RigidBodyDynamics.jl v2.5.0#646
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rdeits merged 4 commits intoJuliaRobotics:masterfrom Nov 8, 2024
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- Update GitHub CI workflow and .gitignore - Update Manifest.toml of all examples - Remove examples/Manifest.toml - Test notebooks only on Julia 1.9 (temporary)
This PR is mostly a FYI regarding JuliaArrays/StaticArrays.jl#913 Depending on whether or not that issue is closed, you may want to switch to explicitly calling `generic_norm2` on static vectors to circumvent the accuracy issue. The issue arises when combining static arrays with ForwardDiff, in our case it occured in `exp(::SkewSymmetric)`. I did some benchmarking, and `generic_norm2` is faster than `norm` for all standard arrays up to at least length 9. For static arrays, it appears to do okay as well, while avoiding the accuracy issue. ```julia julia> a 3-element SVector{3, Int64} with indices SOneTo(3): 1 2 3 julia> @Btime norm($(Ref(a))[]) # standard norm of static array 5.135 ns (0 allocations: 0 bytes) 3.74166 julia> @Btime norm($(Ref(Vector(a)))[]) # standard norm of array 8.545 ns (0 allocations: 0 bytes) 3.74166 julia> @Btime LinearAlgebra.generic_norm2($(Ref((a)))[]) # generic_norm2 of static array 4.490 ns (0 allocations: 0 bytes) 3.74166 julia> @Btime LinearAlgebra.generic_norm2($(Ref(Vector(a)))[]) # generic_norm2 of array 7.671 ns (0 allocations: 0 bytes) 3.74166 ```
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@rdeits I can't edit the list of reviewers, so I'm tagging you in this comment instead. 😛 |
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Thanks for putting this all together! I think we may be able to revert back to |
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You are right. I have opened #647 to revert this. |
This was referenced Nov 8, 2024
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This is my proposal for RigidBodyDynamics.jl 2.5.0.
Summary of changes
.gitignorefilesexamples/examples/Manifest.tomlWrenchesCacheIssues and PRs that can be closed after this is merged
WrenchesCache#616