code: def printComputeEnd(self, output, learn=False):
      
      if self.verbosity >= 3:
        print "----- computeEnd summary: "
        print "numBurstingCols: %s, " % (self.activeState['t'].min(axis=1).sum()),
        print "curPredScore2: %s, " % (self._internalStats['curPredictionScore2']),
        print "curFalsePosScore: %s, " % (self._internalStats['curFalsePositiveScore']),
        print "1-curFalseNegScore: %s, " % (1-self._internalStats['curFalseNegativeScore']),
        print "numPredictedCells[t-1]: %s" % (self.predictedState['t-1'].sum()),
        print "numSegments: ",self.getNumSegments()
  
        print "----- activeState (%d on) ------" \
                % (self.activeState['t'].sum())
        self.printActiveIndices(self.activeState['t'])
        if self.verbosity >= 5:
          self.printState(self.activeState['t'])
  
        print "----- predictedState (%d on)-----" \
                % (self.predictedState['t'].sum())
        self.printActiveIndices(self.predictedState['t'])
        if self.verbosity >= 5:
          self.printState(self.predictedState['t'])
  
        print "----- cell confidence -----"
        self.printActiveIndices(self.confidence['t'], andValues=True)
        if self.verbosity >= 5:
          self.printConfidence(self.confidence['t'])
  
        print "----- confidence[t-1] for currently active cells -----"
        cc = self.confidence['t-1'] * self.activeState['t']
        self.printActiveIndices(cc, andValues=True)
  
        if self.verbosity == 4:
          print "Cells, predicted segments only:"
          self.printCells(predictedOnly=True)
        elif self.verbosity >= 5:
          print "Cells, all segments:"
          self.printCells(predictedOnly=False)
        print
docs: Called at the end of inference to print out various diagnostic
      information based on the current verbosity level.