class_docstr: !
  @brief Basic output dynamic visualizer.
  @details The aim of the visualizer is to displayed output dynamic of any process, for example, output dynamic of
            oscillatory network.
code: def __format_canvases(self, axis):
      for index in range(self.__size):
          canvas = self.__canvases[index]
  
          ax = self.__get_axis(axis, index)
          set_ax_param(
              ax,
              canvas.x_title,
              canvas.y_title,
              canvas.x_lim,
              canvas.y_lim,
              canvas.x_labels,
              canvas.y_labels,
              True,
          )
  
          if (len(self.__canvases) > 1) and (
              index != len(self.__canvases) - 1
          ):
              ax.get_xaxis().set_visible(False)
  
imports: import matplotlib.pyplot
  from pyclustering.utils import set_ax_param
label_desc: Use image node_id 10 for calling the dynamic_visualizer obj's underlying member method code with example usage: obj.__format_canvases(axis) without return types