Can't load trace in the simplest case

[jjj]

Thank you very much for your reply.

@OriolAbril

You can’t combine save_trace and to_netcdf.

I wasn’t doing that. Sorry, maybe the commented code was misleading. When using arviz, I would first run the code using to_netcdf (with return_inference_data=True) and then use from_netcdf to read the inference data.

@OriolAbril

InferenceData arguments also can’t be used as trace argument.

I thought old.posterior is an xarray? Do you mean that only MultiTrace can be used as a trace argument to start sampling where the process finished?

@OriolAbril

it is impossible it “starts sampling from where the old trace finished” (unless using a single chain).

That’s exactly my case! I want to use one chain, and start sampling from where I’ve finished. I just can’t figure out how to do it with arviz.

@OriolAbril

You can use arviz.concat — ArviZ dev documentation to combine multiple posterior fits on the same model, either concating on the draw dimension (or probably recommended in this case unless you do have the mass matrix) on the chain dimension. That is, keep your current results, rerun pm.sample on the same model and then use az.concat

Thanks, that’s really helpful but from what I understand arviz.concat returns an InferenceData object. This still makes it impossible to start sampling from where the old trace finished, right? Do you know if this in general impossible with arviz? This is crucial to me, I am fitting a very slow model on a cluster. The model can fail for many reasons and I need to be able to save the sampling “state”.

Update
Ok, I see there exists a solution for a similar problem for pymc4. I’m not sure yet if this would work with pymc3.