chore: Track revdepcheck results

[krlmlr]

Only three packages failing.

[codecov]

Codecov Report

Merging #621 (66fef30) into dev (d9cc1a8) will not change coverage.
The diff coverage is n/a.

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  Coverage   62.69%   62.69%           
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  Files          73       73           
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  Misses       8031     8031           

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[ntamas]

r6causal imports causaleffect so I strongly suspect that the two failures are related.
As for sfnetwork, the output does not seem to provide any useful clues :(

[ntamas]

Also, is this without the change proposed to avoid recycling of attribute values?

[szhorvat]

As for sfnetwork, the output does not seem to provide any useful clues :(

It references distances() with the Johnson method, which we did change.

   10. └─sfnetworks:::st_network_cost.sfnetwork(...)
   11.   ├─base::do.call(igraph::distances, c(args, dots))
   12.   └─igraph (local) `<fn>`(`<sfnetwrk>`, 1, 10, weights = `<[m]>`, mode = "in", algorithm = "johnson")

Right now it only supports mode='out' with directed graphs, otherwise it throws an error. See #571 for why this change was necessary. Here they use mode='in'. So that's the reason for the failure.

But I have to say that the error message is very confusing:

> g<-sample_gnm(10,20,directed=T)
> distances(g,algorithm='johnson')
Error in distances(g, algorithm = "johnson") : 
  Johnson's algorithm works with mode="out" only for directed graphs

• It's unclear that the problem occurred because the default was mode='all'. BTW that's a pretty bad default for distances() ... I'd expect that in directed graphs, directed distances will be computed by default. But I guess this can't be fixed as it would be a "breaking change".
• When I read the message, it sounded as if the word "only" referred to "directed". In fact, it refers to the mode setting. It should probably say, "Johnson's algorithm only supports mode="out" when using directed graphs."

[krlmlr]

Yes, this is the baseline.

[szhorvat]

It might make sense to implement mode='in' for Johnson on the R side. All it really takes is swapping the from/to arguments an transposing the result matrix. Thoughts?

[szhorvat]

It's good to note that the test sfnetwork uses is somewhat pointless, as it's done on a graph with non-negative edge weights. Johnson's algorithm is only useful with directed graphs that have some negative weights. If the graph is not like this, the C function just calls the Dijkstra implementation anyway.

[ntamas]

All it really takes is swapping the from/to arguments an transposing the result matrix. Thoughts?

Does it? Wouldn't we also need to reverse the edge directions?

[szhorvat]

That function only returns distances, not paths. The A-to-B distance with "out" is the same as the B-to-A distance with "in", no? With "in" we go against the arrows in A--->B.

> g<-sample_gnm(10,20,directed=T)
> all(t(distances(g,mode='in')) == distances(g,mode='out'))
[1] TRUE

[krlmlr]

Merging to add infrastructure to track revdepcheck results on GitHub.