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 Calculates current level of local (partial) synchronization in the network.
  
  @return (double) Level of local (partial) synchronization.
  
  @see sync_order()
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code: def sync_local_order(self):
      """!
      @brief Calculates current level of local (partial) synchronization in the network.
  
      @return (double) Level of local (partial) synchronization.
  
      @see sync_order()
  
      """
  
      if self._ccore_network_pointer is not None:
          return wrapper.sync_local_order(self._ccore_network_pointer)
  
      return order_estimator.calculate_local_sync_order(
          self._phases, self
      )
  
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 4 for calling the sync_network obj's underlying member method code with example usage: obj.sync_local_order() and returns: order_estimator, wrapper