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SciML / NonlinearSolve.jl

High-performance and differentiation-enabled nonlinear solvers (Newton methods), bracketed rootfinding (bisection, Falsi), with sparsity and Newton-Krylov support.
https://docs.sciml.ai/NonlinearSolve/stable/
MIT License
221 stars 39 forks source link

make RobustMultiNewton always respect autodiff choice #347

Closed oscardssmith closed 6 months ago

oscardssmith commented 6 months ago

This probably needs a test, but the TLDR is that it fixes use of RobustMultiNewton with autodiff incompatible functions. Before TrustRegion(; concrete_jac, linsolve, precs) would mean that it would throw duals at the problem even if you specified autodiff=AutoFiniteDiff()

codecov[bot] commented 6 months ago

Codecov Report

Attention: 1 lines in your changes are missing coverage. Please review.

Comparison is base (d47b131) 88.06% compared to head (8614ebe) 83.79%.

Files Patch % Lines
src/default.jl 0.00% 1 Missing :warning:
Additional details and impacted files ```diff @@ Coverage Diff @@ ## master #347 +/- ## ========================================== - Coverage 88.06% 83.79% -4.27% ========================================== Files 28 28 Lines 2178 2179 +1 ========================================== - Hits 1918 1826 -92 - Misses 260 353 +93 ```

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avik-pal commented 6 months ago

@oscardssmith can you rerun the formatter once?

ChrisRackauckas commented 6 months ago

And add a test

oscardssmith commented 6 months ago

Formatted and tests added.