docs: def multi_load_data(Channel, RunNos, RepeatNos, directoryPath='.', calcPSD=True, NPerSegmentPSD=1000000):
      """
      Lets you load multiple datasets at once assuming they have a 
      filename which contains a pattern of the form:
      CH<ChannelNo>_RUN00...<RunNo>_REPEAT00...<RepeatNo>    
  
      Parameters
      ----------
      Channel : int
          The channel you want to load
      RunNos : sequence
          Sequence of run numbers you want to load
      RepeatNos : sequence
          Sequence of repeat numbers you want to load
      directoryPath : string, optional
          The path to the directory housing the data
          The default is the current directory
  
      Returns
      -------
      Data : list
          A list containing the DataObjects that were loaded. 
      """
      matching_files = search_data_std(Channel=Channel, RunNos=RunNos, RepeatNos=RepeatNos, directoryPath=directoryPath)
      #data = []
      #for filepath in matching_files_:
      #    data.append(load_data(filepath, calcPSD=calcPSD, NPerSegmentPSD=NPerSegmentPSD))
  
      cpu_count = _cpu_count()
      workerPool = _Pool(cpu_count)
      load_data_partial = _partial(load_data, calcPSD=calcPSD, NPerSegmentPSD=NPerSegmentPSD)
      data = workerPool.map(load_data_partial, matching_files)
      workerPool.close()
      workerPool.terminate()
      workerPool.join()
         
      #with _Pool(cpu_count) as workerPool:
          #load_data_partial = _partial(load_data, calcPSD=calcPSD, NPerSegmentPSD=NPerSegmentPSD)
          #data = workerPool.map(load_data_partial, files_CorrectRepeatNo)
      return data