Convert the orient predicate to AdaptivePredicates + minor predicate changes #275
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This was referenced Mar 4, 2025
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Graphite looks very good, I should start using too. And this looks good to me, accurate is good, we can make it faster later. |
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AdaptivePredicates is at least 10x if not 40x faster than exact predicates :D |
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Yeah, I'm referring to the missing fast returns |
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This was factored out of the "dev branch" #259 and contains the subset of changes that apply to GeometryOpsCore, for easier review. Child PRs: #271 (TGGeometry) -> #275 (AdaptivePredicates) -> #273 (clipping algorithm type) -> #274 (trees) - Use [StableTasks.jl](https://github.com/JuliaFolds2/StableTasks.jl) in apply and applyreduce - its type-stable tasks save us some allocations! - Remove `Base.@assume_effects` on the low level functions, which caused issues on Julia v1.11 and was probably incorrect anyway - Add an algorithm interface with an abstract supertype `Algorithm{M <: Manifold}`, as discussed in #247. Also adds an abstract Operator supertype and some discussion in code comments, but no implementation or interface surface there yet. - Split out `types.jl` into a directory `types` with a bunch of files in it, for ease of readability / docs / use. - (out of context change): refactor CI a bit for cleanliness. TODOs for later (not this PR): - [ ] Add a `format` method that takes in an incompletely specified algorithm and some geometry as input, and returns a completely specified algorithm. What does this mean? Imagine I call `GO.intersection(FosterHormannClipping(), geom1, geom2)`. That `FosterHormannClipping()` should get expanded to `FosterHormannClipping(AutoAlgorithm(), AutoAccelerator())`. Then, `format` will take `format(alg, args...)` and: - get the `crstrait` of the two geometries, scan for incompatibilities, assign the correct manifold to the algorithm (maybe warn or emit debug info) - if no geometries available, get the manifold via `best_manifold(::Algorithm)`. - maybe inflate the accelerator by checking `npoint` and later preparations to see what's most efficient, maybe not - depends on what we want!
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https://github.com/JuliaGeometry/AdaptivePredicates.jl is a library that implements adaptive predicates - substantially faster, BUT harder to construct, than exact predicates. Adaptive predicates are valid through the range of coordinates that geometries usually have, but we may need exact predicates if they are not.
This should increase speed although we will have to benchmark. Still, at least it's benchmarkable now.
Only one of the geoms in g2 MUST touch the geom in g1, all others MUST be disjoint or touching. This could potentially be accelerated by building an STRtree if the query width is long enough, or we may also need some tree interface / preparation here. E.g. Canada has a lot of islands that a tree approach could get rid of.
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Spun out from #259
Replaces #272 (which was a bad branch name)
Parent: #271 (TG geometry and algorithm implementations for GEOS and PROJ)
Children: #273 (clipping changes and passthrough) -> #274 (trees)
https://github.com/JuliaGeometry/AdaptivePredicates.jl is a library that implements adaptive predicates - substantially faster, BUT harder to construct, than exact predicates. Adaptive predicates are valid through the range of coordinates that geometries usually have, but we may need exact predicates if they are not.