code: def test_fowlkes_mallows_score():
      # General case
      score = fowlkes_mallows_score(
          [0, 0, 0, 1, 1, 1], [0, 0, 1, 1, 2, 2]
      )
      assert_almost_equal(score, 4.0 / np.sqrt(12.0 * 6.0))
  
      # Perfect match but where the label names changed
      perfect_score = fowlkes_mallows_score(
          [0, 0, 0, 1, 1, 1], [1, 1, 1, 0, 0, 0]
      )
      assert_almost_equal(perfect_score, 1.0)
  
      # Worst case
      worst_score = fowlkes_mallows_score(
          [0, 0, 0, 0, 0, 0], [0, 1, 2, 3, 4, 5]
      )
      assert_almost_equal(worst_score, 0.0)
  
imports: import warnings
  import numpy
  import pytest
  from numpy.testing import assert_allclose, assert_array_almost_equal, assert_array_equal
  from sklearn.metrics.cluster import adjusted_mutual_info_score, adjusted_rand_score, completeness_score, contingency_matrix, entropy, expected_mutual_information, fowlkes_mallows_score, homogeneity_completeness_v_measure, homogeneity_score, mutual_info_score, normalized_mutual_info_score, pair_confusion_matrix, rand_score, v_measure_score
  from sklearn.metrics.cluster._supervised import _generalized_average, check_clusterings
  from sklearn.utils import assert_all_finite
  from sklearn.utils._testing import assert_almost_equal
label_desc: Use image node_id 19 for calling a global function with example usage: test_fowlkes_mallows_score() without return types