Tukukkk

I have matrix M and N given by

> M

     [,1] [,2] [,3] [,4] [,5]

[1,]    5    1    1    7    7

[2,]    4    7    4    2    7

[3,]   11   19   20   50   30



> N

      [,1] [,2]

[1,]    7    1

[2,]    7    7

I want to find the column values in M that should be paired with N to get

  [,1] [,2]

    7    1

    7    7

    30   19

I tried the code below. Can i get an efficient way of doing it or especially doing it without using the for commands?

E=numeric()

for (i in 1:2){

    for (j in 1:5) {

        if (N[1,i]==M[1,j] & N[2,i]==M[2,j]){

           E[i]= M[3,j]

        }

    }  

}

E

rbind(N,E)

Here's a way using multiple calls to apply. We iterate over the columns of M and N to find which column in M matches the first column in N and then which matches the second column in N.

logicals <- apply(M[-3,], # exclude third row

                  2, # iterate over columns

                  FUN = function(x) 

                    apply(N, 2, #then iterate over columns of N

                          FUN = function(y) all(x == y)))



#       [,1]  [,2]  [,3]  [,4]  [,5]

# [1,] FALSE FALSE FALSE FALSE  TRUE

# [2,] FALSE  TRUE FALSE FALSE FALSE  



M[,apply(logicals, 1, which)]



     [,1] [,2]

[1,]    7    1

[2,]    7    7

[3,]   30   19

data

M <- structure(c(5, 4, 11, 1, 7, 19, 

        1, 4, 20, 7, 2, 50, 

        7, 7, 30), 

      .Dim = c(3L, 5L))



N <- structure(c(7, 7, 1, 7), .Dim = c(2L, 2L))

Well here is your loop re-written

E <- vapply(seq(nrow(N)), function(i) M[3,M[1,] == N[1,i] & M[2,] == N[2,i]], numeric(1))

# with

> rbind(N,E)

  [,1] [,2]

     7    1

     7    7

E   30   19 

there is only one loop (vapply - a wrapper for a loop) which runs through the rows of N.