Combine powers with PYMC 3?

[datnamer]

Both Emcee and PYMC are amazing packages with differing but somewhat overlapping utility.

Any thought of combining the two, ala: http://twiecki.github.io/blog/2013/09/23/emcee-pymc/

Would provide great synergy for bayesian analysis in python while reducing package fragmentation and perhaps be a boon to both packages.

[bobcolner]

+10,000

As a bayesian noob the pymc API is much more approachable. It would be a huge win to embed the emcee sampler in PyMC!

[twiecki]

+1 :)

[dfm]

Oh hai @twiecki... weren't you going to do that?? ;-)

[twiecki]

Well, I sorta already did ;). I'd be happy to help but probably more advising than taking the lead. I don't think it should be too hard. Mainly we need something with the same interface as the ArrayStep: https://github.com/pymc-devs/pymc/blob/master/pymc/step_methods/arraystep.py#L13

Someone interested?

[twiecki]

Do moves have to be proposed serially or can that part be parallelized? If I remember correctly it's serial (but groups of walkers can be split up).

[ipashchenko]

One half of walkers propose positions for other half using it's parameters and parameters of the others + some random numbers (from some specified distribution). That's the idea i suppose:)

[twiecki]

Ah, neat. So this could be sped up significantly by testing the proposals on the GPU (which pymc3 supports).

[ipashchenko]

I think the most heavy part it the lnprob (posterior) calculation for each walker - that is where GPU could greatly help. Now, EnsembleSampler has interface - pool object that is passed to it's constructor. It can be any object with a map method that follows the same calling sequence as the built-in map function (from docs). Proposal calculation itself is fast thanks to numpy.

[twiecki]

FYI: pymc-devs/pymc#1689

[dfm]

Thanks @twiecki