Cleanup for docs and tests #86
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This looks all good to me, small comment on the |
TorkelE
reviewed
Oct 30, 2025
| function loss(ps, (oprob_base, set_ps, sample_t, sample_X, sample_Y)) | ||
| p = set_ps(oprob_base, ps) | ||
| new_oprob = remake(oprob_base; p) | ||
| new_osol = solve(new_oprob, Tsit5(); saveat = sample_t, verbose = false, maxiters = 10000) |
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see comment, but if you prefer not to have too many arguments than all good
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Needs to fix the test deps |
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There were some things in the docs that I would not necessarily recommend, like
θ...for the parameters of a neural network, which for larger neural networks could explode in compile timemaxitersfor the ODE solve is not need here and it could be a hindrance in some cases as the NN parameters that need large maxiters would lead to a wrong model anywayModelingToolkit.setp_oop, since the function is from SIII've also added the suggestion on how to access the values of the neural network with
oprob_fitted.ps[sym_nn](y, oprob_fitted.ps[θ])[1], which would be even shorter if youroprob_fittedvariable name was shorter 😅This is also what I recommend in the NN block tutorial.
Other than that I cleaned up the tests a bit and consolidated the reported issues under a singe testset.