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 __update_single_canvas_xlim(self, canvas_index, t):
      dynamic_xlim = [0, t[len(t) - 1]]
      if (self.__canvases[canvas_index].x_lim is None) or (
          self.__canvases[canvas_index].x_lim < dynamic_xlim
      ):
          self.__canvases[canvas_index].x_lim = dynamic_xlim
  
imports: import matplotlib.pyplot
  from pyclustering.utils import set_ax_param
label_desc: Use image node_id 12 for calling the dynamic_visualizer obj's underlying member method code with example usage: obj.__update_single_canvas_xlim(canvas_index, t) without return types