def to_directed(self):
"""Return a directed representation of the graph.
Returns
-------
G : MultiDiGraph
A 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=DiGraph(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 MultiGraph to use dict-like objects in the
data structure, those changes do not transfer to the MultiDiGraph
created by this method.
Examples
--------
>>> G = nx.Graph() # or MultiGraph, etc
>>> G.add_path([0,1])
>>> H = G.to_directed()
>>> H.edges()
[(0, 1), (1, 0)]
If already directed, return a (deep) copy
>>> G = nx.DiGraph() # or MultiDiGraph, etc
>>> G.add_path([0,1])
>>> H = G.to_directed()
>>> H.edges()
[(0, 1)]
"""
from networkx.classes.multidigraph import MultiDiGraph
G=MultiDiGraph()
G.add_nodes_from(self)
G.add_edges_from( (u,v,key,deepcopy(datadict))
for u,nbrs in self.adjacency_iter()
for v,keydict in nbrs.items()
for key,datadict in keydict.items() )
G.graph=deepcopy(self.graph)
G.node=deepcopy(self.node)
return G
