docs: def _load_h5(file, devices, channels):
      """
      Function used for reading .h5 files generated by OpenSignals.
  
      ----------
      Parameters
      ----------
      file : file path.
          File Path.
  
      devices : list ["mac_address_1" <str>, "mac_address_2" <str>...]
          List of devices selected by the user.
  
      channels : list [[mac_address_1_channel_1 <int>, mac_address_1_channel_2 <int>...],
                      [mac_address_2_channel_1 <int>...]...]
          From which channels will the data be loaded.
  
      Returns
      -------
      out_dict : dict
          Data read from the h5 file.
      """
  
      # %%%%%%%%%%%%%%%%%%%%%%%%%%%% Creation of h5py object %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
      h5_object = h5py.File(file)
  
      # %%%%%%%%%%%%%%%%%%%%%%%%% Data of the selected channels %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
      out_dict = {}
      for dev_nbr, device in enumerate(devices):
          out_dict[device] = {}
          for chn in channels[dev_nbr]:
              data_temp = list(h5_object.get(device).get("raw").get("channel_" + str(chn)))
  
              # Conversion of a nested list to a flatten list by list-comprehension
              # The following line is equivalent to:
              # for sublist in h5_data:
              #    for item in sublist:
              #        flat_list.append(item)
              #out_dict[device]["CH" + str(chn)] = [item for sublist in data_temp for item in sublist]
              out_dict[device]["CH" + str(chn)] = numpy.concatenate(data_temp)
  
      return out_dict