class_docstr: A dlm module containing all plot methods
      
docstr: Function to plot the N-day prediction results.
  
  The input is the same as `dlm.predictN`. For details,
  please refer to that function.
  
  Args:
      N:    The length of days to predict.
      date: The index when the prediction based on. Default to the
            last day.
      FeatureDict: The feature set for the dynamic Components, in a form
            of {"component_name": feature}, where the feature must have
            N elements of feature vectors. If the featureDict is not
            supplied, then the algo reuses those stored in the dynamic
            components. For dates beyond the last day, featureDict must
            be supplied.
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code: def plotPredictN(self, N=1, date=None, featureDict=None):
      """
      Function to plot the N-day prediction results.
  
      The input is the same as `dlm.predictN`. For details,
      please refer to that function.
  
      Args:
          N:    The length of days to predict.
          date: The index when the prediction based on. Default to the
                last day.
          FeatureDict: The feature set for the dynamic Components, in a form
                of {"component_name": feature}, where the feature must have
                N elements of feature vectors. If the featureDict is not
                supplied, then the algo reuses those stored in the dynamic
                components. For dates beyond the last day, featureDict must
                be supplied.
      """
      if date is None:
          date = self.n - 1
  
      # load the library only when needed
      # import pydlm.plot.dlmPlot as dlmPlot
      self.loadPlotLibrary()
  
      # provide a fake time for plotting
      if self.time is None:
          time = range(len(self.data))
      else:
          time = self.time
  
      # change option setting if some results are not available
      if not self.initialized:
          raise NameError(
              "The model must be constructed and"
              + " fitted before ploting."
          )
  
      # check the filter status and automatically turn off bad plots
      self._checkPlotOptions()
  
      predictedTimeRange = range(date, date + N)
      predictedData, predictedVar = self.predictN(
          N=N, date=date, featureDict=featureDict
      )
      dlmPlot.plotPrediction(
          time=time,
          data=self.data,
          predictedTime=predictedTimeRange,
          predictedData=predictedData,
          predictedVar=predictedVar,
          options=self.options,
      )
  
      dlmPlot.plotout()
  
file_path: pydlm/pydlm/plot/dlmPlotMod.py
imports: from pydlm.core._dlm import _dlm
label_desc: Use image node_id 10 for calling the dlmPlotModule obj's underlying member method code with example usage: obj.plotPredictN(N, date, featureDict) without return types