code: def test_three_clusters(bisecting_strategy, init):
      """Tries to perform bisect k-means for three clusters to check
      if splitting data is performed correctly.
      """
      X = np.array(
          [
              [1, 1],
              [10, 1],
              [3, 1],
              [10, 0],
              [2, 1],
              [10, 2],
              [10, 8],
              [10, 9],
              [10, 10],
          ]
      )
      bisect_means = BisectingKMeans(
          n_clusters=3,
          random_state=0,
          bisecting_strategy=bisecting_strategy,
          init=init,
      )
      bisect_means.fit(X)
  
      expected_centers = [[2, 1], [10, 1], [10, 9]]
      expected_labels = [0, 1, 0, 1, 0, 1, 2, 2, 2]
  
      assert_allclose(
          sorted(expected_centers),
          sorted(bisect_means.cluster_centers_.tolist()),
      )
      assert_allclose(
          v_measure_score(expected_labels, bisect_means.labels_), 1.0
      )
  
file_path: scikit-learn/sklearn/cluster/tests/test_bisect_k_means.py
imports: import numpy
  import pytest
  from sklearn.cluster import BisectingKMeans
  from sklearn.metrics import v_measure_score
  from sklearn.utils._testing import assert_allclose, assert_array_equal
  from sklearn.utils.fixes import CSR_CONTAINERS
label_desc: Use image node_id 1 for calling a global function with example usage: test_three_clusters(bisecting_strategy, init) without return types