nodes: 0, module; 1, function_definition; 2, function_name:_nodes; 3, parameters; 4, block; 5, identifier:self; 6, expression_statement; 7, return_statement; 8, comment:"""
          Returns the list of nodes present in the network
  
          Examples
          --------
          >>> from pgmpy.models import DynamicBayesianNetwork as DBN
          >>> dbn = DBN()
          >>> dbn.add_nodes_from(['A', 'B', 'C'])
          >>> sorted(dbn._nodes())
          ['B', 'A', 'C']
          """; 9, call; 10, identifier:list; 11, argument_list; 12, call; 13, identifier:set; 14, argument_list; 15, list_comprehension; 16, identifier:node; 17, for_in_clause; 18, pattern_list; 19, call; 20, identifier:node; 21, identifier:timeslice; 22, attribute; 23, argument_list; 24, call; 25, identifier:nodes; 26, identifier:super; 27, argument_list; 28, identifier:DynamicBayesianNetwork; 29, identifier:self
code: def _nodes(self):
          """
          Returns the list of nodes present in the network
  
          Examples
          --------
          >>> from pgmpy.models import DynamicBayesianNetwork as DBN
          >>> dbn = DBN()
          >>> dbn.add_nodes_from(['A', 'B', 'C'])
          >>> sorted(dbn._nodes())
          ['B', 'A', 'C']
          """
          return list(set([node for node, timeslice in
                           super(DynamicBayesianNetwork, self).nodes()]))