Make my R code run faster (nested loops)

Question

Imagine you have a 150 by 5 matrix. Each element contains a random integer from 0 to 20.

Now think each column of the matrix as independent; I need to loop through all the possible combination of all 5 columns, which yields 150^5 = 75937500000 combinations.

It is critical I run every single combination exactly once. The order which I ran combinations do not matter.

I tried doing this using while loops. See code below.

To run this loop, based on my calculation it would take me 54 hours on my laptop.

Questions

• Any way to make my code run faster on my laptop? (bootstrapping?)

• If not, are there any web R servers I can access that would run my code at a significant faster rate?

• If not, would it make any significant difference to run this in another/faster language? (Python)

   while(counter1 <= 150) { while(counter2 <= 150) { while(counter3 <= 150) { while(counter4 <= 150) { while(counter5 <= 150) { #Other operations that take additional time# result<-c( giant_matrix[counter1,1], giant_matrix[counter2,2], giant_matrix[counter3,3], giant_matrix[counter4,4], giant_matrix[counter5,5]) counter5=counter5+1 } counter5=1 counter4=counter4+1 } counter4=1 counter3=counter3+1 } counter3=1 counter2=counter2+1 } counter2=1 counter1=counter1+1 } 

Answer 1

Here is the above solution with a 20 x 5 matrix of 100 elements. It results in a data frame of 3,200,000 x 5 size:

m <- matrix(sample(1:20, 100, replace = TRUE), nrow = 20)
df <- expand.grid(m[, 1], m[, 2], m[, 3], m[, 4], m[, 5])

Example output of the above df (head):

head(df)
  Var1 Var2 Var3 Var4 Var5
1   10   19   13    4    7
2   19   19   13    4    7
3    3   19   13    4    7
4    5   19   13    4    7
5   11   19   13    4    7
6    8   19   13    4    7

nrow(df)
[1] 3200000

dim(df)
[1] 3200000       5