code: def stripUnlearnedColumns(self, activeArray):
      
      neverLearned = numpy.where(self._activeDutyCycles == 0)[0]
      activeArray[neverLearned] = 0
docs: Removes the set of columns who have never been active from the set of
      active columns selected in the inhibition round. Such columns cannot
      represent learned pattern and are therefore meaningless if only inference
      is required. This should not be done when using a random, unlearned SP
      since you would end up with no active columns.
  
      :param activeArray: An array whose size is equal to the number of columns.
          Any columns marked as active with an activeDutyCycle of 0 have
          never been activated before and therefore are not active due to
          learning. Any of these (unlearned) columns will be disabled (set to 0).