find_box: Box Numbers (Multivariate) Points Fall Into

In gnn: Generative Neural Networks

Box Numbers (Multivariate) Points Fall Into

Description

Finding the numbers of boxes that given (multivariate) points fall into (the default is similar to findInterval() but other methods are provided, too).

Usage

find_box(x, endpoints = NULL,
         method = c("per.dim", "lexicographic", "nested", "diagonal"),
         rightmost.closed = TRUE, left.open = TRUE, ...)

Arguments

x	(n, d)-matrix containing n d-dimensional data points, n \ge 1, d \ge 1.
endpoints	d-list containing numeric vectors of endpoints of the intervals in each dimension (each of the d elements is an argument vec as required by findInterval()).
method	character string indicating the method to be used. Available are: "per.dim" the default. Each row x[i,] of x produces d numbers, where the jth indicates in which interval x[i,j] falls. This is essentially findInterval() applied to the d coordinate samples (the columns of x). "lexicographic" Each row x[i,] produces one number, indicating in which box x[i,] falls if all nonempty boxes are numbered consecutively in lexicographic order. "nested" Each row x[i,] produces one number, indicating in which box x[i,] falls along the d-dimensional diagonal in a nested way, with a non-nested middle part if the number of interval endpoints per dimension is even (note that this method requires all elements of endpoints to have the same length, so that the diagonal is well-defined). "diagonal" Each row x[i,] produces one number, indicating in which box x[i,] falls along the d-dimensional diagonal (note that this method requires all elements of endpoints to have the same length, so that the diagonal is well-defined).
rightmost.closed	see findInterval() (note the different default here).
left.open	see findInterval() (note the different default here).
...	additional arguments passed to the underlying findInterval().

Details

The box numbers can be used, for example, to color points; see the examples below.

Value

"per.dim"

(n,d)-matrix of box numbers per dimension.

"lexicographic", "nested", "diagonal"

n-vector with box numbers.

Note that, as findInterval(), 0 means ‘in no box’.

Author(s)

Marius Hofert

Examples

## Example data
n <- 1000
d <- 2
set.seed(271)
U <- matrix(runif(n * d), ncol = d) # (n, d)-matrix of data (here: in [0,1]^d)


### 1 Basic example calls ######################################################

## Define endpoints and evaluate for different methods
epts <- seq(0, 1, by = 1/5) # 5 boxes per dimension
find_box(U, endpoints = epts)[1:10,] # default "per.dim" (first 10 points only)
boxes.lexi <- find_box(U, endpoints = epts, method = "lexicographic")
boxes.nest <- find_box(U, endpoints = epts, method = "nested")
boxes.diag <- find_box(U, endpoints = epts, method = "diagonal")

## Special cases
## First row of U (n = 1)
U[1,] # ~= (0.25, 0.14)
stopifnot(find_box(U[1, 1:2], endpoints = epts) == c(2, 1))
stopifnot(find_box(U[1, 1:2], endpoints = epts, method = "lexicographic") == 1)
## Note concerning the last line: It's 1 because all other boxes are empty
stopifnot(find_box(U[1, 1:2], endpoints = epts, method = "nested") == 2)
stopifnot(find_box(U[1, 1:2], endpoints = epts, method = "diagonal") == 0)
## Single number U[1,1] (d = 1)
U[1,1] # ~= 0.25
stopifnot(find_box(U[1,1], endpoints = epts) == 2)
stopifnot(find_box(U[1,1], endpoints = epts, method = "lexicographic") == 1)
stopifnot(find_box(U[1,1], endpoints = epts, method = "nested") == 2)
stopifnot(find_box(U[1,1], endpoints = epts, method = "diagonal") == 2)


### 2 Coloring points in lexicographic ordering ################################

## Define color palette
library(RColorBrewer)
basecols <- c("#000000", brewer.pal(8, name = "Dark2")[c(8,7,3,1,5,4,2,6)])
mypal <- function(n) rep_len(basecols, length.out = n)

## Colors
ncols <- diff(range(boxes.lexi)) + 1 # maximal number of colors needed
palette(mypal(ncols)) # set palette according to maximum number of colors needed


## Boxes of equal size
boxes.lexi <- find_box(U, endpoints = epts, method = "lexicographic")
cols <- if(min(boxes.lexi) == 0) boxes.lexi + 1 else boxes.lexi
plot(U, pch = 20, xlab = expression(U[1]), ylab = expression(U[2]), col = cols)
abline(v = epts, h = epts, col = "gray50") # guides

## Boxes of different sizes and numbers
epts. <- list(seq(0.2, 1, by = 1/5), seq(1/3, 1, by = 1/3))
boxes.lexi <- find_box(U, endpoints = epts., method = "lexicographic")
cols <- if(min(boxes.lexi) == 0) boxes.lexi + 1 else boxes.lexi
plot(U, pch = 20, xlab = expression(U[1]), ylab = expression(U[2]), col = cols)
abline(v = epts.[[1]], h = epts.[[2]], col = "gray50")


### 3 Coloring points along the diagonal in a nested way #######################

## Boxes of equal size (with 'middle' part)
boxes.nest <- find_box(U, endpoints = epts, method = "nested")
cols <- if(min(boxes.nest) == 0) boxes.nest + 1 else boxes.nest # color numbers
plot(U, pch = 20, xlab = expression(U[1]), ylab = expression(U[2]), col = cols)
abline(v = epts, h = epts, col = "gray50") # guides

## Boxes of different sizes (without 'middle' part; have to be the same number of
## boxes per dimension, otherwise there is no obvious 'diagonal')
epts. <- lapply(1:d, function(j) c(0, 0.1, 0.3, 0.6, 1)) # 4 boxes per dimension
boxes.nest <- find_box(U, endpoints = epts., method = "nested")
cols <- if(min(boxes.nest) == 0) boxes.nest + 1 else boxes.nest # color numbers
plot(U, pch = 20, xlab = expression(U[1]), ylab = expression(U[2]), col = cols)
abline(v = epts.[[1]], h = epts.[[2]], col = "gray50") # guides


### 4 Coloring points along the diagonal #######################################

## Boxes of equal size
boxes.diag <- find_box(U, endpoints = epts, method = "diagonal")
cols <- if(min(boxes.diag) == 0) boxes.diag + 1 else boxes.diag # color numbers
plot(U, pch = 20, xlab = expression(U[1]), ylab = expression(U[2]), col = cols)
abline(v = epts, h = epts, col = "gray50") # guides

## Boxes of different sizes (have to be the same number of
## boxes per dimension, otherwise there is no obvious 'diagonal')
epts. <- lapply(1:d, function(j) c(0, 0.05, 0.1, 0.3, 0.6, 1))
boxes.diag <- find_box(U, endpoints = epts., method = "diagonal")
cols <- if(min(boxes.diag) == 0) boxes.diag + 1 else boxes.diag # color numbers
plot(U, pch = 20, xlab = expression(U[1]), ylab = expression(U[2]), col = cols)
abline(v = epts.[[1]], h = epts.[[2]], col = "gray50") # guides

gnn documentation built on May 29, 2024, 6:13 a.m.