Cobaya: Issue with measuring speeds when derived parameters added
Posted: August 19 2020
Hello,
I am having some trouble with cobaya's automatic determination of the oversampling power.
I have added a derived parameter by modifying the logp method of the likelihood I am using (sigma12, by adding the line), which seems to cause cobaya to get stuck at "Measuring speeds" stage of the run, regardless of the sampler used. However, manually passing the oversampling powers or running "evaluate" dummy sampler works fine.
When looking at the debug file, it seems like the issue is an error when computing a new state that results in zero likelihood value:
I suppose the issue is with the params_values dictionary at this stage, but I am not sure how to solve this.
Of course, one can avoid the issue by setting the oversampling manually, but I was wondering if there is a way to make this work?
I am having some trouble with cobaya's automatic determination of the oversampling power.
I have added a derived parameter by modifying the logp method of the likelihood I am using (sigma12, by adding the line
Code: Select all
params_values["_derived"]["sigma12"] = sigma12
When looking at the debug file, it seems like the issue is an error when computing a new state that results in zero likelihood value:
Code: Select all
[des_y1.clustering_copy] Ignored error at evaluation and assigned 0 likelihood (set 'stop_at_error: True' as an option for this component to stop here). Error message: TypeError("'NoneType' object does not support item assignment",)
Of course, one can avoid the issue by setting the oversampling manually, but I was wondering if there is a way to make this work?