code: def _drcif_feature(X, interval, dim, att, c22, case_id=None):
      """Compute DrCIF feature."""
      if att > 21:
          return _summary_stat(
              X[:, dim, interval[0] : interval[1]], att
          )
      else:
          return c22._transform_single_feature(
              X[:, dim, interval[0] : interval[1]], att, case_id=case_id
          )
  
file_path: sktime/sktime/classification/sklearn/_continuous_interval_tree_numba.py
imports: import math
  import numpy
  from sktime.utils.numba.njit import njit
  from sktime.utils.numba.stats import iqr, mean, numba_max, numba_min, slope, std
label_desc: Use image node_id 3 for calling a global function with example usage: _drcif_feature(X, interval, dim, att, c22, case_id) and returns: _summary_stat, c22