code: def _copyAllocatedStates(self):
      
  
      # Get learn states if we need to print them out
      if self.verbosity > 1 or self.retrieveLearningStates:
        (activeT, activeT1, predT, predT1) = self.cells4.getLearnStates()
        self.lrnActiveState['t-1'] = activeT1.reshape((self.numberOfCols, self.cellsPerColumn))
        self.lrnActiveState['t'] = activeT.reshape((self.numberOfCols, self.cellsPerColumn))
        self.lrnPredictedState['t-1'] = predT1.reshape((self.numberOfCols, self.cellsPerColumn))
        self.lrnPredictedState['t'] = predT.reshape((self.numberOfCols, self.cellsPerColumn))
  
      if self.allocateStatesInCPP:
        assert False
        (activeT, activeT1, predT, predT1, colConfidenceT, colConfidenceT1, confidenceT,
         confidenceT1) = self.cells4.getStates()
        self.cellConfidence['t'] = confidenceT.reshape((self.numberOfCols, self.cellsPerColumn))
        self.cellConfidence['t-1'] = confidenceT1.reshape((self.numberOfCols, self.cellsPerColumn))
        self.colConfidence['t'] = colConfidenceT.reshape(self.numberOfCols)
        self.colConfidence['t-1'] = colConfidenceT1.reshape(self.numberOfCols)
        self.infActiveState['t-1'] = activeT1.reshape((self.numberOfCols, self.cellsPerColumn))
        self.infActiveState['t'] = activeT.reshape((self.numberOfCols, self.cellsPerColumn))
        self.infPredictedState['t-1'] = predT1.reshape((self.numberOfCols, self.cellsPerColumn))
        self.infPredictedState['t'] = predT.reshape((self.numberOfCols, self.cellsPerColumn))
docs: If state is allocated in CPP, copy over the data into our numpy arrays.