I would like to use NetworkX Graph
objects as keys in a Python dict
. However, I do not want the default behavior for comparison (i.e., by the address of the object). Instead, I would like isomorphic graphs to refer to be keys to the same elements in the dict
.
Is this behavior already implemented somewhere? I could not find any information in this direction.
If I have to implement it myself, is the following assessment realistic?
networkx.Graph
in a class.__eq__
such that it calls is_isomorphic
.__hash__
somehow (suggestions welcomed).I think that I would have to make this wrapped Graph immutable, because:
If a class defines mutable objects and implements an
__eq__()
method, it should not implement__hash__()
, since the implementation of hashable collections requires that a key’s hash value is immutable (if the object’s hash value changes, it will be in the wrong hash bucket).
Here is an example of subclassing a networkx Graph and adding a eq and hash function as you describe. I'm not sure if it solves your problem but should be a start.
import networkx as nx
class myGraph(nx.Graph):
def __eq__(self, other):
return nx.is_isomorphic(self, other)
def __hash__(self):
return hash(tuple(sorted(self.degree().values())))
if __name__ == '__main__':
G1 = myGraph([(1,2)])
G2 = myGraph([(2,3)])
G3 = myGraph([(1,2),(2,3)])
print G1.__hash__(), G1.edges()
print G2.__hash__(), G2.edges()
print G3.__hash__(), G3.edges()
print G1 == G2
print G1 == G3
graphs = {}
graphs[G1] = 'G1'
graphs[G2] = 'G2'
graphs[G3] = 'G3'
print graphs.items()
Outputs something like:
3713081631935493181 [(1, 2)]
3713081631935493181 [(2, 3)]
2528504235175490287 [(1, 2), (2, 3)]
True
False
[(<__main__.myGraph object at 0xe47a90>, 'G2'), (<__main__.myGraph object at 0x1643250>, 'G3')]
[aric@hamerkop tmp]$ python gc.py
3713081631935493181 [(1, 2)]
3713081631935493181 [(2, 3)]
2528504235175490287 [(1, 2), (2, 3)]
True
False
[(<__main__.myGraph object at 0x1fefad0>, 'G2'), (<__main__.myGraph object at 0x27ea290>, 'G3')]