Dilan Pathirana

> > The model doesn't appear to unscale the parameter, so estimating in `[-5, 3]` is incorrect, and instead should be `[0.00001, 1000]`. > > I see what you mean....

> I do however see the issue that this causes trouble when for example trying to run model selection where some parameters are fixed/unfixed. I would say the best way...

> Could you briefly describe the changes you made to the original parameters file? I see that some fixed parameters are now missing. Briefly: the missing parameters were always "off"...

> Amici regression tests for this problem are failing following this merge: https://github.com/AMICI-dev/AMICI/actions/runs/11797774460/job/32862480540?pr=2584 > > ``` > FAILED test_petab_benchmark.py::test_nominal_parameters_llh[Isensee_JCB2018] - Failed: Computed llh -6.5484e+03 does not match reference -3.9494e+03. Absolute...

> Can this be merged/consolidated with issue #156? Yes, thanks for the contributions from everyone so far

The suggestion for the reinitialization looks good to me. I could separate step 2 into "petab changes" and "model changes", if you agree. Here's a suggestion, that also includes some...

Thanks for the quick feedback. I changed the first post to address some of it. @m-philipps > It should also be trivial to create the conditions table in wide format...

@paulflang > putting rows with different meaning in the same table should be avoided To me, the rows do not have a different meaning. Every row describes the (piecewise-)constant input...

> Then you can just go with object-relational mapping (table=class, column=class attribute, row=instance) to represent everything in (Python) objects. Also not an expert, but I think this is already supported....

> > Thanks for the quick feedback. I changed the first post to address some of it. > > Thanks for bringing up this discussion. For some joining in late...