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.
Usage
aaply(
.data,
.margins,
.fun = NULL,
...,
.expand = TRUE,
.progress = "none",
.inform = FALSE,
.drop = TRUE,
.parallel = FALSE,
.paropts = NULL
)
Arguments
.data |
matrix, array or data frame to be processed |
.margins |
a vector giving the subscripts to split up |
.fun |
function to apply to each piece |
... |
other arguments passed on to |
.expand |
if |
.progress |
name of the progress bar to use, see
|
.inform |
produce informative error messages? This is turned off by default because it substantially slows processing speed, but is very useful for debugging |
.drop |
should extra dimensions of length 1 in the output be
dropped, simplifying the output. Defaults to |
.parallel |
if |
.paropts |
a list of additional options passed into
the |
Details
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
aaply(input, X, identity)
is equivalent to aperm(input, X)
.
Value
if results are atomic with same type and dimensionality, a vector, matrix or array; otherwise, a list-array (a list with dimensions)
Warning
Contrary to alply
and adply
, passing a data
frame as first argument to aaply
may lead to unexpected results
such as huge memory allocations.
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. https://www.jstatsoft.org/v40/i01/.
See Also
Other array input:
a_ply()
,
adply()
,
alply()
Other array output:
daply()
,
laply()
,
maply()
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)