code: def manhattan_distance(a, b):
      """!
      @brief Calculate Manhattan distance between vector a and b.
  
      @param[in] a (list): The first cluster.
      @param[in] b (list): The second cluster.
  
      @return (double) Manhattan distance between two vectors.
  
      """
  
      if ((type(a) == float) and (type(b) == float)) or (
          (type(a) == int) and (type(b) == int)
      ):
          return abs(a - b)
  
      distance = 0.0
      dimension = len(a)
  
      for i in range(0, dimension):
          distance += abs(a[i] - b[i])
  
      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 10 for calling a global function with example usage: manhattan_distance(a, b) and returns: distance, abs