code: def reset(self,):
      
  
      self.activeState['t-1'].fill(0)
      self.activeState['t'].fill(0)
      self.predictedState['t-1'].fill(0)
      self.predictedState['t'].fill(0)
      self.learnState['t-1'].fill(0)
      self.learnState['t'].fill(0)
      self.confidence['t-1'].fill(0)
      self.confidence['t'].fill(0)
  
      # Flush the segment update queue
      self.segmentUpdates = {}
  
      self._internalStats['nInfersSinceReset'] = 0
  
      #To be removed
      self._internalStats['curPredictionScore'] = 0
      #New prediction score
      self._internalStats['curPredictionScore2']   = 0
      self._internalStats['curFalseNegativeScore'] = 0
      self._internalStats['curFalsePositiveScore'] = 0
  
      self._internalStats['curMissing'] = 0
      self._internalStats['curExtra'] = 0
  
  
      # When a reset occurs, set prevSequenceSignature to the signature of the
      # just-completed sequence and start accumulating histogram for the next
      # sequence.
      self._internalStats['prevSequenceSignature'] = None
      if self.collectSequenceStats:
        if self._internalStats['confHistogram'].sum() > 0:
          sig = self._internalStats['confHistogram'].copy()
          sig.reshape(self.numberOfCols * self.cellsPerColumn)
          self._internalStats['prevSequenceSignature'] = sig
        self._internalStats['confHistogram'].fill(0)
  
      self.resetCalled = True
docs: Reset the state of all cells.
      This is normally used between sequences while training. All internal states
      are reset to 0.