Usage
a_ply(.data, .margins, .fun = NULL, ..., .expand = TRUE,
.progress = "none", .inform = FALSE, .print = FALSE,
.parallel = FALSE, .paropts = NULL)
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.
.inform
produce informative error messages? This is turned off
by default because it substantially slows processing speed, but is very
useful for debugging
.print
automatically print each result? (default: FALSE
)
.parallel
if TRUE
, apply function in parallel, using parallel
backend provided by foreach
.paropts
a list of additional options passed into
the foreach
function when parallel computation
is enabled. This is important if (for example) your code relies on
external data or packages: use the .e