code: def test_graph_reverse_cuthill_mckee():
      A = np.array(
          [
              [1, 0, 0, 0, 1, 0, 0, 0],
              [0, 1, 1, 0, 0, 1, 0, 1],
              [0, 1, 1, 0, 1, 0, 0, 0],
              [0, 0, 0, 1, 0, 0, 1, 0],
              [1, 0, 1, 0, 1, 0, 0, 0],
              [0, 1, 0, 0, 0, 1, 0, 1],
              [0, 0, 0, 1, 0, 0, 1, 0],
              [0, 1, 0, 0, 0, 1, 0, 1],
          ],
          dtype=int,
      )
  
      graph = csr_matrix(A)
      perm = reverse_cuthill_mckee(graph)
      correct_perm = np.array([6, 3, 7, 5, 1, 2, 4, 0])
      assert_equal(perm, correct_perm)
  
      # Test int64 indices input
      graph.indices = graph.indices.astype("int64")
      graph.indptr = graph.indptr.astype("int64")
      perm = reverse_cuthill_mckee(graph, True)
      assert_equal(perm, correct_perm)
  
file_path: catboost/contrib/python/scipy/py2/scipy/sparse/csgraph/tests/test_reordering.py
imports: from __future__ import division, print_function, absolute_import
  import numpy
  from numpy.testing import assert_equal
  from scipy.sparse.csgraph import reverse_cuthill_mckee, maximum_bipartite_matching, structural_rank
  from scipy.sparse import diags, csc_matrix, csr_matrix, coo_matrix
label_desc: Use image node_id 1 for calling a global function with example usage: test_graph_reverse_cuthill_mckee() without return types