code: def test_callable_method(df_correlated_double, random_uniform_method):
      X = df_correlated_double
  
      transformer = DropCorrelatedFeatures(
          variables=None, method=random_uniform_method, threshold=0.6
      )
  
      Xt = transformer.fit_transform(X)
  
      # test no empty dataframe
      assert not Xt.empty
  
      # test fit attrs
      assert len(transformer.correlated_feature_sets_) > 0
      assert len(transformer.features_to_drop_) > 0
      assert len(transformer.variables_) > 0
      assert transformer.n_features_in_ == len(X.columns)
  
file_path: feature_engine/tests/test_selection/test_drop_correlated_features.py
imports: import pandas
  import pytest
  from sklearn.datasets import make_classification
  from feature_engine.selection import DropCorrelatedFeatures
label_desc: Use image node_id 6 for calling a global function with example usage: test_callable_method(df_correlated_double, random_uniform_method) without return types