code: def test_csgraph_to_dense():
      np.random.seed(1234)
      G = np.random.random((10, 10))
      nulls = G < 0.8
      G[nulls] = np.inf
  
      G_csr = csgraph_from_dense(G)
  
      for null_value in [0, 10, -np.inf, np.inf]:
          G[nulls] = null_value
          assert_array_almost_equal(
              G, csgraph_to_dense(G_csr, null_value)
          )
  
file_path: catboost/contrib/python/scipy/py2/scipy/sparse/csgraph/tests/test_conversions.py
imports: from __future__ import division, print_function, absolute_import
  import numpy
  from numpy.testing import assert_array_almost_equal
  from scipy.sparse import csr_matrix
  from scipy.sparse.csgraph import csgraph_from_dense, csgraph_to_dense
label_desc: Use image node_id 2 for calling a global function with example usage: test_csgraph_to_dense() without return types