code: def noise_distort1d(shape, sigma=100.0, magnitude=100.0):
      h, w = shape
      noise = cv.GaussianBlur(
          np.random.randn(w),
          (0, 0),
          sigmaX=sigma,
          borderType=cv.BORDER_REFLECT,
      )
      noise *= magnitude / np.amax(abs(noise))
      dys = np.array([noise] * h)
      deltas = np.array([dys, np.zeros((h, w))])
      return deltas
  
imports: import random
  from random import randint
  import numpy
  import cv2
label_desc: Use image node_id 7 for calling a global function with example usage: noise_distort1d(shape, sigma, magnitude) and returns: deltas