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.
docstr: !
  @brief Append single dynamic to specified canvas (by default to the first with index '0').
  
  @param[in] t (list): Time points that corresponds to dynamic values and considered on a X axis.
  @param[in] dynamic (list): Value points of dynamic that are considered on an Y axis.
  @param[in] canvas (uint): Canvas where dynamic should be displayed.
  @param[in] color (string): Color that is used for drawing dynamic on the canvas.
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code: def append_dynamic(self, t, dynamic, canvas=0, color="blue"):
      """!
      @brief Append single dynamic to specified canvas (by default to the first with index '0').
  
      @param[in] t (list): Time points that corresponds to dynamic values and considered on a X axis.
      @param[in] dynamic (list): Value points of dynamic that are considered on an Y axis.
      @param[in] canvas (uint): Canvas where dynamic should be displayed.
      @param[in] color (string): Color that is used for drawing dynamic on the canvas.
  
      """
      description = dynamic_descr(canvas, t, dynamic, False, color)
      self.__dynamic_storage.append(description)
      self.__update_canvas_xlim(description.time, description.separate)
  
imports: import matplotlib.pyplot
  from pyclustering.utils import set_ax_param
label_desc: Use image node_id 3 for calling the dynamic_visualizer obj's underlying member method code with example usage: obj.append_dynamic(t, dynamic, canvas, color) without return types