code: def test_asymmetric_laplacian():
      # adjacency matrix
      A = [[0, 1, 0], [4, 2, 0], [0, 0, 0]]
  
      # Laplacian matrix using out-degree
      L = [[1, -1, 0], [-4, 4, 0], [0, 0, 0]]
      d = [1, 4, 0]
      _check_laplacian(A, L, d, normed=False, use_out_degree=True)
  
      # normalized Laplacian matrix using out-degree
      L = [[1, -0.5, 0], [-2, 1, 0], [0, 0, 0]]
      d = [1, 2, 1]
      _check_laplacian(A, L, d, normed=True, use_out_degree=True)
  
      # Laplacian matrix using in-degree
      L = [[4, -1, 0], [-4, 1, 0], [0, 0, 0]]
      d = [4, 1, 0]
      _check_laplacian(A, L, d, normed=False, use_out_degree=False)
  
      # normalized Laplacian matrix using in-degree
      L = [[1, -0.5, 0], [-2, 1, 0], [0, 0, 0]]
      d = [2, 1, 1]
      _check_laplacian(A, L, d, normed=True, use_out_degree=False)
  
file_path: catboost/contrib/python/scipy/py3/scipy/sparse/csgraph/tests/test_graph_laplacian.py
imports: import numpy
  from numpy.testing import assert_allclose, assert_array_almost_equal
  from pytest import raises
  from scipy import sparse
  from scipy.sparse import csgraph
label_desc: Use image node_id 7 for calling a global function with example usage: test_asymmetric_laplacian() without return types