k-nearest neighbors search for RBush. Implements a simple depth-first kNN search algorithm using a priority queue.
import RBush from 'rbush';
import knn from 'rbush-knn';
const tree = new RBush(); // create RBush tree
tree.load(data); // bulk insert
const 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:
const neighbors = knn(tree, 40, 40, 10, function (item) {
return item.foo === 'bar';
});
knn(tree, x, y, [k, filterFn, maxDistance])
tree: an RBush treex, y: query coordinatesk: 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)JavaScript
100.0%
k-nearest neighbors search for RBush. Implements a simple depth-first kNN search algorithm using a priority queue.
import RBush from 'rbush';
import knn from 'rbush-knn';
const tree = new RBush(); // create RBush tree
tree.load(data); // bulk insert
const 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:
const neighbors = knn(tree, 40, 40, 10, function (item) {
return item.foo === 'bar';
});
knn(tree, x, y, [k, filterFn, maxDistance])
tree: an RBush treex, y: query coordinatesk: 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)JavaScript
100.0%