class_docstr: !
  @brief Visualizer of K-Means algorithm's results.
  @details K-Means visualizer provides visualization services that are specific for K-Means algorithm.
docstr: !
  @brief Closes figure object that was used or allocated by the visualizer.
  
  @param[in] figure (figure): Figure object that was used or allocated by the visualizer.
docstr_tok: ["!","@","brief","Closes","figure","object","that","was","used","or","allocated","by","the","visualizer",".","@","param","[","in","]","figure","(","figure",")",":","Figure","object","that","was","used","or","allocated","by","the","visualizer","."]
code: def close(figure):
      """!
      @brief Closes figure object that was used or allocated by the visualizer.
  
      @param[in] figure (figure): Figure object that was used or allocated by the visualizer.
  
      """
      plt.close(figure)
  
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 2 for calling the kmeans_visualizer obj's underlying member method code with example usage: obj.close(figure) without return types