This seems entirely avoidable, given that there is a relatively simple
formula for converting 2-ary indices [i,j] of S to 1-ary indices k of
S[lower.tri(S, TRUE)]:
k <- i + round(0.5 * (2L * n - j) * (j - 1L)) # for i >= j
I ought to be slightly more precise here: _coercion_ is avoidable,
because we can always map [i,j] to [k], but memory limits are not.
Certainly S@x[k] cannot be arbitrarily long...
At the very least, it would be convenient if the subset were performed
efficiently whenever dimensions would be dropped anyway:
* S[i, ] and S[, j] where i and j are vectors indexing exactly zero or
one rows/columns
* S[i] where i is a matrix of the form cbind(i, j)
This would support, e.g., a memory-efficient 'apply' analogue without
any need for MARGIN...
applySymmetric <- function(X, FUN, ..., simplify = TRUE, check = TRUE) {
if (check && !isSymmetric(X)) {
stop("'X' is not a symmetric matrix.")
}
## preprocessing
ans <- vector("list", n)
for (i in seq_len(n)) {
ans[[i]] <- forceAndCall(1L, FUN, S[i, ], ...)
}
## postprocessing
ans
}
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