code: def test_get_feature_names_out_shuffled(create_data):
      data, _ = create_data()
      order = np.array(
          [
              "binary_1",
              "N0",
              "N3",
              "trinary",
              "binary_2",
              "N1",
              "N2",
              "many",
          ]
      )
      expected_columns = np.array(
          [
              "binary_1=No",
              "N0",
              "N3",
              "trinary=Blue",
              "trinary=Red",
              "binary_2=West",
              "N1",
              "N2",
              "many=Two",
              "many=Three",
              "many=Four",
              "many=Five",
              "many=Six",
          ]
      )
  
      t = OneHotEncoder()
      t.fit(data.loc[:, order])
  
      out_names = t.get_feature_names_out()
      assert_array_equal(out_names, expected_columns)
  
      with pytest.raises(
          ValueError,
          match="input_features is not equal to feature_names_in_",
      ):
          t.get_feature_names_out(data.columns.tolist())
  
file_path: scikit-survival/tests/test_preprocessing.py
imports: from collections import OrderedDict
  import numpy
  from numpy.testing import assert_array_equal
  import pandas
  import pandas.testing
  import pytest
  from sksurv.preprocessing import OneHotEncoder
label_desc: Use image node_id 5 for calling the TestOneHotEncoder obj's underlying member method code with example usage: obj.test_get_feature_names_out_shuffled(create_data) without return types