Fix Floyd-Warshall when weights have 0 weight. Addresses #976.
Clarify comment in code regarding nan weights.
Fix tests that fail due to hash randomization
Make `nonedge` default to 0.0. Add more comments.
Clarify description of `weight` parameter.
Allow 'weight' to be callable.
For example, weight=lambda attrs: attrs.get('weight', 0).
Handle nonzero edges via masked arrays.
Also, allow custom multigraph_weight opertor functions.
Revert commits 1bca2d1 and 31b5b70.
Fixed typo
Merge pull request #1000 from invisibleroads/patch-1

Fixed typo
Describe conversion to directed graph
Some pagerank implementations work with multigraphs

Remove restrictions on multigraphs in pagerank_numpy() and pagerank_scipy().
Clarify in comments.
pagerank() degree should consider weights
Clarify input type. Remove multigraph guard.
Warn on zero out-degree (row-sum)
Force double precision in scipy matrix for layout

Gets rid of scipy eigs/eigsh warning of double precision only
Match convergence tolerances

Match convergence criteria to be the same for pagerank and pagerank_scipy
Normalize negative entries to match pagerank algs

Now pagerank_scipy() is the same as pagerank().
That is, both will possibly produce the same incorrect answer if you put in negative weights.
Merge pull request #1002 from hagberg/scipy-eigs-double

Force double precision in scipy matrix for layout
Merge pull request #1001 from hagberg/stochastic-zero

Stochastic zero row + pagerank

The various pagerank(), pagerank_numpy(), and pagerank_scipy() should produce the same results now for cases with weighted graphs with zero row sums or negative weights.   The negative weight case may produce answers but I don't know if they are meaningful (certainly that breaks the intentions and assumptions of the algorithm.)  The convergence tolerances now match between implementations too.