code: def _create_imshow_objects(self):
          
  
          # uniform values for initial image can cause weird behaviour with normalization
          #       as imshow.set_data() does not automatically update the normalization!!
          # using random data is a better choice
          random_image = np.random.rand(20, 20)
          self.images = [None] * len(self.flat_grid)
          for ix, ax in enumerate(self.flat_grid):
              self.images[ix] = ax.imshow(random_image, **self.display_params)
docs: Turns off all the x and y axes in each Axis