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jump-dev / JuMP.jl

Modeling language for Mathematical Optimization (linear, mixed-integer, conic, semidefinite, nonlinear)
http://jump.dev/JuMP.jl/
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[docs] clarify section on automatic differentiation in nonlinear.md #3683

Closed odow closed 7 months ago

odow commented 7 months ago

x-ref https://discourse.julialang.org/t/nonlinear-optimization-with-many-constraints-autodifferentiation-which-julia-solution/110678/20

Thoughts @gdalle

Preview: https://jump.dev/JuMP.jl/previews/PR3683/manual/nonlinear/#jump_user_defined_operators

codecov[bot] commented 7 months ago

Codecov Report

All modified and coverable lines are covered by tests :white_check_mark:

Project coverage is 98.33%. Comparing base (4be967c) to head (702a54a).

Additional details and impacted files ```diff @@ Coverage Diff @@ ## master #3683 +/- ## ======================================= Coverage 98.33% 98.33% ======================================= Files 43 43 Lines 5696 5696 ======================================= Hits 5601 5601 Misses 95 95 ```

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odow commented 7 months ago

How about this now. I don't really know where the trade-off is between providing lots of information one the details for expert users, and trying to hide irrelevant information for new users.