sweep: Sweep out Array Summaries
In robertzk/monadicbase: The R Base Package

Description Usage Arguments Details Value References See Also Examples

Return an array obtained from an input array by sweeping out a summary statistic.

1	sweep(x, MARGIN, STATS, FUN = "-", check.margin = TRUE, ...)

`x`	an array.
`MARGIN`	a vector of indices giving the extent(s) of `x` which correspond to `STATS`.
`STATS`	the summary statistic which is to be swept out.
`FUN`	the function to be used to carry out the sweep.
`check.margin`	logical. If `TRUE` (the default), warn if the length or dimensions of `STATS` do not match the specified dimensions of `x`. Set to `FALSE` for a small speed gain when you know that dimensions match.
`...`	optional arguments to `FUN`.

FUN is found by a call to match.fun. As in the default, binary operators can be supplied if quoted or backquoted.

FUN should be a function of two arguments: it will be called with arguments x and an array of the same dimensions generated from STATS by aperm.

The consistency check among STATS, MARGIN and x is stricter if STATS is an array than if it is a vector. In the vector case, some kinds of recycling are allowed without a warning. Use sweep(x, MARGIN, as.array(STATS)) if STATS is a vector and you want to be warned if any recycling occurs.

An array with the same shape as x, but with the summary statistics swept out.

Becker, R. A., Chambers, J. M. and Wilks, A. R. (1988) The New S Language. Wadsworth & Brooks/Cole.

apply on which sweep used to be based; scale for centering and scaling.

require(stats) # for median
med.att <- apply(attitude, 2, median)
sweep(data.matrix(attitude), 2, med.att)  # subtract the column medians

## More sweeping:
A <- array(1:24, dim = 4:2)

## no warnings in normal use
sweep(A, 1, 5)
(A.min <- apply(A, 1, min))  # == 1:4
sweep(A, 1, A.min)
sweep(A, 1:2, apply(A, 1:2, median))

## warnings when mismatch
sweep(A, 1, 1:3)  # STATS does not recycle
sweep(A, 1, 6:1)  # STATS is longer

## exact recycling:
sweep(A, 1, 1:2)  # no warning
sweep(A, 1, as.array(1:2))  # warning