code: def test_burkardt_9(self):
      # This matrix is due to the NAG Library.
      # It is an example for function F01ECF.
      A = np.array(
          [
              [1, 2, 2, 2],
              [3, 1, 1, 2],
              [3, 2, 1, 2],
              [3, 3, 3, 1],
          ],
          dtype=float,
      )
      desired = np.array(
          [
              [740.7038, 610.8500, 542.2743, 549.1753],
              [731.2510, 603.5524, 535.0884, 542.2743],
              [823.7630, 679.4257, 603.5524, 610.8500],
              [998.4355, 823.7630, 731.2510, 740.7038],
          ],
          dtype=float,
      )
      actual = expm(A)
      assert_allclose(actual, desired)
  
imports: from __future__ import division, print_function, absolute_import
  import math
  import numpy
  from numpy import array, eye, exp, random
  from numpy.linalg import matrix_power
  from numpy.testing import assert_allclose, assert_, assert_array_almost_equal, assert_equal, assert_array_almost_equal_nulp
  from scipy._lib._numpy_compat import suppress_warnings
  from scipy.sparse import csc_matrix, SparseEfficiencyWarning
  from scipy.sparse.construct import eye
  from scipy.sparse.linalg.matfuncs import expm, _expm, ProductOperator, MatrixPowerOperator, _onenorm_matrix_power_nnm
  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 22 for calling the TestExpM obj's underlying member method code with example usage: obj.test_burkardt_9() without return types