knnLookup: Perform k-Nearest Neighbors Lookup Using a Search Tree

In SearchTrees: Spatial Search Trees

Perform k-Nearest Neighbors Lookup Using a Search Tree

Description

This function performs fast k-Nearest Neighbors lookup on a SearchTree object

Usage

knnLookup(tree, newx, newy, newdat, columns = 1:2, k = 5)

Arguments

tree	An object which inherits from the SearchTree S4 class.
newx	Numeric. Vector of x values for the points to look up neighbors for.
newy	Numeric. Vector of x values for the points to look up neighbors for.
newdat	Matrix or data.frame. Data containing x and y values of the points to look up neighbors for. Ignored if x and y are specified.
columns	Numeric. Columns x and y values can be found in within newdat.
k	Numeric. Number of neighbors to find for each point.

Value

The return value is an integer matrix indicating the indices in the original data used to create treE where the nearest neighbors were found. Row indicates the indice of the new point, while column indicates the order of the k neighbors.

Note

No defined order is specified for exact ties in distance.

Author(s)

Gabriel Becker

See Also

createTree rectLookup

Examples

x = rnorm(100)
y = rnorm(100)
tree = createTree(cbind(x,y))
newx = c(0, .5)
newy = c(.5, 0)
inds = knnLookup(tree, newx, newy, k=7)

ch = rep(1, times=100)
ch[inds[1:7]] = 3
ch[inds[8:14]] = 5
cls = rep("black", times=100)
cls[inds[1:7]] = "red"
cls[inds[8:14]] ="blue"

plot(x,y, pch=ch, col = cls)
abline(v=newx[1], h = newy[1] , col="red")
abline(v=newx[2], h = newy[2], col = "blue")

SearchTrees documentation built on Oct. 4, 2022, 1:06 a.m.