCKS")
          self.NG_PRICE = pricing[pricing['Code'] == 'NATURALGAS'].iloc[0]['Opex_var_buy_USD2015perkWh'] / 1000 # in USD/Wh
          self.BG_PRICE = pricing[pricing['Code'] == 'BIOGAS'].iloc[0]['Opex_var_buy_USD2015perkWh']  / 1000# in USD/Wh
          self.WB_PRICE = pricing[pricing['Code'] == 'WASTE'].iloc[0]['Opex_var_buy_USD2015perkWh']  / 1000# in USD/Wh
          self.DB_PRICE = pricing[pricing['Code'] == 'WOOD'].iloc[0]['Opex_var_buy_USD2015perkWh'] / 1000 # in USD/Wh
          self.SOLAR_PRICE = pricing[pricing['Code'] == 'SOLAR'].iloc[0]['Opex_var_buy_USD2015perkWh']  / 1000# in USD/Wh
          self.SOLAR_PRICE_EXPORT = pricing[pricing['Code'] == 'SOLAR'].iloc[0]['Opex_var_sell_USD2015perkWh'] / 1000 # in USD/Wh
  
          if detailed_electricity_pricing:
              electricity_costs = pd.read_excel(locator.get_database_supply_systems(), sheet_name="DETAILED_ELEC_COSTS")
              self.ELEC_PRICE = electricity_costs['Opex_var_buy_USD2015perkWh'].values / 1000  # in USD_2015 per Wh
              self.ELEC_PRICE_EXPORT = electricity_costs['Opex_var_sell_USD2015perkWh'].values / 1000  # in USD_2015 per Wh
          else:
              average_electricity_price = pricing[pricing['Code'] == 'GRID'].iloc[0]['Opex_var_buy_USD2015perkWh'] / 1000
              average_electricity_selling_price = pricing[pricing['Code'] == 'GRID'].iloc[0]['Opex_var_sell_USD2015perkWh'] / 1000
              self.ELEC_PRICE = np.ones(HOURS_IN_YEAR) * average_electricity_price  # in USD_2015 per Wh
              self.ELEC_PRICE_EXPORT = np.ones(HOURS_IN_YEAR) * average_electricity_selling_price  # in USD_2015 per Wh
  
  
subject: fix to sheet name