code: def test_alternative_operation(df_vartypes):
      # input df
      df = df_vartypes.copy()
  
      # Expected result
      dft = df.copy()
      dft["Age_truediv_Marks"] = dft["Age"].truediv(dft["Marks"])
      dft["Age_floordiv_Marks"] = dft["Age"].floordiv(dft["Marks"])
      dft["Age_mod_Marks"] = dft["Age"].mod(dft["Marks"])
      dft["Age_pow_Marks"] = dft["Age"].pow(dft["Marks"])
  
      transformer = RelativeFeatures(
          variables=["Age"],
          reference=["Marks"],
          func=["truediv", "floordiv", "mod", "pow"],
      )
      X = transformer.fit_transform(df)
  
      pd.testing.assert_frame_equal(X, dft)
  
imports: import numpy
  import pandas
  import pytest
  from sklearn.pipeline import Pipeline
  from feature_engine.creation import RelativeFeatures
label_desc: Use image node_id 9 for calling a global function with example usage: test_alternative_operation(df_vartypes) without return types