code: def test_multiple_operations_with_multiple_variables(df_vartypes):
      transformer = RelativeFeatures(
          variables=["Age", "Marks"],
          reference=["Age", "Marks"],
          func=["sub", "add"],
      )
  
      X = transformer.fit_transform(df_vartypes)
  
      ref = pd.DataFrame.from_dict(
          {
              "Name": ["tom", "nick", "krish", "jack"],
              "City": ["London", "Manchester", "Liverpool", "Bristol"],
              "Age": [20, 21, 19, 18],
              "Marks": [0.9, 0.8, 0.7, 0.6],
              "dob": pd.date_range("2020-02-24", periods=4, freq="T"),
              "Age_sub_Age": [0, 0, 0, 0],
              "Marks_sub_Age": [-19.1, -20.2, -18.3, -17.4],
              "Age_sub_Marks": [19.1, 20.2, 18.3, 17.4],
              "Marks_sub_Marks": [0.0, 0.0, 0.0, 0.0],
              "Age_add_Age": [40, 42, 38, 36],
              "Marks_add_Age": [20.9, 21.8, 19.7, 18.6],
              "Age_add_Marks": [20.9, 21.8, 19.7, 18.6],
              "Marks_add_Marks": [1.8, 1.6, 1.4, 1.2],
          }
      )
  
      pd.testing.assert_frame_equal(X, ref)
  
      transformer = RelativeFeatures(
          variables=["Age", "Marks"],
          reference=["Age", "Marks"],
          func=["add", "sub"],
      )
  
      X = transformer.fit_transform(df_vartypes)
  
      ref = pd.DataFrame.from_dict(
          {
              "Name": ["tom", "nick", "krish", "jack"],
              "City": ["London", "Manchester", "Liverpool", "Bristol"],
              "Age": [20, 21, 19, 18],
              "Marks": [0.9, 0.8, 0.7, 0.6],
              "dob": pd.date_range("2020-02-24", periods=4, freq="T"),
              "Age_add_Age": [40, 42, 38, 36],
              "Marks_add_Age": [20.9, 21.8, 19.7, 18.6],
              "Age_add_Marks": [20.9, 21.8, 19.7, 18.6],
              "Marks_add_Marks": [1.8, 1.6, 1.4, 1.2],
              "Age_sub_Age": [0, 0, 0, 0],
              "Marks_sub_Age": [-19.1, -20.2, -18.3, -17.4],
              "Age_sub_Marks": [19.1, 20.2, 18.3, 17.4],
              "Marks_sub_Marks": [0.0, 0.0, 0.0, 0.0],
          }
      )
  
      pd.testing.assert_frame_equal(X, ref)
  
imports: import numpy
  import pandas
  import pytest
  from sklearn.pipeline import Pipeline
  from feature_engine.creation import RelativeFeatures
label_desc: Use image node_id 11 for calling a global function with example usage: test_multiple_operations_with_multiple_variables(df_vartypes) without return types