code: def show_clusters(clusters, sample, covariances, means, figure = None, display = True):
          
          
          visualizer = cluster_visualizer()
          visualizer.append_clusters(clusters, sample)
          
          if figure is None:
              figure = visualizer.show(display = False)
          else:
              visualizer.show(figure = figure, display = False)
          
          if len(sample[0]) == 2:
              ema_visualizer.__draw_ellipses(figure, visualizer, clusters, covariances, means)
  
          if display is True:
              plt.show()
  
          return figure
docs: !
          @brief Draws clusters and in case of two-dimensional dataset draws their ellipses.
          
          @param[in] clusters (list): Clusters that were allocated by the algorithm.
          @param[in] sample (list): Dataset that were used for clustering.
          @param[in] covariances (list): Covariances of the clusters.
          @param[in] means (list): Means of the clusters.
          @param[in] figure (figure): If 'None' then new is figure is creater, otherwise specified figure is used
                      for visualization.
          @param[in] display (bool): If 'True' then figure will be shown by the method, otherwise it should be
                      shown manually using matplotlib function 'plt.show()'.
          
          @return (figure) Figure where clusters were drawn.