code: def solve_dicrete_lyapunov_direct(self, a, q, complex_step=False):
      # This is the discrete Lyapunov solver as "real function of real
      # variables":  the difference between this and the usual, complex,
      # version is that in the Kronecker product the second argument is
      # *not* conjugated here.
      if not complex_step:
          lhs = np.kron(a, a.conj())
          lhs = np.eye(lhs.shape[0]) - lhs
          x = np.linalg.solve(lhs, q.flatten())
      else:
          lhs = np.kron(a, a)
          lhs = np.eye(lhs.shape[0]) - lhs
          x = np.linalg.solve(lhs, q.flatten())
  
      return np.reshape(x, q.shape)
  
imports: import pytest
  import numpy
  from numpy.testing import assert_allclose, assert_equal, assert_array_less, assert_array_equal, assert_almost_equal
  import pandas
  from scipy.linalg import solve_discrete_lyapunov
  from statsmodels.tsa.statespace import tools
  from statsmodels.tsa.stattools import acovf
label_desc: Use image node_id 1 for calling the TestSolveDiscreteLyapunov obj's underlying member method code with example usage: obj.solve_dicrete_lyapunov_direct(a, q, complex_step) and returns: np