pyclustering/container/cftree.py
def __split_leaf_node(self, node):
        """!
        @brief Performs splitting of the specified leaf node.
        
        @param[in] node (leaf_node): Leaf node that should be splitted.
        
        @return (list) New pair of leaf nodes [leaf_node1, leaf_node2].
        
        @warning Splitted node is transformed to non_leaf.
        
        """
        
        # search farthest pair of entries
        [farthest_entity1, farthest_entity2] = node.get_farthest_entries(self.__type_measurement);
                    
        # create new nodes
        new_node1 = leaf_node(farthest_entity1, node.parent, [ farthest_entity1 ], None);
        new_node2 = leaf_node(farthest_entity2, node.parent, [ farthest_entity2 ], None);
        
        # re-insert other entries
        for entity in node.entries:
            if ( (entity is not farthest_entity1) and (entity is not farthest_entity2) ):
                distance1 = new_node1.feature.get_distance(entity, self.__type_measurement);
                distance2 = new_node2.feature.get_distance(entity, self.__type_measurement);
                
                if (distance1 < distance2):
                    new_node1.insert_entry(entity);
                else:
                    new_node2.insert_entry(entity);
        
        return [new_node1, new_node2];
def __split_leaf_node(self, node):
        """!
        @brief Performs splitting of the specified leaf node.
        
        @param[in] node (leaf_node): Leaf node that should be splitted.
        
        @return (list) New pair of leaf nodes [leaf_node1, leaf_node2].
        
        @warning Splitted node is transformed to non_leaf.
        
        """
        
        # search farthest pair of entries
        [farthest_entity1, farthest_entity2] = node.get_farthest_entries(self.__type_measurement);
                    
        # create new nodes
        new_node1 = leaf_node(farthest_entity1, node.parent, [ farthest_entity1 ], None);
        new_node2 = leaf_node(farthest_entity2, node.parent, [ farthest_entity2 ], None);
        
        # re-insert other entries
        for entity in node.entries:
            if ( (entity is not farthest_entity1) and (entity is not farthest_entity2) ):
                distance1 = new_node1.feature.get_distance(entity, self.__type_measurement);
                distance2 = new_node2.feature.get_distance(entity, self.__type_measurement);
                
                if (distance1 < distance2):
                    new_node1.insert_entry(entity);
                else:
                    new_node2.insert_entry(entity);
        
        return [new_node1, new_node2];
def __split_leaf_node ( self , node ) : # search farthest pair of entries
 [ farthest_entity1 , farthest_entity2 ] = node . get_farthest_entries ( self . __type_measurement ) # create new nodes
 new_node1 = leaf_node ( farthest_entity1 , node . parent , [ farthest_entity1 ] , None ) new_node2 = leaf_node ( farthest_entity2 , node . parent , [ farthest_entity2 ] , None ) # re-insert other entries
 for entity in node . entries : if ( ( entity is not farthest_entity1 ) and ( entity is not farthest_entity2 ) ) : distance1 = new_node1 . feature . get_distance ( entity , self . __type_measurement ) distance2 = new_node2 . feature . get_distance ( entity , self . __type_measurement ) if ( distance1 < distance2 ) : new_node1 . insert_entry ( entity ) else : new_node2 . insert_entry ( entity ) return [ new_node1 , new_node2 ]
!
        @brief Performs splitting of the specified leaf node.
        
        @param[in] node (leaf_node): Leaf node that should be splitted.
        
        @return (list) New pair of leaf nodes [leaf_node1, leaf_node2].
        
        @warning Splitted node is transformed to non_leaf.
!