code: def score(self, measurement, output_format='array'):
          
          scores = np.array([])
          for obs in self.observations:
              c, sd = self.__get_centroids_sd(obs)
              p, ids = self.__get_features_for_observation(data_frame = measurement, observation=obs,
                                                           last_column_is_id=True)
  
              scores = np.append(scores, [self.get_single_score(p, centroids=c, sd=sd)], axis=0)
  
          if output_format == 'array':
              return scores.astype(int)
          else:
              return np.array_str(scores.astype(int))
docs: Method to score/classify a measurement against the trained knn clusters
  
              :param measurement: the point to classify
              :type measurement: pandas.DataFrame
              :param output_format: the format to return the scores ('array' or 'str')
              :type output_format: string
              :return scores: the scores for a given test/point
              :rtype scores: np.array