code: def test_compute_jac_indices():
      n = 2
      m = 4
      k = 2
      i, j = compute_jac_indices(n, m, k)
      s = coo_matrix((np.ones_like(i), (i, j))).toarray()
      s_true = np.array(
          [
              [1, 1, 1, 1, 0, 0, 0, 0, 1, 1],
              [1, 1, 1, 1, 0, 0, 0, 0, 1, 1],
              [0, 0, 1, 1, 1, 1, 0, 0, 1, 1],
              [0, 0, 1, 1, 1, 1, 0, 0, 1, 1],
              [0, 0, 0, 0, 1, 1, 1, 1, 1, 1],
              [0, 0, 0, 0, 1, 1, 1, 1, 1, 1],
              [1, 1, 0, 0, 0, 0, 1, 1, 1, 1],
              [1, 1, 0, 0, 0, 0, 1, 1, 1, 1],
              [1, 1, 0, 0, 0, 0, 1, 1, 1, 1],
              [1, 1, 0, 0, 0, 0, 1, 1, 1, 1],
          ]
      )
      assert_array_equal(s, s_true)
  
imports: import sys
  import numpy
  from numpy.testing import assert_, assert_array_equal, assert_allclose, assert_equal
  from pytest import raises
  from scipy.sparse import coo_matrix
  from scipy.special import erf
  from scipy.integrate._bvp import modify_mesh, estimate_fun_jac, estimate_bc_jac, compute_jac_indices, construct_global_jac, solve_bvp
label_desc: Use image node_id 36 for calling a global function with example usage: test_compute_jac_indices() without return types