k-nearest neighbors search for RBush. Implements a simple depth-first kNN search algorithm using a priority queue.

var rbush = require('rbush');
var knn = require('rbush-knn');

var tree = rbush().load(data); // create an RBush index
var neighbors = knn(tree, 40, 40, 10); // return 10 nearest items around point [40, 40]

You can optionally pass a filter function to find k neighbors that satisfy a certain condition:

var neighbors = knn(tree, 40, 40, 10, function (item) {
    return item.foo === 'bar';
});

knn(tree, x, y, [k, filterFn, maxDistance])

• tree: an RBush tree
• x, y: query coordinates
• k: number of neighbors to search for (Infinity by default)
• filterFn: optional filter function; k nearest items where filterFn(item) === true will be returned.
• maxDistance (optional): maximum distance between neighbors and the query coordinates (Infinity by default)

• Breaking: updated to be compatible with RBush 2.0.
• Breaking: signature changed from tree, [x, y], k, filterFn to tree, x, y, k, filterFn
• Improved performance by ~20%.

• Add an optional filter function argument.

• 2.5x performance improvement!

• Fixed an error when requesting more items than the tree has. #1

• Initial release.