On 22-Dec-10 18:19:38, Ron Michael wrote:
> Let say, I have a matrix with 8 rows and 6 columns:_
> df1 <- matrix(NA, 8, 4)
> df1
> [,1] [,2] [,3] [,4]
> [1,] NA NA NA NA
> [2,] NA NA NA NA
> [3,] NA NA NA NA
> [4,] NA NA NA NA
> [5,] NA NA NA NA
> [6,] NA NA NA NA
> [7,] NA NA NA NA
> [8,] NA NA NA NA
>
> Now I want to get **all possible** ways to fetch 6 cells at
> a time. Is there any function to do that?
> Thanks,
If you just want all possible sets of 6 values (i.e. the values
at 6 different cells, for all possible choices of 6 out of 8*4 = 32)
then it is straightforward enough using the combn() function.
I give a smaller example to show the principle. You get the 20 ways
of choosing the values in 3 different cells of a 6-cell (3*2) matrix:
df1 <- matrix((1:6),ncol=2)
df1
# [,1] [,2]
# [1,] 1 4
# [2,] 2 5
# [3,] 3 6
combn(df1,3)
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 1 1 1 1 1 1 1 1 1
[2,] 2 2 2 2 3 3 3 4 4 5
[3,] 3 4 5 6 4 5 6 5 6 6
[,11] [,12] [,13] [,14] [,15] [,16] [,17] [,18] [,19] [,20]
[1,] 2 2 2 2 2 2 3 3 3 4
[2,] 3 3 3 4 4 5 4 4 5 5
[3,] 4 5 6 5 6 6 5 6 6 6
This basically works because the elements of a matrix are stored
linearly (1->2->3->4->5->6) down the columns, with a "dim" attribute
to sort out the indexing by rows and columns. combn(df1,3) then
picks out all sets of 3 from these 6 and returns the results in
"natural" order.
However, this result loses all information about the row-column
indexing of the values which are returned.
Getting at this is a little trickier. There may be some function
which can do it directly, though I don't know of one. An alternative
(the least subtle I can think of ... ) could be to do the same combn()
operation on vectors which gives the rows and columns of the elements
in the matrix df1:
The result of combn() is a list, as above, and you can make it a
linear vector with:
as.vector(combn(df1,3))
# [1] 1 2 3 1 2 4 1 2 5 1 2 6 1 3 4 1 3 5 1 3 6 1 4 5 1 4 6 1 5 6
[16] 2 3 4 2 3 5 2 3 6 2 4 5 2 4 6 2 5 6 3 4 5 3 4 6 3 5 6 4 5 6
Now you can do the same with the columns of a matrix which carries
the row indices and the column indices:
RC <- cbind(Row=rep(c(1,2,3),2),Col=rep(c(1,2),each=3))
RC
# Row Col
# [1,] 1 1
# [2,] 2 1
# [3,] 3 1
# [4,] 1 2
# [5,] 2 2
# [6,] 3 2
Now:
df1.3 <- as.vector(combn(df1,3))
ix.RC <- combn((1:nrow(RC)),3)
All <- cbind(RC[ix.RC,],df1.3)
colnames(All) <- c("Row","Col","Val")
All
# Row Col Val
# [1,] 1 1 1
# [2,] 2 1 2
# [3,] 3 1 3
# [4,] 1 1 1
# [5,] 2 1 2
# [6,] 1 2 4
# [7,] 1 1 1
# [8,] 2 1 2
# [9,] 2 2 5
# [10,] 1 1 1
# [11,] 2 1 2
# [12,] 3 2 6
# .................
# [49,] 3 1 3
# [50,] 1 2 4
# [51,] 2 2 5
# [52,] 3 1 3
# [53,] 1 2 4
# [54,] 3 2 6
# [55,] 3 1 3
# [56,] 2 2 5
# [57,] 3 2 6
# [58,] 1 2 4
# [59,] 2 2 5
# [60,] 3 2 6
in which each block of 3 successive rows gives you the 3 Rows,
the 3 Columns, and the 3 Values for one of the 20 possible
choices of 3 cells out of the 6 in the matrix. You could
subsequently rearrange this to suit your purposes.
Ted.
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E-Mail: (Ted Harding) <ted.hard...@wlandres.net>
Fax-to-email: +44 (0)870 094 0861
Date: 22-Dec-10 Time: 22:39:03
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