[R] Creating a maxtrix from "conditional prints"

From: EM <evilmastea_at_gmail.com>
Date: Fri, 04 Jun 2010 21:08:22 +0200


Hi guys :)

I'm dealing with this problem, perhaps conceptually not that complex, but still - I'm stuck.

Two columns, values 1<x<10, only integers. I want to check when the first column's index is identical to the second's (and vice versa). If that's true, I want to add a further column with value 1 (if true) or NA (if false).
Thus, I obtain 100 matrices (for each columns I will have 1-1, 1-2, 1-3 etc). Now, I want R to consider only those matrices whose "new" column has value = 1 & whose total number of rows is equal to 2. I can get R to "print" this result inside the "for" cycle, yet I can't manage to build a single matrix, to store all the results altoghether - which is what I really want.

Code example:

for (x in 1:10) {
for (y in 1:10) {
qui <- ifelse((mac[,1] == x) & (mac[,5] == y) | (mac[,1] == y) & (mac[,5] == x), 1, NA)
quo <- cbind(mac,qui)
qua <- subset(quo, qui ==1)
if(nrow(qua) == 2)
print(qua)
}}

result (wrong, now):

     ricevente genere_r abo_r classieta_r donatore genere_d abo_d
classieta_d    eta_d mismatch pra comp       mum qui

[1,] 8 0 1 3 9 1 1
4 56.17437 2 1 1 -6.645437 1
[2,] 9 1 1 2 8 0 1
3 48.77579 2 1 1 -5.905579 1 ricevente genere_r abo_r classieta_r donatore genere_d abo_d classieta_d eta_d mismatch pra comp mum qui
[1,] 8 0 1 3 10 0 0
3 48.77579 2 1 1 -5.905579 1
[2,] 10 0 2 5 8 0 1
3 48.77579 1 1 1 -5.391579 1 ricevente genere_r abo_r classieta_r donatore genere_d abo_d classieta_d eta_d mismatch pra comp mum qui
[1,] 8 0 1 3 9 1 1
4 56.17437 2 1 1 -6.645437 1
[2,] 9 1 1 2 8 0 1
3 48.77579 2 1 1 -5.905579 1 ricevente genere_r abo_r classieta_r donatore genere_d abo_d classieta_d eta_d mismatch pra comp mum qui
[1,] 9 1 1 2 10 0 0
3 48.77579 0 1 1 -4.877579 1
[2,] 10 0 2 5 9 1 1
4 56.17437 0 1 1 -5.617437 1

what I'd like to get:

     ricevente genere_r abo_r classieta_r donatore genere_d abo_d
classieta_d    eta_d mismatch pra comp       mum qui

[1,] 8 0 1 3 9 1 1
4 56.17437 2 1 1 -6.645437 1
[2,] 9 1 1 2 8 0 1

3 48.77579 2 1 1 -5.905579 1
[3,] 8 0 1 3 10 0 0
3 48.77579 2 1 1 -5.905579 1
[4,] 10 0 2 5 8 0 1
3 48.77579 1 1 1 -5.391579 1
[5,] 8 0 1 3 9 1 1
4 56.17437 2 1 1 -6.645437 1
[6,] 9 1 1 2 8 0 1
3 48.77579 2 1 1 -5.905579 1
[7,] 9 1 1 2 10 0 0
3 48.77579 0 1 1 -4.877579 1
[8,] 10 0 2 5 9 1 1
4 56.17437 0 1 1 -5.617437 1

(don't mind the values & names, this is just a small part of a longer algorithm)

Thanks for your help, in advance :)

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