code: def test_get_feature_names_out(_varnames, _drop, df_vartypes):
      tr = MathFeatures(
          variables=["Age", "Marks"],
          func=["sum", "mean"],
          new_variables_names=_varnames,
          drop_original=_drop,
      )
      X = tr.fit_transform(df_vartypes)
      feat_out = list(X.columns)
      assert tr.get_feature_names_out(input_features=None) == feat_out
      assert (
          tr.get_feature_names_out(input_features=df_vartypes.columns)
          == feat_out
      )
  
imports: import numpy
  import pandas
  import pytest
  from sklearn.pipeline import Pipeline
  from feature_engine.creation import MathFeatures
label_desc: Use image node_id 15 for calling a global function with example usage: test_get_feature_names_out(_varnames, _drop, df_vartypes) without return types