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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def to_directed(self):
 """Return a directed representation of the graph. Returns ------- G : DynDiGraph A dynamic directed graph with the same name, same nodes, and with each edge (u,v,data) replaced by two directed edges (u,v,data) and (v,u,data). Notes ----- This returns a "deepcopy" of the edge, node, and graph attributes which attempts to completely copy all of the data and references. This is in contrast to the similar D=DynDiGraph(G) which returns a shallow copy of the data. See the Python copy module for more information on shallow and deep copies, http://docs.python.org/library/copy.html. Warning: If you have subclassed Graph to use dict-like objects in the data structure, those changes do not transfer to the DynDiGraph created by this method. Examples -------- [(0, 1), (1, 0)] If already directed, return a (deep) copy [(0, 1)] """

        from .dyndigraph import DynDiGraph
        G = DynDiGraph()
        G.name = self.name
        G.add_nodes_from(self)
        for it in self.interactions_iter():
            for t in it[2]['t']:
                G.add_interaction(it[0], it[1], t=t[0], e=t[1])

        G.graph = deepcopy(self.graph)
        G._node = deepcopy(self._node)
        return G