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 Returns True if there is connection between i and j oscillators and False - if connection doesn't exist.
  
  @param[in] i (uint): index of an oscillator in the network.
  @param[in] j (uint): index of an oscillator in the network.
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code: def has_connection(self, i, j):
      """!
      @brief Returns True if there is connection between i and j oscillators and False - if connection doesn't exist.
  
      @param[in] i (uint): index of an oscillator in the network.
      @param[in] j (uint): index of an oscillator in the network.
  
      """
  
      if (self._ccore_network_pointer is not None) and (
          self._osc_conn is None
      ):
          self._osc_conn = wrapper.sync_connectivity_matrix(
              self._ccore_network_pointer
          )
  
      return super().has_connection(i, j)
  
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 12 for calling the sync_network obj's underlying member method code with example usage: obj.has_connection(i, j) and returns: super