plyr (version 1.5.2)

aaply: Split array, apply function, and return results in an array.

Description

Split array, apply function, and return results in an array. For each slice of an array, apply function then combine results into an array

Usage

aaply(.data, .margins, .fun, ..., .expand=TRUE,
    .progress="none", .drop=TRUE, .parallel=FALSE)

Arguments

.data

matrix, array or data frame to be processed

.margins

a vector giving the subscripts to split up data by. 1 splits up by rows, 2 by columns and c(1,2) by rows and columns, and so on for higher dimensions

.fun

function to apply to each piece

...

other arguments passed on to .fun

.expand

if .data is a data frame, should output be 1d (expand = FALSE), with an element for each row; or nd (expand = TRUE), with a dimension for each variable.

.progress

name of the progress bar to use, see create_progress_bar

.drop

should extra dimensions of length 1 be dropped, simplifying the output. Defaults to TRUE

.parallel

if TRUE, apply function in parallel, using parallel backend provided by foreach

Value

• if results are atomic with same type and dimensionality, a vector, matrix or array; otherwise, a list-array (a list with dimensions)

Details

All plyr functions use the same split-apply-combine strategy: they split the input into simpler pieces, apply .fun to each piece, and then combine the pieces into a single data structure. This function splits matrices, arrays and data frames by dimensions and combines the result into an array. If there are no results, then this function will return a vector of length 0 (vector()).

This function is very similar to apply, except that it will always return an array, and when the function returns >1 d data structures, those dimensions are added on to the highest dimensions, rather than the lowest dimensions. This makes aaply idempotent, so that apply(input, X, identity) is equivalent to aperm(input, X).

References

Hadley Wickham (2011). The Split-Apply-Combine Strategy for Data Analysis. Journal of Statistical Software, 40(1), 1-29. http://www.jstatsoft.org/v40/i01/.

Examples

dim(ozone)
aaply(ozone, 1, mean)
aaply(ozone, 1, mean, .drop = FALSE)
aaply(ozone, 3, mean)
aaply(ozone, c(1,2), mean)

dim(aaply(ozone, c(1,2), mean))
dim(aaply(ozone, c(1,2), mean, .drop = FALSE)) 

aaply(ozone, 1, each(min, max))
aaply(ozone, 3, each(min, max))

standardise <- function(x) (x - min(x)) / (max(x) - min(x))
aaply(ozone, 3, standardise)
aaply(ozone, 1:2, standardise)

aaply(ozone, 1:2, diff)