def _create_imshow_objects(self):
        """Turns off all the x and y axes in each Axis"""

        # 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)
Turns off all the x and y axes in each Axis