poker VS openmc

I wrote a Haskell version that includes two components:

A very efficient function to rank a set of Texas Hold’em hands.

A Monte Carlo situation that gives you the probability of winning each hand from any known amount of information.

It is available here: https://github.com/ghais/poker

The reason for excluding a 7-card evaluator is threefold - I have no imminent need for it (yet), I want to do so but haven't done it, and I'm hoping to accommodate ghais' work here: https://github.com/ghais/poker. I'm not sure whether he's active though, since it's been a couple of weeks since I posted an issue. If you have work you'd like to include please ping me, or we can discuss what architectural work would be required. I do, however, think that a 7-card evaluator might be best kept as a separate package. One reason is because the naming for an evaluator might heavily conflict with other applications. On the other hand, it would be easier to maintain in a single library - I'm very open to the discussion.

It was actually invented for this.

Open source radiation transport Monte Carlo code here if you'd like to play around:

https://github.com/openmc-dev/openmc

Even given their nuclear weapons origin, we lowly civil nuclear power engineers still use Monte Carlo methods all day every day. We all make our employers buy big supercomputers or get us access to the national lab leadership class HPC to just pound the hell out of our reactor design problems with random particle transport chains. Sure there are (dramatically) faster deterministic methods that are generally good enough, but Monte Carlo allows you to use exact geometry and not bother too much with the pesky art of computing average nuclear interaction probabilities.

Heck, my buddy at MIT made an open-source Monte Carlo code called OpenMC that's now run by Argonne National Lab [1]. Now everyone can do truly legit reactor design with Monte Carlo!

[1] https://github.com/openmc-dev/openmc

openmc source code