code: def test_indicators_are_correct():
      transformer = Winsorizer(
          tail="left",
          capping_method="quantiles",
          fold=0.1,
          add_indicators=True,
      )
      df = pd.DataFrame({"col": np.arange(100).astype(np.float64)})
      df_out = transformer.fit_transform(df)
      expected_ind = np.r_[
          np.repeat(True, 10), np.repeat(False, 90)
      ].astype(np.float64)
      pd.testing.assert_frame_equal(
          df_out.drop("col", axis=1),
          df.assign(col_left=expected_ind).drop("col", axis=1),
      )
  
      transformer.set_params(tail="right")
      df_out = transformer.fit_transform(df)
      expected_ind = np.r_[
          np.repeat(False, 90), np.repeat(True, 10)
      ].astype(np.float64)
      pd.testing.assert_frame_equal(
          df_out.drop("col", axis=1),
          df.assign(col_right=expected_ind).drop("col", axis=1),
      )
  
      transformer.set_params(tail="both")
      df_out = transformer.fit_transform(df)
      expected_ind_left = np.r_[
          np.repeat(True, 10), np.repeat(False, 90)
      ].astype(np.float64)
      expected_ind_right = np.r_[
          np.repeat(False, 90), np.repeat(True, 10)
      ].astype(np.float64)
      pd.testing.assert_frame_equal(
          df_out.drop("col", axis=1),
          df.assign(
              col_left=expected_ind_left, col_right=expected_ind_right
          ).drop("col", axis=1),
      )
  
imports: import math
  import numpy
  import pandas
  import pytest
  from feature_engine.outliers import Winsorizer
label_desc: Use image node_id 13 for calling a global function with example usage: test_indicators_are_correct() without return types