code: def test_burkardt_14(self):
      # This is Moler's example.
      # This badly scaled matrix caused problems for MATLAB's expm().
      A = np.array(
          [
              [0, 1e-8, 0],
              [-(2e10 + 4e8 / 6.0), -3, 2e10],
              [200.0 / 3.0, 0, -200.0 / 3.0],
          ],
          dtype=float,
      )
      desired = np.array(
          [
              [
                  0.446849468283175,
                  1.54044157383952e-09,
                  0.462811453558774,
              ],
              [
                  -5743067.77947947,
                  -0.0152830038686819,
                  -4526542.71278401,
              ],
              [
                  0.447722977849494,
                  1.54270484519591e-09,
                  0.463480648837651,
              ],
          ],
          dtype=float,
      )
      actual = expm(A)
      assert_allclose(actual, desired)
  
imports: 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, 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 27 for calling the TestExpM obj's underlying member method code with example usage: obj.test_burkardt_14() without return types