class_docstr: !
  @brief Genetic algorithm observer that is used to collect information about clustering process on each iteration.
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docstr: !
  @return (dict) Returns dictionary with keys 'chromosome' and 'fitness_function' where evolution of the best chromosome
           and its fitness function's value (evolution of global optimum) are stored in lists.
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code: def get_global_best(self):
      """!
      @return (dict) Returns dictionary with keys 'chromosome' and 'fitness_function' where evolution of the best chromosome
               and its fitness function's value (evolution of global optimum) are stored in lists.
  
      """
      return self._global_best_result
  
imports: import numpy
  import matplotlib.pyplot
  import matplotlib.animation
  from pyclustering.cluster import cluster_visualizer
  from pyclustering.cluster.ga_maths import ga_math
label_desc: Use image node_id 6 for calling the ga_observer obj's underlying member method code with example usage: obj.get_global_best() and returns: self