hub/imports/weather_feeders/dat_weather_parameters.py

"""
DatWeatherParameters class to extract weather parameters from a defined region in .dat format
SPDX - License - Identifier: LGPL - 3.0 - or -later
Copyright © 2020 Project Author Pilar Monsalvete pilar_monsalvete@yahoo.es
"""

import pandas as pd
from pathlib import Path
import sys


class DatWeatherParameters:
  """
  DatWeatherParameters class
  """
  def __init__(self, city, path):
    self._weather_values = None
    self._city = city
    self._city_name = city.climate_reference_city
    file_name = 'inseldb_' + self._city_name + '.dat'
    self._path = Path(path / file_name)

    if self._weather_values is None:
      try:
        self._weather_values = pd.read_csv(self._path, sep='\s+', header=None,
                                           names=['hour', 'global_horiz', 'temperature', 'diffuse', 'beam', 'empty'])
      except SystemExit:
        sys.stderr.write(f'Error: weather file {self._path} not found\n')
        sys.exit()

    for building in self._city.buildings:
      new_value = pd.DataFrame(self._weather_values[['temperature']].to_numpy(), columns=['inseldb'])
      if 'hour' not in building.external_temperature:
        building.external_temperature['hour'] = new_value
      else:
        pd.concat([building.external_temperature['hour'], new_value], axis=1)

      new_value = pd.DataFrame(self._weather_values[['global_horiz']].to_numpy(), columns=['inseldb'])
      if 'hour' not in building.global_horizontal:
        building.global_horizontal['hour'] = new_value
      else:
        pd.concat([building.global_horizontal['hour'], new_value], axis=1)

      new_value = pd.DataFrame(self._weather_values[['diffuse']].to_numpy(), columns=['inseldb'])
      if 'hour' not in building.diffuse:
        building.diffuse['hour'] = new_value
      else:
        pd.concat([building.diffuse['hour'], new_value], axis=1)

      new_value = pd.DataFrame(self._weather_values[['beam']].to_numpy(), columns=['inseldb'])
      if 'hour' not in building.beam:
        building.beam['hour'] = new_value
      else:
        pd.concat([building.beam['hour'], new_value], axis=1)