code: def create_clustered_intra_test_data(
      self,
      train: Optional[pd.DataFrame] = None,
  ) -> pd.DataFrame:
      not_set = (
          set(
              [
                  (
                      row[AccessAnomalyConfig.default_user_col],
                      row[AccessAnomalyConfig.default_res_col],
                  )
                  for _, row in train.iterrows()
              ],
          )
          if train is not None
          else None
      )
  
      return self.tups2pdf(
          self.edges_between(
              self.hr_users, self.join_resources, 1.0, True
          )
          + self.edges_between(
              self.fin_users, self.join_resources, 1.0, True
          )
          + self.edges_between(
              self.eng_users, self.join_resources, 1.0, True
          )
          + self.edges_between(
              self.hr_users,
              self.hr_resources,
              0.025,
              False,
              not_set,
          )
          + self.edges_between(
              self.fin_users,
              self.fin_resources,
              0.05,
              False,
              not_set,
          )
          + self.edges_between(
              self.eng_users,
              self.eng_resources,
              0.035,
              False,
              not_set,
          ),
      )
  
file_path: SynapseML/core/src/main/python/synapse/ml/cyber/dataset.py
imports: from typing import List, Set, Optional, Tuple
  import pandas
  import random
  from synapse.ml.cyber.anomaly.collaborative_filtering import AccessAnomalyConfig
label_desc: Use image node_id 6 for calling the DataFactory obj's underlying member method code with example usage: obj.create_clustered_intra_test_data(train) and returns: self