code: def test_transform_shuffled_indices(self, get_iris_data):
      data = get_iris_data.copy(deep=True)
      ground_truth = np.array(
          [
              [0, 0, 1, 0, 1],
              [0, 0, 0, 0, 0],
              [0, 1, 1, 2, 1],
              [2, 1, 1, 0, 1],
              [1, 2, 1, 0, 2],
              [2, 2, 2, 0, 0],
              [1, 1, 0, 2, 2],
              [1, 2, 0, 2, 2],
              [2, 2, 0, 1, 2],
              [1, 1, 2, 1, 1],
          ]
      )
  
      sample_data = data[["sepal length (cm)", "target"]].sample(
          50, random_state=2021
      )
      dt_single = DecisionTreeSupervisedDiscretiserMethod(
          tree_params={"max_depth": 2},
          mode="single",
      )
      dt_single.fit(
          feat_names=["sepal length (cm)"],
          dataframe=sample_data,
          target_continuous=False,
          target="target",
      )
      discretiser_output = dt_single.transform(
          sample_data[["sepal length (cm)"]]
      )
      assert discretiser_output.isnull().values.sum() == 0
      assert (
          ground_truth == discretiser_output.values.reshape(10, 5)
      ).all()
  
file_path: causalnex/tests/discretiser/test_decision_tree.py
imports: import numpy
  import pytest
  from causalnex.discretiser.discretiser_strategy import DecisionTreeSupervisedDiscretiserMethod
label_desc: Use image node_id 11 for calling the TestDecisionTree obj's underlying member method code with example usage: obj.test_transform_shuffled_indices(get_iris_data) without return types