docs: def find_sample_min_std(self, Intensities):
          '''
          find the best interpretation with the minimum stratard deviation (in units of percent % !)
          '''
  
          Best_array = []
          best_array_std_perc = inf
          Best_array_tmp = []
          Best_interpretations = {}
          Best_interpretations_tmp = {}
          for this_specimen in list(Intensities.keys()):
              for value in Intensities[this_specimen]:
                  Best_interpretations_tmp[this_specimen] = value
                  Best_array_tmp = [value]
                  all_other_specimens = list(Intensities.keys())
                  all_other_specimens.remove(this_specimen)
  
                  for other_specimen in all_other_specimens:
                      closest_value = self.find_close_value(
                          Intensities[other_specimen], value)
                      Best_array_tmp.append(closest_value)
                      Best_interpretations_tmp[other_specimen] = closest_value
  
                  if std(Best_array_tmp, ddof=1) / mean(Best_array_tmp) < best_array_std_perc:
                      Best_array = Best_array_tmp
                      best_array_std_perc = std(
                          Best_array, ddof=1) / mean(Best_array_tmp)
                      Best_interpretations = copy.deepcopy(
                          Best_interpretations_tmp)
                      Best_interpretations_tmp = {}
          return Best_interpretations, mean(Best_array), std(Best_array, ddof=1)