code: def test_preprocess_X_expanded_cols(self, dist_type, X):
      np.random.seed(42)
      dist_types = [dist_type(idx=idx) for idx in np.arange(X.shape[1])]
      for dt in dist_types:
          X = dt.preprocess_X(X)
  
      # check size of column expansion
      assert X.shape[1] == 6
  
      # check that the correct indecies are pulled out
      assert dist_types[0].idx_group == [0, 2, 3]
      assert dist_types[1].idx_group == [1, 4, 5]
      # test that the expanded get_columns works
      assert np.array_equal(
          dist_types[0].get_columns(X), X[:, dist_types[0].idx_group]
      )
      assert np.array_equal(
          dist_types[1].get_columns(X), X[:, dist_types[1].idx_group]
      )
  
imports: import copy
  import numpy
  import pandas
  import pytest
  import torch
  from causalnex.structure.pytorch.dist_type import DistTypeBinary, DistTypeCategorical, DistTypeContinuous, DistTypeOrdinal, DistTypePoisson
  from causalnex.structure.pytorch.notears import from_numpy, from_pandas
label_desc: Use image node_id 5 for calling the TestDistTypeClasses obj's underlying member method code with example usage: obj.test_preprocess_X_expanded_cols(dist_type, X) without return types