code: def plotActivation(self, position=None, time=None, velocity=None):
      
      self.ax1.clear()
      y = self.activations["n"] + self.activations["s"] + self.activations["e"] + \
          self.activations["w"]
      self.ax1.matshow(y.reshape(self.dimensions))
  
      self.ax2.clear()
      self.ax2.matshow(self.activationsI.reshape(self.dimensions))
  
      self.ax3.clear()
      self.ax3.matshow(self.activationHistoryI.reshape(self.dimensions))
  
      titleString = ""
      if time is not None:
        titleString += "Time = {}".format(str(time))
      if velocity is not None:
        titleString += "  Velocity = {}".format(str(velocity)[:4])
      if position is not None:
        titleString += "  Position = {}".format(str(position)[:4])
      plt.suptitle(titleString)
  
      self.ax1.set_xlabel("Excitatory activity")
      self.ax2.set_xlabel("Inhibitory activity")
      self.ax3.set_xlabel("Boosting activity")
  
      plt.tight_layout()
  
      self.fig.canvas.draw()
docs: Plot the activation of the current cell populations.  Assumes that
      two axes have already been created, ax1 and ax2.  If done in a Jupyter
      notebook, this plotting will overwrite the old plot.
      :param position: The current location of the animal
      :param time: The current time in the simulation
      :param velocity: The current velocity of the animal