text: __author__ = "Christian Kongsgaard"
  __license__ = 'MIT'
  
  # -------------------------------------------------------------------------------------------------------------------- #
  # IMPORTS
  
  # Modules
  import data_process_functions as dp
  import pandas as pd
  from matplotlib import pyplot as plt
  import numpy as np
  from scipy.stats import linregress
  import statsmodels
  
  # RiBuild Modules
  
  # -------------------------------------------------------------------------------------------------------------------- #
  # RIBuild
  
  acronym_file = r'U:\RIBuild\2D_1D\2D to 1D Transformation.xlsx'
  out_folder = r'C:\Users\ocni\PycharmProjects\delphin_6_automation\data_process\2d_1d\processed_data'
  result_folder = r'U:\RIBuild\2D_1D\Results'
  graphic_folder = r'U:\RIBuild\2D_1D\Processed Results\4A'
  #dp.process_results(acronym_file, result_folder, out_folder)
  
  quantities = ['heat loss', 'temperature', 'relative humidity', 'moisture content', 'moisture integral']
  quantity = quantities[2]
  hdf_file = out_folder + '/' + quantity + '.h5'
  
  
  # Open HDF
  #total_uninsulated_4a = pd.read_hdf(hdf_file, 'total_4a_36_uninsulated')
  #total_insulated_4a = pd.read_hdf(hdf_file, 'total_4a_36_insulated')
  
  insulation = 'insulated'
  acros = [f'dresden_zp_high_cement_{insulation}_36_4a', f'dresden_zd_high_cement_{insulation}_36_4a',
           f'potsdam_high_cement_{insulation}_36_4a', f'dresden_zp_low_cement_{insulation}_36_4a',
           f'dresden_zd_low_cement_{insulation}_36_4a', f'potsdam_low_cement_{insulation}_36_4a']
  
  acro_data_frame = pd.read_hdf(hdf_file, acros[1])
  
  for i in range(7):
      test_data = acro_data_frame.loc[:, pd.IndexSlice[str(i), :, 'out']].rolling(24*7).mean()
      test_data.plot()
  
  #granger_test_brick = statsmodels.grangercausalitytests(test_data)
  plt.show()
  