How to use the 'sweep' function

This question is a bit old, but since I've recently faced this problem a typical use of sweep can be found in the source code for the stats function cov.wt, used for computing weighted covariance matrices. I'm looking at the code in R 3.0.1. Here sweep is used to subtract out column means before computing the covariance. On line 19 of the code the centering vector is derived:

 center <- if (center) 
        colSums(wt * x)
    else 0

and on line 54 it is swept out of the matrix

x <- sqrt(wt) * sweep(x, 2, center, check.margin = FALSE)

The author of the code is using the default value FUN = "-", which confused me for a while.

sweep() can be great for systematically manipulating a large matrix either column by column, or row by row, as shown below:

> print(size)
     Weight Waist Height
[1,]    130    26    140
[2,]    110    24    155
[3,]    118    25    142
[4,]    112    25    175
[5,]    128    26    170

> sweep(size, 2, c(10, 20, 30), "+")
     Weight Waist Height
[1,]    140    46    170
[2,]    120    44    185
[3,]    128    45    172
[4,]    122    45    205
[5,]    138    46    200

Granted, this example is simple, but changing the STATS and FUN argument, other manipulations are possible.

One use is when you're computing weighted sums for an array. Where rowSums or colSums can be assumed to mean 'weights=1', sweep can be used prior to this to give a weighted result. This is particularly useful for arrays with >=3 dimensions.

This comes up e.g. when calculating a weighted covariance matrix as per @James King's example.

Here's another based on a current project:

set.seed(1)
## 2x2x2 array
a1 <- array(as.integer(rnorm(8, 10, 5)), dim=c(2, 2, 2))
## 'element-wise' sum of matrices
## weights = 1
rowSums(a1, dims=2)
## weights
w1 <- c(3, 4)
## a1[, , 1] * 3;  a1[, , 2] * 4
a1 <- sweep(a1, MARGIN=3, STATS=w1, FUN="*")
rowSums(a1, dims=2)

sweep() is typically used when you operate a matrix by row or by column, and the other input of the operation is a different value for each row / column. Whether you operate by row or column is defined by MARGIN, as for apply(). The values used for what I called "the other input" is defined by STATS. So, for each row (or column), you will take a value from STATS and use in the operation defined by FUN.

For instance, if you want to add 1 to the 1st row, 2 to the 2nd, etc. of the matrix you defined, you will do:

sweep (M, 1, c(1: 4), "+")

I frankly did not understand the definition in the R documentation either, I just learned by looking up examples.