code: def test_burkardt_5(self):
      # This example is due to Moler and Van Loan.
      # This matrix is strictly upper triangular
      # All powers of A are zero beyond some (low) limit.
      # This example will cause problems for Pade approximations.
      A = np.array(
          [
              [0, 6, 0, 0],
              [0, 0, 6, 0],
              [0, 0, 0, 6],
              [0, 0, 0, 0],
          ],
          dtype=float,
      )
      desired = np.array(
          [
              [1, 6, 18, 36],
              [0, 1, 6, 18],
              [0, 0, 1, 6],
              [0, 0, 0, 1],
          ],
          dtype=float,
      )
      actual = expm(A)
      assert_allclose(actual, desired)
  
imports: import math
  import numpy
  from numpy import array, eye, exp, random
  from numpy.testing import assert_allclose, assert_, assert_array_almost_equal, assert_equal, assert_array_almost_equal_nulp, suppress_warnings
  from scipy.sparse import csc_matrix, csc_array, SparseEfficiencyWarning
  from scipy.sparse._construct import eye
  from scipy.sparse.linalg._matfuncs import expm, _expm, ProductOperator, MatrixPowerOperator, _onenorm_matrix_power_nnm, matrix_power
  from scipy.sparse._sputils import matrix
  from scipy.linalg import logm
  from scipy.special import factorial, binom
  import scipy.sparse
  import scipy.sparse.linalg
label_desc: Use image node_id 18 for calling the TestExpM obj's underlying member method code with example usage: obj.test_burkardt_5() without return types