class_docstr: !
  @brief Model of oscillatory network that is based on the Kuramoto model of synchronization.
  
  @details CCORE option can be used to use the pyclustering core - C/C++ shared library for processing that significantly increases performance.
docstr: !
  @brief Performs static simulation of Sync oscillatory network.
  
  @param[in] steps (uint): Number steps of simulations during simulation.
  @param[in] time (double): Time of simulation.
  @param[in] solution (solve_type): Type of solution (solving).
  @param[in] collect_dynamic (bool): If True - returns whole dynamic of oscillatory network, otherwise returns only last values of dynamics.
  
  @return (list) Dynamic of oscillatory network. If argument 'collect_dynamic' = True, than return dynamic for the whole simulation time,
          otherwise returns only last values (last step of simulation) of dynamic.
  
  @see simulate_dynamic()
  @see simulate_static()
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code: def simulate(
      self, steps, time, solution=solve_type.FAST, collect_dynamic=True
  ):
      """!
      @brief Performs static simulation of Sync oscillatory network.
  
      @param[in] steps (uint): Number steps of simulations during simulation.
      @param[in] time (double): Time of simulation.
      @param[in] solution (solve_type): Type of solution (solving).
      @param[in] collect_dynamic (bool): If True - returns whole dynamic of oscillatory network, otherwise returns only last values of dynamics.
  
      @return (list) Dynamic of oscillatory network. If argument 'collect_dynamic' = True, than return dynamic for the whole simulation time,
              otherwise returns only last values (last step of simulation) of dynamic.
  
      @see simulate_dynamic()
      @see simulate_static()
  
      """
  
      return self.simulate_static(
          steps, time, solution, collect_dynamic
      )
  
imports: import math
  import numpy
  import random
  import matplotlib.pyplot
  import matplotlib.animation
  import pyclustering.core.sync_wrapper
  from pyclustering.core.wrapper import ccore_library
  from scipy.integrate import odeint
  from pyclustering.nnet import network, conn_represent, conn_type, initial_type, solve_type
  from pyclustering.utils import pi, draw_dynamics, draw_dynamics_set, set_ax_param
label_desc: Use image node_id 6 for calling the sync_network obj's underlying member method code with example usage: obj.simulate(steps, time, solution, collect_dynamic) and returns: self