Comments (3)
That's a good idea!
There used to be a "debug" mode that you could activate that added some stats but it was removed in https://github.com/KristofferC/NearestNeighbors.jl/pull/98/files#diff-3d112593fe19c53f85f19846cc9d0406c17b39736378b65e7d12821d20207302.
With more experienced eyes, I think a better alternative is to allow one to pass something like a
struct EvaluationData
n_distance_evals
n_tree_intersection_evals
...
end
to inrange
and knn
and have that struct be populated. By default that argument would just be nothing
and unused.
from nearestneighbors.jl.
I made a minor modification on my fork to include a global counter:
master...fcdimitr:NearestNeighbors.jl:master
It works correctly, and some preliminary benchmarking shows that it does not affect the running time.
In any case, I agree that a more structured approach to collecting statistics should be preferred.
from nearestneighbors.jl.
Another thing that can be used is GFlops.jl (requires the https://github.com/charleskawczynski/GFlops.jl/tree/ck/julia1.10 branch).
julia> tree = BallTree(rand(3,10^5));
julia> v = rand(3)
3-element Vector{Float64}:
0.38248598898980024
0.6378296367207168
0.9255061078525778
julia> @count_ops knn(tree, v, 4)
Flop Counter: 9124 flop
┌──────┬─────────┐
│ │ Float64 │
├──────┼─────────┤
│ add │ 2184 │
│ sub │ 3300 │
│ mul │ 2912 │
│ sqrt │ 728 │
└──────┴─────────┘
from nearestneighbors.jl.
Related Issues (20)
- 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
- 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 1
- `get_min_distance_sq` seems weird
- Interface for tree traversal / walking of BallTree/KDTree HOT 3
- Trees for integer input data errors now it seems
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from nearestneighbors.jl.