Increase speed for a ifelse-for loop in R, while filling matrix within loop

user_12198665 0
Viewed 82

How can I increase the speed of the following loop operation, if the actual loop range is in 1000's? In the code below:

DF3= Dataframe

OP and k are two columns in DF3 dataframe. Here, k takes a value from 1 to 10.

l1 <- seq(1, 10, 1)
E<-matrix(data=0, nrow=10, ncol=10)
for (i in seq_along(l1)){
  for (j in seq_along(l1)){
    E[i,j]=sum(ifelse (DF3$OP[DF3$k==i]<DF3$OP[DF3$k==j],1,0))
  }
}

DF3 example:

k   OP
1   60
1   30
1   38
1   46
2   29
2   35
2   13
2   82
3   100
3   72
3   63
3   45
if-statement r for-loop matrix
3 Answers

Perhaps you can simplify your nested for loops via using combn, which computes the values for upper triangular matrix only (but they are sufficient to obtain the values in the whole matrix)

E <- matrix(data = 0, nrow = max(DF3$k), ncol = max(DF3$k))
v <- split(DF3$OP, DF3$k)
E[lower.tri(E)] <- combn(v, 2, FUN = function(x) sum(do.call("-", x) < 0))
E[upper.tri(E)] <- max(lengths(v)) - t(E)[upper.tri(E)]
E <- t(E)

and finally you will get

> E
     [,1] [,2] [,3]
[1,]    0    2    3
[2,]    2    0    3
[3,]    1    1    0

Data

> dput(DF3)
structure(list(k = c(1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 3L, 3L, 
3L, 3L), OP = c(60L, 30L, 38L, 46L, 29L, 35L, 13L, 82L, 100L,
72L, 63L, 45L)), class = "data.frame", row.names = c(NA, -12L
))
user_121587570

The logical comparison

DF3$OP[DF3$k==i]<DF3$OP[DF3$k==j]

implies that across all groups of k that there are an equal number of results. If there were uneven amounts of records between groups, there would be issues with the calculation.

In your dataset, you have 4 records in each group. That suggests that instead of working with a dataframe, we may be better off working with a matrix.

ncols = length(unique(DF3$k))
mat = matrix(DF3$OP, ncol = ncols)
E = matrix(0L, ncols, ncols)

for (i in seq_len(ncols)) {
  x = mat[, i]
  for (j in seq_len(ncols)) {
    E[i, j] = sum(x < mat[, j])
  }
}
E

##      [,1] [,2] [,3]
## [1,]    0    2    3
## [2,]    2    0    3
## [3,]    1    1    0
user_113550660

Since you need pairwise blocks of DF3$OP by DF3$k groups with reverse duplicates for greater and less than comparison, you are essentially filling in upper and lower triangle of a square matrix. Therefore, consider splitting data frame into OP blocks with by and pass into combn for matrix fill.

OP_list <- by(DF3, DF3$k, function(sub) sub$OP)
OP_list
# DF3$k: 1
# [1] 60 30 38 46
# ------------------------------------------------------------ 
# DF3$k: 2
# [1] 29 35 13 82
# ------------------------------------------------------------ 
# DF3$k: 3

E <- matrix(data=0, nrow=max(DF3$k), ncol=max(DF3$k))

# COMPARE ACROSS ALL COMBINATIONS OF K-GROUP VECTORS
E[upper.tri(E)] <- combn(OP_list, 2, function(x) sum(x[[1]] < x[[2]]))
E[lower.tri(E)] <- combn(OP_list, 2, function(x) sum(x[[1]] > x[[2]]))

E
#      [,1] [,2] [,3]
# [1,]    0    2    3
# [2,]    2    0    3
# [3,]    1    1    0

Should work for small or large sets. See: Online Demo

user_14224510
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