Allow n-dimensional arrays into polygonize in DD #253
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rafaqz
reviewed
Jan 25, 2025
| else | ||
| map(eachslice(A; dims = DD.otherdims(A, dims))) do a | ||
| ap = PermutedDimsArray(a, dims) | ||
| GO.polygonize(bounds_vecs..., a; crs, kw...) |
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Can we just pass through the dims kw instead of permuting?
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The x and y dims need to be in the same order as the lookups though, so I'm not sure how we'd do this...
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Doesn't it already fix that with dims ordering? It probably should...
Maybe it's counter intuitive but reordering dims in the inner loop is essentially free, so usually faster than array wrappers that have a runtime Indirection
(Ohh right it's not a DD alg internally so it has to be slow... unfortunate why would I write something like that 😭)
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This allows polygonize over an n-dimensional datacube to generate an n-2 dimensional datacube of geometries / featurecollections...kind of like R style vector data cubes.
Maybe we should allow the values to be unpacked into an n-1th dimension so we can unpack the polygons too.
This is particularly useful when polygonizing datacubes.