code: def _naive_concordance_summary_statistics(event_times, predicted_event_times, event_observed):
      
      num_pairs = 0.0
      num_correct = 0.0
      num_tied = 0.0
  
      for a, time_a in enumerate(event_times):
          pred_a = predicted_event_times[a]
          event_a = event_observed[a]
          # Don't want to double count
          for b in range(a + 1, len(event_times)):
              time_b = event_times[b]
              pred_b = predicted_event_times[b]
              event_b = event_observed[b]
  
              if _valid_comparison(time_a, time_b, event_a, event_b):
                  num_pairs += 1.0
                  crct, ties = _concordance_value(time_a, time_b, pred_a, pred_b, event_a, event_b)
                  num_correct += crct
                  num_tied += ties
  
      return (num_correct, num_tied, num_pairs)
docs: Fallback, simpler method to compute concordance.
  
      Assumes the data has been verified by lifelines.utils.concordance_index first.