docs: def get_n_cluster_in_events(event_numbers):
      '''Calculates the number of cluster in every given event.
      An external C++ library is used since there is no sufficient solution in python possible.
      Because of np.bincount # BUG #225 for values > int32 and the different handling under 32/64 bit operating systems.
  
      Parameters
      ----------
      event_numbers : numpy.array
          List of event numbers to be checked.
  
      Returns
      -------
      numpy.array
          First dimension is the event number.
          Second dimension is the number of cluster of the event.
      '''
      logging.debug("Calculate the number of cluster in every given event")
      event_numbers = np.ascontiguousarray(event_numbers)  # change memory alignement for c++ library
      result_event_numbers = np.empty_like(event_numbers)
      result_count = np.empty_like(event_numbers, dtype=np.uint32)
      result_size = analysis_functions.get_n_cluster_in_events(event_numbers, result_event_numbers, result_count)
      return np.vstack((result_event_numbers[:result_size], result_count[:result_size])).T