code: def euclidean_distance(a, b):
      """!
      @brief Calculate Euclidean distance between vector a and b.
      @details The Euclidean between vectors (points) a and b is calculated by following formula:
  
      \f[
      dist(a, b) = \sqrt{ \sum_{i=0}^{N}(b_{i} - a_{i})^{2}) };
      \f]
  
      Where N is a length of each vector.
  
      @param[in] a (list): The first vector.
      @param[in] b (list): The second vector.
  
      @return (double) Euclidian distance between two vectors.
  
      @note This function for calculation is faster then standard function in ~100 times!
  
      """
  
      distance = euclidean_distance_square(a, b)
      return distance ** (0.5)
  
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 8 for calling a global function with example usage: euclidean_distance(a, b) and returns: unknown