InitialAssignment issue about amici

[FFroehlich]

Is it possible this is a typo of Ke_3 vs Ka_3. Hard to say anything else without the full PEtab problem

[aidinbii]

@FFroehlich , unfortunately not

Here are the PEtab tables:

• parameters_modelDef_PK_1C_constr_2.csv
• experimental_conditions_modelDef_PK_1C_constr_2.csv
• measurement_table_PK_1C.csv
• observables_modelDef_PK_1C_constr_2.csv
• problem_PK_1C_constr_2.txt

This is related to ICB-DCM/pyPESTO#1334

[dweindl]

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.

[aidinbii]

@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.

See: ICB-DCM/pyPESTO#1334

[FFroehlich]

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.

[aidinbii]

@FFroehlich, that's what I did before. Actually, this brought me to this InitialAssignment issue

Please, see ICB-DCM/pyPESTO#1334