Consistent interface for (directed) graph creation

This toy example suggests a problem with our current approach to creating graphs:

In [13]: A = np.array([[0,1,0],[1,0,1],[0,0,0]])                                                                                                                                               

In [14]: A                                                                                                                                                                                     
Out[14]: 
array([[0, 1, 0],
       [1, 0, 1],
       [0, 0, 0]])

In [15]: import networkx as nx                                                                                                                                                                 

In [16]: G = nx.from_numpy_array(A)                                                                                                                                                            

In [17]: G.is_directed()                                                                                                                                                                       
Out[17]: False

It seems that if we have an asymmetric matrix we need to be explicit about using the nx.DiGraph constructor.

A utility function for determining which graph constructor to use (and performing other potentially useful preprocessing, like removing self-loops) would probably be useful here.

[sdmccabe]

Making explicit a conversation with @leotrs: I’m not sure that from_numpy_array strictly requires networkx 2.2, but the arguments I’m passing to the create_using parameter follow a style used in 2.2. If need be, I suspect we can rewrite some things to be 2.0-compatible, but for the sake of simplicity let’s just bump the requirements for now. (Networkx 2.3 will be out soon anyway.)

[sdmccabe]

@jkbren @tlarock Note that now that this is merged it might affect the distance heatmaps. Let me know if something has dramatically changed.