For each matrix row apply a function over a ragged array

For each matrix row apply a function to each cell of a ragged array, that is to each (non-empty) group of values given by a unique combination of the levels of certain factors.

tgs_matrix_tapply(x, index, fun, ...)

Arguments

x

a matrix or a sparse matrix of 'dgCMatrix' type

index

a 'list' of one or more 'factor's, each of same length as the number of columns in 'x'. The elements are coerced to factors by 'as.factor'.

fun

the function to be applied

...

optional arguments to 'fun'

Value

A matrix of length(index) X nrow(x) size. Each [i,j] element represents the result of applying 'fun' to x[i,which(index==levels(index)[j])].
Note that the return value is a dense matrix even when x is sparse.

Details

'tgs_matrix_tapply(x, index, fun)' is essentialy an efficient implementation of 'apply(mat, 1, function(x) tapply(x, index, fun))'.

Examples

# \donttest{
# Note: all the available CPU cores might be used

set.seed(seed = 1)
nr <- 6
nc <- 10
mat <- matrix(sample(c(rep(0, 6), 1:3), nr * nc, replace = TRUE), nrow = nr, ncol = nc)
index <- factor(rep_len(1:3, ncol(mat)), levels = 0:5)
r1 <- apply(mat, 1, function(x) tapply(x, index, sum))
r2 <- tgs_matrix_tapply(mat, index, sum)
# }