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Document sortres optional argument to knn, knn! #220

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a5f1672
Document `sortres` optional argument
cgarling Aug 23, 2025
62d1abd
document sortres option
cgarling Aug 23, 2025
5438150
fix formatting
cgarling Aug 23, 2025
65fc137
fix formatting
cgarling Aug 23, 2025
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5 changes: 3 additions & 2 deletions README.md
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Original file line number Diff line number Diff line change
Expand Up @@ -66,13 +66,14 @@ kdtree_seq = KDTree(data; parallel=false)
A kNN search finds the `k` nearest neighbors to a given point or points. This is done with the methods:

```julia
knn(tree, point[s], k [, skip=always_false]) -> idxs, dists
knn!(idxs, dists, tree, point, k [, skip=always_false])
knn(tree, point[s], k [, sortres=false, skip=always_false]) -> idxs, dists
knn!(idxs, dists, tree, point, k [, sortres=false, skip=always_false])
```

* `tree`: The tree instance.
* `point[s]`: A vector or matrix of points to find the `k` nearest neighbors for. A vector of numbers represents a single point; a matrix means the `k` nearest neighbors for each point (column) will be computed. `points` can also be a vector of vectors.
* `k`: Number of nearest neighbors to find.
* `sortres`: Whether to sort the returned values by their `distances` (`true`) or not (default: `false`).
* `skip` (optional): A predicate function to skip certain points, e.g., points already visited.


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6 changes: 4 additions & 2 deletions src/knn.jl
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Expand Up @@ -5,7 +5,7 @@ function check_k(tree, k)
end

"""
knn(tree::NNTree, points, k [, skip=always_false]) -> indices, distances
knn(tree::NNTree, points, k [, sortres=false, skip=always_false]) -> indices, distances

Performs a lookup of the `k` nearest neighbors to the `points` from the data
in the `tree`.
Expand All @@ -14,6 +14,7 @@ in the `tree`.
- `tree`: The tree instance
- `points`: Query point(s) - can be a vector (single point), matrix (multiple points), or vector of vectors
- `k`: Number of nearest neighbors to find
- `sortres`: Whether to sort the returned values by their `distances` (`true`) or not (default: `false`)
- `skip`: Optional predicate function to skip points based on their index (default: `always_false`)

# Returns
Expand Down Expand Up @@ -53,7 +54,7 @@ function knn_point!(tree::NNTree{V}, point::AbstractVector{T}, sortres, dist, id
end

"""
knn!(idxs, dists, tree, point, k [, skip=always_false])
knn!(idxs, dists, tree, point, k [, sortres=false, skip=always_false])

Same functionality as `knn` but stores the results in the input vectors `idxs` and `dists`.
Useful to avoid allocations or specify the element type of the output vectors.
Expand All @@ -64,6 +65,7 @@ Useful to avoid allocations or specify the element type of the output vectors.
- `tree`: The tree instance
- `point`: Query point
- `k`: Number of nearest neighbors to find
- `sortres`: Whether to sort the returned values by their `distances` (`true`) or not (default: `false`)
- `skip`: Optional predicate function to skip points based on their index (default: `always_false`)

See also: `knn`, `nn`.
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