code: def euclidean_distance_square(a, b):
      """!
      @brief Calculate square Euclidian distance between vector a and b.
  
      @param[in] a (list): The first vector.
      @param[in] b (list): The second vector.
  
      @return (double) Square Euclidian distance between two vectors.
  
      """
  
      if ((type(a) == float) and (type(b) == float)) or (
          (type(a) == int) and (type(b) == int)
      ):
          return (a - b) ** 2.0
  
      distance = 0.0
      for i in range(0, len(a)):
          distance += (a[i] - b[i]) ** 2.0
  
      return distance
  
imports: import time
  import numpy
  from numpy import array
  from PIL import Image
  import matplotlib.pyplot
  from sys import platform
  from pyclustering.utils.metric import distance_metric, type_metric
label_desc: Use image node_id 9 for calling a global function with example usage: euclidean_distance_square(a, b) and returns: distance, unknown