def __create_sync_layer(self, weights):
        """!
        @brief Creates second layer of the network.
        
        @param[in] weights (list): List of weights of SOM neurons.
        
        @return (syncnet) Second layer of the network.
        
        """
        sync_layer = syncnet(weights, 0.0, initial_phases = initial_type.RANDOM_GAUSSIAN, ccore = False);
        
        for oscillator_index1 in range(0, len(sync_layer)):
            for oscillator_index2 in range(oscillator_index1 + 1, len(sync_layer)):
                if (self.__has_object_connection(oscillator_index1, oscillator_index2)):
                    sync_layer.set_connection(oscillator_index1, oscillator_index2);
        
        return sync_layer;
def __create_sync_layer(self, weights):
        """!
        @brief Creates second layer of the network.
        
        @param[in] weights (list): List of weights of SOM neurons.
        
        @return (syncnet) Second layer of the network.
        
        """
        sync_layer = syncnet(weights, 0.0, initial_phases = initial_type.RANDOM_GAUSSIAN, ccore = False);
        
        for oscillator_index1 in range(0, len(sync_layer)):
            for oscillator_index2 in range(oscillator_index1 + 1, len(sync_layer)):
                if (self.__has_object_connection(oscillator_index1, oscillator_index2)):
                    sync_layer.set_connection(oscillator_index1, oscillator_index2);
        
        return sync_layer;
def __create_sync_layer ( self , weights ) : sync_layer = syncnet ( weights , 0.0 , initial_phases = initial_type . RANDOM_GAUSSIAN , ccore = False ) for oscillator_index1 in range ( 0 , len ( sync_layer ) ) : for oscillator_index2 in range ( oscillator_index1 + 1 , len ( sync_layer ) ) : if ( self . __has_object_connection ( oscillator_index1 , oscillator_index2 ) ) : sync_layer . set_connection ( oscillator_index1 , oscillator_index2 ) return sync_layer
!
        @brief Creates second layer of the network.
        
        @param[in] weights (list): List of weights of SOM neurons.
        
        @return (syncnet) Second layer of the network.
!