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
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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:
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[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?