class_docstr: !
  @brief Visualizer of output dynamic of pulse-coupled neural network (PCNN).
class_docstr_tok: ["!","@","brief","Visualizer","of","output","dynamic","of","pulse-coupled","neural","network","(","PCNN",")","."]
docstr: !
  @brief Shows output dynamic (output of each oscillator) during simulation.
  
  @param[in] pcnn_output_dynamic (pcnn_dynamic): Output dynamic of the pulse-coupled neural network.
  @param[in] separate_representation (list): Consists of lists of oscillators where each such list consists of oscillator indexes that will be shown on separated stage.
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code: def show_output_dynamic(
      pcnn_output_dynamic, separate_representation=False
  ):
      """!
      @brief Shows output dynamic (output of each oscillator) during simulation.
  
      @param[in] pcnn_output_dynamic (pcnn_dynamic): Output dynamic of the pulse-coupled neural network.
      @param[in] separate_representation (list): Consists of lists of oscillators where each such list consists of oscillator indexes that will be shown on separated stage.
  
      """
  
      figure, _ = draw_dynamics(
          pcnn_output_dynamic.time,
          pcnn_output_dynamic.output,
          x_title="t",
          y_title="y(t)",
          separate=separate_representation,
      )
      plt.close(figure)
  
imports: import random
  import numpy
  import matplotlib.pyplot
  import matplotlib.animation
  from PIL import Image
  from pyclustering.nnet import *
  from pyclustering.core.wrapper import ccore_library
  import pyclustering.core.pcnn_wrapper
  from pyclustering.utils import draw_dynamics
label_desc: Use image node_id 2 for calling the pcnn_visualizer obj's underlying member method code with example usage: obj.show_output_dynamic(pcnn_output_dynamic, separate_representation) without return types