code: def test_nemenyi():
      """Test nemenyi."""
      evaluator, metrics_by_strategy = evaluator_setup(
          score_function=accuracy_score
      )
      expected = np.array(
          [
              [1.0, 0.082085, 0.53526143],
              [0.082085, 1.0, 0.53526143],
              [0.53526143, 0.53526143, 1.0],
          ]
      )
      expected = np.round(expected, 3)
      result = np.round(evaluator.nemenyi().values, 3)
  
      return 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 8 for calling a global function with example usage: test_nemenyi() and returns: np