Comments (3)
I've seen the source code of knn
, and specifically here the "optimized version":
https://github.com/KristofferC/NearestNeighbors.jl/blob/master/src/knn.jl#L16-L26
Based on this, I wrote up a simple modified loop that goes like this:
function find_all_neighbors(vtree, vs, ns, K, w)
k, sortres, N = maximum(K), true, length(vs)
dists = [Vector{eltype(vs[1])}(undef, k) for _ in 1:N]
idxs = [Vector{Int}(undef, k) for _ in 1:N]
for i in 1:N
# The skip predicate also skips the point itself for w ≥ 0
skip = j -> ns[i] - w ≤ j ≤ ns[i] + w
NearestNeighbors.knn_point!(vtree, vs[i], sortres, dists[i], idxs[i], skip)
end
return idxs
end
I think it makes sense. If anyone confirms that this indeed is the way I should do it, let me know and I can close this!
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Yeah, the skip
function didn't turn out too great (I feel this always happens when you merge something you aren't 100% on heh). Something like what you do there makes sense but it is of course unfortunate that you need to use internal things like knn_point!
.
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It's okay, it's not a big deal. True, I use something internal, but that's the reason that I wanted you to confirm. Since I am not sure about knn_point!
, I wanted the expert to give the a-ok. Now all is good!
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Related Issues (20)
- 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 3
- Make datatypes of the KNN results selectable for potentially lower memory overhead
- Does ball tree work with any metric? HOT 2
- Add example with `skip` option to documentation HOT 1
- Julia 1.10 is waiting on IO to finish during compilation HOT 3
- It should be possible to make `KDNode` smaller
- KDTree: Wrong results for non-Euclidean metrics
- Cannot build KDTree with Subarrays since v0.4.14 HOT 3
- KDTree with Matrix{ComplexF64} HOT 1
- Can't do `knn` on `AbstractVector{SVector}` HOT 2
- Test benchmarks and have them run on CI
- 1.0 road map HOT 5
- `get_min_distance_sq` seems weird
- Interface for tree traversal / walking of BallTree/KDTree HOT 3
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