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Motivated by https://github.com/AMICI-dev/AMICI/issues/1230
Should be done for both forward and adjoint sensitivities (#18).
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so far we only allow for uniform, however, we should in my opinion distinguish between uniform and logUniform. in most cases we use actually log-uniform as we consider a uniform distribution on log sc…
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`AggregatedObjective` calls `call_unprocessed`, not `__call__`, so then handling via `__call__` introduced in #835 doesn't have any effect and rdata will not be fully populated.
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AMICI uses SymPy for symbolic computation and mathematical formulas from SBML files are converted to strings and loaded with `sympy.sympify`. This function does not produce a faithful representation o…
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Currently, there are way too many warnings issued in the test suite:
base: 570 warnings
optimize: 53 warnings
hierarchical: 27 warnings
select: 205 warnings
petab: 40 warnings
Some are from …
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Example failure
https://github.com/PEtab-dev/PEtab/runs/1622376739#step:6:63
Tries to access this file
https://raw.githubusercontent.com/PEtab-dev/petab_test_suite/master/cases/0001/_0001.yaml
…
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Looking at the Chen_MSB2009 benchmark model, I suspect I may have identified some errors in the measurements table (https://github.com/Benchmarking-Initiative/Benchmark-Models-PEtab/blob/master/Benchm…
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It would be good to be able to include constraints on functions of parameters.
e.g ```par1 = par2 + par3``` where only ```par2``` and ```par3``` are to be estimated but bounds on ```par1``` are avail…
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When importing a PEtab problem, I would expect that the resulting objective on has the estimated parameters as parameters.
However, currently it has all (instead of `petab_problem.x_free_ids`):
http…
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Hi! I'm Jakob, a chemistry collaborator of Torkel's, and I was trying to see if I could figure out a way to utilize the Bayesian Inference implemented in PEtab for Catalyst (I really like the combinat…