## Examples for accumarray
val = 101:105
subs = as.matrix(c(1, 2, 4, 2, 4))
accumarray(subs, val)
# [101; 206; 0; 208]
val = 101:105
subs <- matrix(c(1,2,2,2,2, 1,1,3,1,3, 1,2,2,2,2), ncol = 3)
accumarray(subs, val)
# , , 1
# [,1] [,2] [,3]
# [1,] 101 0 0
# [2,] 0 0 0
# , , 2
# [,1] [,2] [,3]
# [1,] 0 0 0
# [2,] 206 0 208
val = 101:106
subs <- matrix(c(1, 2, 1, 2, 3, 1, 4, 1, 4, 4, 4, 1), ncol = 2, byrow = TRUE)
accumarray(subs, val, func = function(x) sum(diff(x)))
# [,1] [,2] [,3] [,4]
# [1,] 0 1 0 0
# [2,] 0 0 0 0
# [3,] 0 0 0 0
# [4,] 2 0 0 0
val = 101:105
subs = matrix(c(1, 1, 2, 1, 2, 3, 2, 1, 2, 3), ncol = 2, byrow = TRUE)
accumarray(subs, val, sz = c(3, 3), func = max, fillval = NA)
# [,1] [,2] [,3]
# [1,] 101 NA NA
# [2,] 104 NA 105
# [3,] NA NA NA
## Examples for uniq
a <- c(1, 1, 5, 6, 2, 3, 3, 9, 8, 6, 2, 4)
A <- uniq(a); A
# A$b 1 5 6 2 3 9 8 4
# A$m 2 3 10 11 7 8 9 12
# A$n 1 1 2 3 4 5 5 6 7 3 4 8
A <- uniq(a, first = TRUE); A
# A$m 1 3 4 5 6 8 9 12
## Example: Subset sum problem
# Distribution of unique sums among all combinations of a vectors.
allsums <- function(a) {
S <- c(); C <- c()
for (k in 1:length(a)) {
U <- uniq(c(S, a[k], S + a[k]))
S <- U$b
C <- accumarray(U$n, c(C, 1, C))
}
o <- order(S); S <- S[o]; C <- C[o]
return(list(S = S, C = C))
}
A <- allsums(seq(1, 9, by=2)); A
# A$S 1 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 24 25
# A$C 1 1 1 1 1 1 2 2 2 1 2 2 1 2 2 2 1 1 1 1 1 1 1
Run the code above in your browser using DataLab