code: def test_t_test_bonfer():
      """Test t_test_bonfer."""
      evaluator, metrics_by_strategy = evaluator_setup(
          score_function=accuracy_score
      )
      expected = np.array(
          [
              [False, True, True],
              [True, False, True],
              [True, True, False],
          ]
      )
      result = evaluator.t_test_with_bonferroni_correction().values
      assert np.array_equal(expected, result)
  
imports: import numpy
  import pandas
  import pytest
  from sklearn.metrics import accuracy_score
  from sktime.benchmarking.evaluation import Evaluator
  from sktime.benchmarking.metrics import PairwiseMetric
  from sktime.benchmarking.results import RAMResults
  from sktime.series_as_features.model_selection import PresplitFilesCV
  from sktime.utils.validation._dependencies import _check_soft_dependencies
label_desc: Use image node_id 7 for calling a global function with example usage: test_t_test_bonfer() without return types