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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def update_disparity_map(self):
 """ Update disparity map in GUI. The disparity image is normalized to the range 0-255 and then divided by 255, because OpenCV multiplies it by 255 when displaying. This is because the pixels are stored as floating points. """

        disparity = self.block_matcher.get_disparity(self.pair)
        norm_coeff = 255 / disparity.max()
        cv2.imshow(self.window_name, disparity * norm_coeff / 255)
        cv2.waitKey()