class_docstr: Block transformer that creates a block partitioned data object with each
  block k containing only the original feature k.
class_docstr_tok: ["Block","transformer","that","creates","a","block","partitioned","data","object","with","each","block","k","containing","only","the","original","feature","k","."]
code: def _transform_one_feature(self, X, k):
      return X[:, [k]]
  
imports: from abc import ABC, abstractmethod
  import numpy
  from collections import defaultdict
  from sklearn.ensemble import BaseEnsemble
  from sklearn.ensemble._forest import _generate_unsampled_indices, _generate_sample_indices
  from .local_stumps import make_stumps, tree_feature_transform
label_desc: Use image node_id 2 for calling the IdentityTransformer obj's underlying member method code with example usage: obj._transform_one_feature(X, k) and returns: X