buildVptree: Build a VP tree

In BiocNeighbors: Nearest Neighbor Detection for Bioconductor Packages

Description

Build a vantage point tree in preparation for a nearest-neighbors search.

Usage

buildVptree(X, transposed=FALSE, distance=c("Euclidean", "Manhattan"))

Arguments

X	A numeric matrix where rows correspond to data points and columns correspond to variables (i.e., dimensions).
transposed	Logical scalar indicating whether X is transposed, i.e., rows are variables and columns are data points.
distance	String specifying the type of distance to use.

Details

This function is automatically called by findVptree and related functions. However, it can be called directly by the user to save time if multiple queries are to be performed to the same X.

Value

A VptreeIndex object containing:

• data, a numeric matrix with points in the columns and dimensions in the rows, i.e., transposed relative to the input. Points have also been reordered to improve data locality during the nearest-neighbor search.

• nodes, a list containing four vectors of equal length describing the structure of the VP tree. Each parallel element specifies a node.

  • The first integer vector specifies the column index of data of the current node.

  • The second integer vector specifies the column index of the left child of the current node,

  • The third integer vector specifies the column index of the right child of the current node.

  • The fourth numeric vector specifies the radius of the current node.

  All indices here are zero-based, with child values set to -1 for leaf nodes.

• order, an integer vector specifying how rows in X have been reordered in columns of data.

• NAMES, a character vector or NULL equal to rownames(X).

• distance, a string specifying the distance metric used.

Author(s)

Aaron Lun

See Also

See VptreeIndex for details on the output class.

See findVptree and queryVptree for dependent functions.

Examples

Y <- matrix(rnorm(100000), ncol=20)
out <- buildVptree(Y)
out

Example output

class: VptreeIndex
dim: 5000 20
distance: Euclidean

BiocNeighbors documentation built on Dec. 9, 2020, 2:01 a.m.