code: def testGetLatentCov(self):
      # for forward filter
      self.dlm5.fitForwardFilter()
      filteredTrend = self.dlm5.getLatentCov(
          filterType="forwardFilter", name="trend"
      )
      diff = 0.0
      for i in range(len(filteredTrend)):
          diff += abs(
              filteredTrend[i][0, 0]
              - self.dlm5.result.filteredCov[i][0, 0]
          )
      self.assertAlmostEqual(diff, 0)
  
      # for backward smoother
      self.dlm5.fitBackwardSmoother()
      smoothedTrend = self.dlm5.getLatentCov(
          filterType="backwardSmoother", name="trend"
      )
      diff = 0.0
      for i in range(len(smoothedTrend)):
          diff += abs(
              smoothedTrend[i][0, 0]
              - self.dlm5.result.smoothedCov[i][0, 0]
          )
      self.assertAlmostEqual(diff, 0)
  
imports: import numpy
  import unittest
  from pydlm.modeler.trends import trend
  from pydlm.modeler.seasonality import seasonality
  from pydlm.modeler.dynamic import dynamic
  from pydlm.modeler.autoReg import autoReg
  from pydlm.dlm import dlm
label_desc: Use image node_id 22 for calling the testDlm obj's underlying member method code with example usage: obj.testGetLatentCov() without return types