class_docstr: _dlm includes all basic functions for building dlm model.
  
  Attributes:
      data: the observed time series data
      n: the length of the time series data
      result: the inner class that records the filtered and smoothed results
      builder: the @builder that is used for providing the modeling
      functionality. For details please refer to @builder
      Filter: the filter used for filtering time series data using the model.
              For details please refer to @kalmanFilter
      initialized: indicates whether the dynamic linear model has been
                   initialized
      options: model options, including initial guess of the observational
               variance.
               More is going to be added (plot options and shrinkage options)
      time: the time label, used for plotting
  
  
  Methods:
      _initialize: initialize the dlm (builder and kalmanFilter)
      _forwardFilter: run forward filter for a specific start and end date
      _backwardSmoother: run backward smooth for a specific start and end
                         date
      _predictInSample: predict the latent state and observation for a given
                        period of time (deprecated)
      _resetModelStatus: reset the model status to its prior status
      _setModelStatus: set the model status to a specific date
      _defaultOptions: a class to store and set default options
      _result: a class to store the results
      _copy: copy the result from the model to the _result class
      _reverseCopy: copy the result from the _result class to the model
      _checkFeatureSize: check whether the features's n matches the data's n
      _checkComponent: check whether a component is in dlm
      _checkPlotOptions: set the correct options according to the fit
      _checkAndGetWorkingDates: get the correct filtering dates
docstr: Check the filter status and return the dates that have
  been filtered according to the filterType.
  
  Args:
      filterType: the type of the filter to check. Could be
                 "forwardFilter", "backwardSmoother" and "predict"
  
  Returns:
      a tuple of (start_date, end_date)
docstr_tok: ["Check","the","filter","status","and","return","the","dates","that","have","been","filtered","according","to","the","filterType",".","Args",":","filterType",":","the","type","of","the","filter","to","check",".","Could","be","``","forwardFilter","''",",","``","backwardSmoother","''","and","``","predict","''","Returns",":","a","tuple","of","(","start_date",",","end_date",")"]
code: def _checkAndGetWorkingDates(self, filterType):
      """Check the filter status and return the dates that have
      been filtered according to the filterType.
  
      Args:
          filterType: the type of the filter to check. Could be
                     "forwardFilter", "backwardSmoother" and "predict"
  
      Returns:
          a tuple of (start_date, end_date)
      """
      if filterType == "forwardFilter" or filterType == "predict":
          if self.result.filteredSteps != [0, self.n - 1]:
              self._logger.info(
                  "The fitlered dates are from "
                  + str(self.result.filteredSteps[0])
                  + " to "
                  + str(self.result.filteredSteps[1])
              )
          start = self.result.filteredSteps[0]
          end = self.result.filteredSteps[1]
  
      elif filterType == "backwardSmoother":
          if self.result.smoothedSteps != [0, self.n - 1]:
              self._logger.info(
                  "The smoothed dates are from "
                  + str(self.result.smoothedSteps[0])
                  + " to "
                  + str(self.result.smoothedSteps[1])
              )
          start = self.result.smoothedSteps[0]
          end = self.result.smoothedSteps[1]
  
      else:
          raise ValueError("Incorrect filter type.")
  
      return (start, end)
  
imports: from pydlm.base.kalmanFilter import kalmanFilter
  from pydlm.modeler.builder import builder
  from numpy import var
  import logging
label_desc: Use image node_id 16 for calling the _dlm obj's underlying member method code with example usage: obj._checkAndGetWorkingDates(filterType) and returns: start,  end