Little useless-useful R functions – Finding total sum of all sub-arrays and sum of maximums

When it comes to O(N log(N)) time complexity functions, this is the right section. 🙂

Given an array of natural numbers (later, you will see, it can be real, or any other less complex system (rational, irrational)) and you create a tree of all permutations preserving conjugation order.

array = c(1,2,3,4)
#sub-array with sum in [] brackets
1. c(1) [1]
2. c(1,2)     [3]
3. c(1,2,3)  [6]
4. c(1,2,3,4) [10]
6. c(2) [2]
7. c(2,3) [5]
8. c(2,3,4) [9]
10. c(3) [3]
11. c(3,4) [7]
13. c(4) [4]

with total SUM = 1+3+6+10+2+5+9+3+7+4 = 50

With simple R function, we can achieve this by:

arr = c(1,2,3,4,4,5,6,7,7,6,5,4,3,1)

sumArr <- function(x){
  summ <- 0
  i <- 1
  for (i in 1:length(arr)) {
    j <- i + 0
    midsum <- 0
    for (j in j:length(arr)) {
      midsum <- sum(arr[i:j])
      summ <- summ + midsum
      #print(sum)
    }
  }
  cat(paste0("Total sum of sub-arrays: ", summ))
 }

#calling function
sumArr(arr)

Ok, this was useless and straightforward. What if we decide to find the maximums of each array and create a total sum:

array = c(1,2,3,4)
#sub-array with sum in [] brackets
1. c(1) [1]
2. c(1,2)     [2]
3. c(1,2,3)  [3]
4. c(1,2,3,4) [4]
6. c(2) [2]
7. c(2,3) [3]
8. c(2,3,4) [4]
10. c(3) [3]
11. c(3,4) [4]
13. c(4) [4]

with total SUM = 1+2+3+4+2+3+4+3+4+4 = 30

sumArrOfMax <- function(x){
  summ <- 0
  i <- 1
  for (i in 1:length(arr)) {
    j <- i + 0
    midsum <- 0
    for (j in j:length(arr)) {
      midsum <- max(arr[i:j])
      summ <- summ + midsum
      #print(sum)
    }
  }
  cat(paste0("Total sum of maximums of all sub-arrays: ", summ))
}

# run function
sumArrOfMax(arr)

As always, code is available on the Github in the same Useless_R_function repository. Check Github for future updates.

Happy R-coding and stay healthy!“

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Tagged with: array, function, R, useless
Posted in Useless R functions