Nondeterminism in test_directed_input

[sdmccabe]

Test failed once on PR #293.

_____________________________ test_directed_input ______________________________
    def test_directed_input():
        with warnings.catch_warnings():
            warnings.filterwarnings(
                "ignore", message="Coercing directed graph to undirected."
            )
            G = nx.fast_gnp_random_graph(100, 0.3, directed=True)
    
            for label, obj in distance.__dict__.items():
                if isinstance(obj, type) and BaseDistance in obj.__bases__:
                    dist = obj().dist(G, G)
                    assert np.isclose(dist, 0.0)
    
            G1 = nx.fast_gnp_random_graph(100, 0.3, directed=True)
            G2 = nx.fast_gnp_random_graph(100, 0.3, directed=True)
   
            for label, obj in distance.__dict__.items():
                if isinstance(obj, type) and BaseDistance in obj.__bases__:
                    dist1 = obj().dist(G1, G2)
                    dist2 = obj().dist(G2, G1)
>                   assert np.isclose(dist1, dist2)
E                   assert False
E                    +  where False = <function isclose at 0x7fc528395f70>(nan, nan)
E                    +    where <function isclose at 0x7fc528395f70> = np.isclose
test_distance.py:97: AssertionError

This seemed to be some nondeterminism in the test. I would guess from the nan result that the graphs weren't strongly connected and a distance depends on that.