Adding counts in matrix in R - r

Question

my issue is that within a loop for every i - a matrix like this outputted
structure(c(8L, 4L, 3L, 4L, 1L, 8L, 28L, 32L, 24L, 32L, 8L, 64L,
0L, 6L, 12L, 16L, 4L, 32L, 0L, 0L, 3L, 12L, 3L, 24L, 0L, 0L,
0L, 6L, 4L, 32L, 0L, 0L, 0L, 0L, 0L, 8L, 0L, 0L, 0L, 0L, 0L,
28L), .Dim = 6:7, .Dimnames = structure(list(c("ESN", "GWD",
"LWK", "MSL", "PEL", "YRI"), c("ACB", "ESN", "GWD", "LWK", "MSL",
"PEL", "YRI")), .Names = c("", "")), class = "table")
this matrix counts pariwise sharing - these counts should now be added to a larger table - with more levels than only the 7 present in this table. It is always a symmetric matrix (so the upper triangl) can be neglected
the real table (for which all elements are 0 in the beginnign)
matr<-matrix(0,nrow=26,ncol=26)
pop<-c("CHB","JPT","CHS","CDX","KHV","CEU","TSI","FIN","GBR","IBS","YRI","LWK","GWD","MSL","ESN","ASW","ACB","MXL","PUR","CLM","PEL","GIH","PJL","BEB","STU","ITU")
rownames(matr)<-pop
colnames(matr)<-pop
Can somebody tell me how I can add these counts from the small table to the large table (in the correct field) in an efficient way? I need to update the table 100k time - so effectiveness would be good. As mentioned addiing in the lower triangle is fine....
EDI #####
so another data set - might look like (this would then be generated from the next iteration of the loop)
structure(c(1L, 1L, 1L, 0L, 1L, 1L, 0L, 0L, 1L), .Dim = c(3L,
3L), .Dimnames = structure(list(c("IBS", "MXL", "TSI"), c("GBR",
"IBS", "MXL")), .Names = c("", "")), class = "table")
this should then also be added to matr - if a field has a number in it previously, the two number should be added up
Thanks

Answer 1

Taking into account duplicate/non-equal/non-zero entries in each of "table" created through iterations and updating only the lower.tri of "matr":
for(tab in tabs) {
## if each 'tab' is large enough,
## instead of creating (and subsetting with) 'row(tab)' and 'col(tab)'
##, a 'rep(, each = )' could be used
i = match(rownames(tab), rownames(mat))[row(tab)]
j = match(colnames(tab), colnames(mat))[col(tab)]
## to fill only the 'lower.tri'
ii = pmax(i, j); jj = pmin(i, j)
## sum duplicate entries 'tab' with 'sparseMatrix's intrinsic 'xtabs'-like behaviour
ijx = summary(sparseMatrix(ii, jj, x = c(tab)))
## subset and assign with a matrix index updating previous entries
ij = cbind(ijx$i, ijx$j)
mat[ij] = mat[ij] + ijx$x
}
mat
# a b c d e
#a 0 0 0 0 0
#b 4 1 0 0 0
#c 6 7 2 0 0
#d 5 12 5 7 0
#e 4 6 3 3 0
where "tabs" is a "list" containing the -iteratively- created "table"s:
set.seed(007)
tabs = replicate(3, table(replicate(2,
sample(letters[1:5], 50, TRUE), simplify = FALSE))[
sample(5, sample(2:5, 1)), sample(5, sample(2:5, 1))],
simplify = FALSE)
and "mat" is a smaller "matr":
mat = matrix(0L, 5, 5, dimnames = replicate(2, letters[1:5], simplify = FALSE))