docs: def metta_config(quarter, num_dimensions):
      """Returns metta metadata for a quarter's SOC code classifier matrix
  
      Args:
          quarter (str) quarter, in format '2015Q1'
          num_dimensions (int) Number of features in matrix
  
      Returns: (dict) metadata suitable for metta.archive_train_test
      """
      first_day, last_day = quarter_boundaries(quarter)
      return {
          'start_time': first_day,
          'end_time': last_day,
          'prediction_window': 3, # ???
          'label_name': 'onet_soc_code',
          'label_type': 'categorical',
          'matrix_id': 'job_postings_{}'.format(quarter),
          'feature_names': ['doc2vec_{}'.format(i) for i in range(num_dimensions)],
      }