class_docstr: !
  @brief Observer of K-Means algorithm that is used to collect information about clustering process on each iteration of the algorithm.
  
  @see kmeans
docstr: !
  @brief Initializer of observer of K-Means algorithm.
docstr_tok: ["!","@","brief","Initializer","of","observer","of","K-Means","algorithm","."]
code: def __init__(self):
      """!
      @brief Initializer of observer of K-Means algorithm.
  
      """
      self.__evolution_clusters = []
      self.__evolution_centers = []
      self.__initial_centers = []
  
imports: import copy
  import numpy
  import matplotlib.pyplot
  import matplotlib.animation
  import pyclustering.core.kmeans_wrapper
  from pyclustering.core.wrapper import ccore_library
  from pyclustering.core.metric_wrapper import metric_wrapper
  from pyclustering.cluster.encoder import type_encoding
  from pyclustering.cluster import cluster_visualizer
  from pyclustering.utils.metric import distance_metric, type_metric
label_desc: Use image node_id 1 to create a new kmeans_observer object  with example: obj = kmeans_observer()