Jonas Arruda
Jonas Arruda
I just rerun the notebook and pushed it again. At least I can view it with the GitHub renderer
I reverted the inital fix since I found a better solution. If you now call `problem.x_priors` it behaves exactly as `problem.objective`, which is the behaviour I would expect (wrt fixed...
After discussion, @PaulJonasJost and I removed the deepcopy of the `NegLogParameterPriors` class. Otherwise, copying the prior does not work. This happens in the parallel tempering sampler, when the prior is...
Actually, the dynesty sampler already allows to do both
True, this is not neceassary as a test. It was included to check convergence of the evidence estimation. Okay for me to remove it to speed up testing time.
I agree, same here! #6 seems related
Is the spline mapping saved somewhere? In other words, if I load a result and create the same petab problem, will I get the same results? I noticed that for...
maybe @dweindl can help here?
> I would rather handle `AggregatedObjective` separately in the visualization code instead of adding `amici_model` to `AggregatedObjective`, since there will probably be multiple models. Okay, I thought that `AggregatedObjective` is...
> @arrjon can this be closed with the merge of #1411? Regarding visualisation the bug is fixed. However, `pypesto_problem.objective(x, return_dict=True)` does still return empty `rdatas` when using an aggregated objective,...