Andrew Nelson

Faster cumulative summation would be really, really, useful as well.

> `return -0.5*model.getChiSquare(), B8Flux*model.getProb(0), B8Flux*model.getProb(1), B8Flux*model.getProb(2), B8Flux*(model.getProb(1)+model.getProb(2))` This is an issue with your log-posterior. The line above should be returning a single value, not a tuple.

This is not an issue with emcee as it doesn't take over responsibility for the pool. The correct way to do this is wrapping in a context manager to make...

Have you tried the example from the emcee documentation? That works for me, both on a cluster and locally. If it doesn't work then I suspect it's going to be...

*Speeding up emcee* doesn't really seem like the right phrase to use here, given that the rate limiting step seems to be your log-posterior function. You may have already followed...

What I'm mainly concerned about is the following: - will `ptemcee`retain the same call signatures/internals as `emcee.ptsampler`? I'd like my code to be able to cope with both alternatives without...

I've just been investigating the constructor for `emcee.PTSampler` and `ptemcee.sampler.Sampler`, the signatures differ. In the former `ntemps` is the first positional argument. In the latter it's a kwd argument. This...

It's good to know the history. As an OSD I know the effort that goes into maintaining packages, in addition to doing the day job, so thank you. The transition...

No worries. The rationale for using PTSampler was that it's able to sample multimodal distributions. Do you have any pointers for how much better PTSampler is than bog-standard emcee for...

I'm happy to help with any PRs. What helps these projects helps mine. On 20 Oct 2017 9:24 am, "Will Vousden" wrote: > As for the efficacy of parallel tempering...