Sarah Lutteropp

Search in waves rocks! :) Here a few more arguments for it, taken from the Slack channel: - It is faster than the naive algo - It works pretty well,...

I highly advocate for exclusively using the search in waves strategy, at least in the first paper. It has so much optimization potential! I especially like that it allows us...

So far, search in waves just randomly adds a reticulation to the new network for the next wave (the within-wave horizontal moves are then used to reposition the reticulation). Later...

Another reason why search in waves might be working so much more nicely right now: Only adding/removing reticulations messes up the pmatrix- and clv-indices (because they change number of nodes/edges)....

@celinescornavacca Yes! :) NetRAX fully switched to the search in waves now. I have also added an arrow back, to check whether an arc removal in the best found n+1-reticulations...

Thanks! Is it the book "Phylogenetic Networks: Concepts, Algorithms and Applications"? I only got to read the PDF now, and I don't know what a hardwired vs. a softwired cluster...

I found the book online, trying to speed-read relevant-looking parts of it.

[Copy from Slack message, to have this here as well] I have just figured out that we can easily plot relative distance versions (in range [0.0, 1.0]) of all topological...

@celinescornavacca Does this approach make sense? I am assuming that we can have two networks (on the same set of taxa) which have zero clusters in common.

Of course, the trivial clusters will always be in common. Which means we will never get a distance score of 1.0 by applying this trick. Is this a problem?