code: def _mapPotential(self, index):
      
  
      centerInput = self._mapColumn(index)
      columnInputs = self._getInputNeighborhood(centerInput).astype(uintType)
  
      # Select a subset of the receptive field to serve as the
      # the potential pool
      numPotential = int(columnInputs.size * self._potentialPct + 0.5)
      selectedInputs = numpy.empty(numPotential, dtype=uintType)
      self._random.sample(columnInputs, selectedInputs)
  
      potential = numpy.zeros(self._numInputs, dtype=uintType)
      potential[selectedInputs] = 1
  
      return potential
docs: Maps a column to its input bits. This method encapsulates the topology of
      the region. It takes the index of the column as an argument and determines
      what are the indices of the input vector that are located within the
      column's potential pool. The return value is a list containing the indices
      of the input bits. The current implementation of the base class only
      supports a 1 dimensional topology of columns with a 1 dimensional topology
      of inputs. To extend this class to support 2-D topology you will need to
      override this method. Examples of the expected output of this method:
      * If the potentialRadius is greater than or equal to the largest input
        dimension then each column connects to all of the inputs.
      * If the topology is one dimensional, the input space is divided up evenly
        among the columns and each column is centered over its share of the
        inputs.  If the potentialRadius is 5, then each column connects to the
        input it is centered above as well as the 5 inputs to the left of that
        input and the five inputs to the right of that input, wrapping around if
        wrapAround=True.
      * If the topology is two dimensional, the input space is again divided up
        evenly among the columns and each column is centered above its share of
        the inputs.  If the potentialRadius is 5, the column connects to a square
        that has 11 inputs on a side and is centered on the input that the column
        is centered above.
  
      Parameters:
      ----------------------------
      :param index:   The index identifying a column in the permanence, potential
                      and connectivity matrices.