KDTreeSearcher

Nearest neighbor searcher object.

📝Syntax

Mdl = KDTreeSearcher(X)
Mdl = KDTreeSearcher(X, Name, Value)
[idx, D] = knnsearch(Mdl, Y, Name, Value)
[idx, D] = rangesearch(Mdl, Y, radius, Name, Value)

📥Input Arguments

Parameter	Description
X	the data to search, as a real numeric matrix with one point per row.
Name, Value	options: Distance (default 'euclidean'), P (Minkowski exponent) and BucketSize.

📤Output Arguments

Parameter	Description
Mdl	a KDTreeSearcher object holding the data and the search options.

📄Description

KDTreeSearcher stores a set of points and the distance metric used to query them, so that nearest neighbor searches can be run against the same data with knnsearch and rangesearch. The object exposes the properties X, Distance, DistParameter and BucketSize.

The searches delegate to the knnsearch and rangesearch functions, forwarding the distance metric stored on the object.

💡Examples

X = [0 0; 1 0; 0 2; 4 4];
Mdl = KDTreeSearcher(X);
[idx, D] = knnsearch(Mdl, [0 1; 3 4], 'K', 2)

🔗See Also

knnsearch rangesearch

🕔Version History

Version	Description
2.0.0	initial version

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