Cummulative matrix

[cj_risk]

I am attempting to create a cumulative matrix from another matrix. I was playing around with loops and lappy. The following seems to work, but it's very slow. The actual matrix is much larger. I am wondering if there is a more efficient way to create the cumulatrive matrix. Thanks in advance.

# example original matrix:
mat1<-cbind(1:5,1:5,1:5)

# new matrix with the cumulative sum of all previous columns in mat1.
mat2<-mat1
for(i in 2:ncol(mat1)){
    mat2[,i]=apply(mat1[,1:i],1,sum)
}

[FJCC]

Maybe using cumsum() will be faster.

mat1<-cbind(1:5,1:5,1:5)

# new matrix with the cumulative sum of all previous columns in mat1.
mat2<-mat1
for(i in 2:ncol(mat1)){
  mat2[,i]=apply(mat1[,1:i],1,sum)
}
mat2
#>      [,1] [,2] [,3]
#> [1,]    1    2    3
#> [2,]    2    4    6
#> [3,]    3    6    9
#> [4,]    4    8   12
#> [5,]    5   10   15

mat3 <- t(apply(mat1,1,cumsum))
mat3
#>      [,1] [,2] [,3]
#> [1,]    1    2    3
#> [2,]    2    4    6
#> [3,]    3    6    9
#> [4,]    4    8   12
#> [5,]    5   10   15

^{Created on 2022-08-22 by the reprex package (v2.0.1)}

[FactOREO]

This solution from StackOverflow (r - Calculating cumulative sum for each row - Stack Overflow) seems to be a bit faster:

# define matrix
mat1 <- matrix(c(rep(1:5,3)), ncol = 3)

# define rowCumSum function
colCumSums2 <- function(x) {
  matrix(cumsum(rbind(x,-colSums(x))), ncol=ncol(x))[1:nrow(x),]
}

rowCumSums2 <- function(x) {
  t(colCumSums2(t(x)))
}

# for the for-loop
mat <- matrix(ncol = 3, nrow = 5)

# comparison
rbenchmark::benchmark(
  forloop = for(i in 2:ncol(mat1)){mat[,1] <- apply(mat1[,1:i],1,sum)},
  cumsum  = t(apply(mat1, 1, cumsum)),
  rowCumSums = rowCumSums2(mat1),
  replications = 1000
)
#>      test replications elapsed relative user.self sys.self user.child sys.child
#> 2  cumsum         1000    0.17    2.833      0.11     0.05         NA        NA
#> 1 forloop         1000   10.97  182.833      8.97     0.33         NA        NA
#> 3 rowCumSums      1000    0.06    1.000      0.06     0.00         NA        NA

^{Created on 2022-08-22 with reprex v2.0.2}

[cj_risk]

Much faster and simpler. Thank-you!