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

aaply {plyr}

R Documentation

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

Description

For each slice of an array, apply function, keeping results as an array. 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).

Usage

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

Arguments

`.fun`	function to apply to each piece
`...`	other arguments passed on to `.fun`
`.progress`	name of the progress bar to use, see `create_progress_bar`
`.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
`.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
`.parallel`	if `TRUE`, apply function in parallel, using parallel backend provided by foreach dimension for each variable.
`.drop`	should extra dimensions of length 1 in the output be dropped, simplifying the output. Defaults to `TRUE`

Value

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

Input

This function splits matrices, arrays and data frames by dimensions

Output

If there are no results, then this function will return a vector of length 0 (vector()).

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)

[Package plyr version 1.7.1 Index]