code: def test_hierarchical_k_means():
      X = [[10, -10, 30], [12, -8, 24]]
      truth_labels = np.tile([0, 1, 2], 5)
      X = np.tile(X, 5).T
      test_labels = hierarchical_k_means(X, 3)
      truth_labels = np.tile(
          [test_labels[0], test_labels[1], test_labels[2]], 5
      )
      assert_array_almost_equal(test_labels, truth_labels)
  
file_path: nilearn/nilearn/regions/tests/test_hierarchical_kmeans_clustering.py
imports: import numpy
  import pytest
  from numpy.testing import assert_array_almost_equal
  from nilearn._utils.data_gen import generate_fake_fmri
  from nilearn.input_data import NiftiMasker
  from nilearn.regions.hierarchical_kmeans_clustering import HierarchicalKMeans, _adjust_small_clusters, hierarchical_k_means
label_desc: Use image node_id 2 for calling a global function with example usage: test_hierarchical_k_means() without return types