code: def test_general_transformation_without_dropping_variables(
      df_cyclical,
  ):
      # test case 1: just one variable.
      cyclical = CyclicalFeatures(variables=["day"])
      X = cyclical.fit_transform(df_cyclical)
  
      transf_df = df_cyclical.copy()
  
      # expected output
      transf_df["day_sin"] = [
          -0.78183,
          0.0,
          -0.97493,
          0.43388,
          0.78183,
          0.97493,
          -0.43388,
      ]
      transf_df["day_cos"] = [
          0.623490,
          1.0,
          -0.222521,
          -0.900969,
          0.623490,
          -0.222521,
          -0.900969,
      ]
  
      # fit attr
      assert cyclical.max_values_ == {"day": 7}
  
      # test transform output
      pd.testing.assert_frame_equal(X, transf_df)
  
file_path: feature_engine/tests/test_creation/test_cyclical_features.py
imports: import pandas
  import pytest
  from numpy import array
  from feature_engine.creation import CyclicalFeatures
label_desc: Use image node_id 2 for calling a global function with example usage: test_general_transformation_without_dropping_variables(df_cyclical) without return types