Open aidinbii opened 2 months ago
Is it possible this is a typo of Ke_3
vs Ka_3
. Hard to say anything else without the full PEtab problem
@FFroehlich , unfortunately not
Here are the PEtab tables:
This is related to https://github.com/ICB-DCM/pyPESTO/issues/1334
I can confirm that overriding some parameter A via the condition table with some parameter B, where B has a parameter-dependent initial assignment is currently not supported in amici. We should either implement that, or produce a more informative error.
@dweindl , thank you, I see. Then there is no way to specify parameter constraints for parameter estimation. For example, if I have a parameter vector: (p1, p2, p3, p4). And I want a constraint: p2 <= p3.
If both parameters are estimated on a log scale, you can reparametrize the problem as p3 =p2 + r
or p3=p2 * r
with r>0 or r>1 respectively.
@FFroehlich, that's what I did before. Actually, this brought me to this InitialAssignment issue
Please, see https://github.com/ICB-DCM/pyPESTO/issues/1334
Hello, there is an issue with InitialAssignment
When I run:
It returns:
The compiled model:
But, if I change the InitialAssignment so that there are no other symbols, for example:
It works without errors and the compiled model adds Ke_3 to Model const parameters
I'm using up-to-date versions of packages
Thank you