class_docstr: A dlm module for all the access methods
      
class_docstr_tok: ["A","dlm","module","for","all","the","access","methods"]
docstr: get the error covariance for different components and
  filters.
  
  If the filtered dates are not (0, self.n - 1),
  then a warning will prompt stating the actual filtered dates.
  
  Args:
      filterType: the type of latent covariance to be returned. Could be
                  'forwardFilter', 'backwardSmoother', and 'predict'.
                  Default to 'forwardFilter'.
      name: the component to get latent cov. When name = 'all', then it
            returns the latent covariance for the time series. When
            name = some component's name, then it returns the latent
            covariance for that component. Default to 'all'.
  
  Returns:
      A list of numpy matrices, standing for the filtered latent
      covariance.
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code: def getLatentCov(self, filterType="forwardFilter", name="all"):
      """get the error covariance for different components and
      filters.
  
      If the filtered dates are not (0, self.n - 1),
      then a warning will prompt stating the actual filtered dates.
  
      Args:
          filterType: the type of latent covariance to be returned. Could be
                      'forwardFilter', 'backwardSmoother', and 'predict'.
                      Default to 'forwardFilter'.
          name: the component to get latent cov. When name = 'all', then it
                returns the latent covariance for the time series. When
                name = some component's name, then it returns the latent
                covariance for that component. Default to 'all'.
  
      Returns:
          A list of numpy matrices, standing for the filtered latent
          covariance.
  
      """
      # get the working dates
      start, end = self._checkAndGetWorkingDates(filterType=filterType)
      end += 1
      # to return the full latent covariance
      if name == "all":
          if filterType == "forwardFilter":
              return self.result.filteredCov[start:end]
          elif filterType == "backwardSmoother":
              return self.result.smoothedCov[start:end]
          elif filterType == "predict":
              return self.result.smoothedCov[start:end]
          else:
              raise NameError("Incorrect filter type.")
  
      # to return the latent covariance for a given component
      self._checkComponent(name)
      return self._getLatentCov(
          name=name, filterType=filterType, start=start, end=(end - 1)
      )
  
file_path: pydlm/pydlm/access/dlmAccessMod.py
imports: from copy import deepcopy
  from pydlm.base.tools import getInterval
  from pydlm.access._dlmGet import _dlmGet
label_desc: Use image node_id 7 for calling the dlmAccessModule obj's underlying member method code with example usage: obj.getLatentCov(filterType, name) and returns: self, self, self, self