Comments (3)
Materializing the transpose is likely much better for performance since that keeps the coordinates of a point close in memory.
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See #13, there was some work towards it at #14.
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@KristofferC
Oh, i see. and for the same reason the package does not work with sparse arrays?
By the way, KDTree is not working with array of int-s also. Is it intentional?
from nearestneighbors.jl.
Related Issues (20)
- Querying a vector of NaN occasionally results in invalid indices HOT 5
- Bug: BoundsError when skipping all entries HOT 1
- periodic kdtree or balltree HOT 5
- Benchmarking parallel implementation leads to segfaults HOT 2
- No constructor for NNTree HOT 2
- Nearest Neighbors in a very large dataset. HOT 1
- mutual nearest neighbors HOT 3
- [FR] Classifier function
- BallTree and KDTree do not accept Vector{AbstractVector{Float64}} Type. Possible bug. HOT 1
- knn: skipped items output when there is a skip function has always the last index and not 0 index HOT 3
- `nn` lacking docstring HOT 1
- AssertionError in kmedoids alg
- bug: BoundsError when the skip function returns true for all points HOT 3
- Is there a reason sqeuclidean distance is not supported? HOT 4
- README.md Misleading Custom Metric Documentation
- Document that `inrangecount` also counts the point itself HOT 2
- [Question] Can you insert new data into an existing KDTree object? HOT 2
- Compilation time issues with very high dimensions HOT 3
- Reverse Cuthill-McKee ordering option HOT 1
- Querying number of distance evaluations HOT 2
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from nearestneighbors.jl.