fix: improve resolution of dependent parameter defaults

SciML / ModelingToolkit.jl

An acausal modeling framework for automatically parallelized scientific machine learning (SciML) in Julia. A computer algebra system for integrated symbolics for physics-informed machine learning and automated transformations of differential equations

https://mtk.sciml.ai/dev/

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fix: improve resolution of dependent parameter defaults #3005

Closed AayushSabharwal closed 2 months ago

AayushSabharwal commented 2 months ago

Close #2997

Checklist

[ ] Appropriate tests were added
[ ] Any code changes were done in a way that does not break public API
[ ] All documentation related to code changes were updated
[ ] The new code follows the contributor guidelines, in particular the SciML Style Guide and COLPRAC.
[ ] Any new documentation only uses public API

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Add any other context about the problem here.

ChrisRackauckas commented 2 months ago

Needs a test.

AayushSabharwal commented 2 months ago

See https://github.com/SciML/ModelingToolkit.jl/issues/2997#issuecomment-2324044823. I'm not sure why this fixes the issue, just that it does. So the only test relies on a specific system with a specific initial value which doesn't seem robust.

ChrisRackauckas commented 2 months ago

Might as well make an integration test of it.

ChrisRackauckas commented 2 months ago

We should split the interface 1 tests so the times are shorter zzzz