Aliases: dmperm
Keywords: algebra
### ** Examples set.seed(17) (S9 <- rsparsematrix(9, 9, nnz = 10, symmetric=TRUE)) # dsCMatrix
9 x 9 sparse Matrix of class "dsCMatrix"
[1,] -0.055 . . . . . 1.6 . .
[2,] . . . . . 0.84 . 0.64 .
[3,] . . 0.63 . . . . . 1.30
[4,] . . . 0.16 . . . . 0.37
[5,] . . . . . . . 1.20 .
[6,] . 0.84 . . . . . . 0.19
[7,] 1.600 . . . . . . . .
[8,] . 0.64 . . 1.2 . . . .
[9,] . . 1.30 0.37 . 0.19 . . .
str( dm9 <- dmperm(S9) )
List of 6 $ p : int [1:9] 1 7 8 6 9 4 3 2 5 $ q : int [1:9] 7 1 5 2 3 4 9 6 8 $ r : int [1:8] 0 1 2 3 4 7 8 9 $ s : int [1:8] 0 1 2 3 4 7 8 9 $ rr5: int [1:5] 0 0 9 9 9 $ cc5: int [1:5] 0 0 0 9 9
(S9p <- with(dm9, S9[p, q]))
9 x 9 sparse Matrix of class "dgCMatrix"
[1,] 1.6 -0.055 . . . . . . .
[2,] . 1.600 . . . . . . .
[3,] . . 1.2 0.64 . . . . .
[4,] . . . 0.84 . . 0.19 . .
[5,] . . . . 1.30 0.37 . 0.19 .
[6,] . . . . . 0.16 0.37 . .
[7,] . . . . 0.63 . 1.30 . .
[8,] . . . . . . . 0.84 0.64
[9,] . . . . . . . . 1.20
## looks good, but *not* quite upper triangular; these, too: str( dm9.0 <- dmperm(S9, seed=-1)) # non-random too.
List of 6 $ p : int [1:9] 1 7 8 6 9 4 3 2 5 $ q : int [1:9] 7 1 5 2 3 4 9 6 8 $ r : int [1:8] 0 1 2 3 4 7 8 9 $ s : int [1:8] 0 1 2 3 4 7 8 9 $ rr5: int [1:5] 0 0 9 9 9 $ cc5: int [1:5] 0 0 0 9 9
str( dm9_1 <- dmperm(S9, seed= 1)) # a random one
List of 6 $ p : int [1:9] 1 7 8 6 3 9 4 2 5 $ q : int [1:9] 7 1 5 2 3 4 9 6 8 $ r : int [1:8] 0 1 2 3 4 7 8 9 $ s : int [1:8] 0 1 2 3 4 7 8 9 $ rr5: int [1:5] 0 0 9 9 9 $ cc5: int [1:5] 0 0 0 9 9
## The last two permutations differ, but have the same effect! (S9p0 <- with(dm9.0, S9[p, q])) # .. hmm ..
9 x 9 sparse Matrix of class "dgCMatrix"
[1,] 1.6 -0.055 . . . . . . .
[2,] . 1.600 . . . . . . .
[3,] . . 1.2 0.64 . . . . .
[4,] . . . 0.84 . . 0.19 . .
[5,] . . . . 1.30 0.37 . 0.19 .
[6,] . . . . . 0.16 0.37 . .
[7,] . . . . 0.63 . 1.30 . .
[8,] . . . . . . . 0.84 0.64
[9,] . . . . . . . . 1.20
stopifnot(all.equal(S9p0, S9p))# same as as default, but different from the random one set.seed(11) (M <- triu(rsparsematrix(9,11, 1/4)))
9 x 11 sparse Matrix of class "dgCMatrix"
[1,] . 0.89 . . 0.0072 . . . . . .
[2,] . -0.34 . . . -0.61 -0.44 . . . -0.94
[3,] . . . . -1.6000 . . . . . 0.89
[4,] . . . . 1.5000 -0.19 . 0.02 . -0.22 .
[5,] . . . . . . . . . -0.98 .
[6,] . . . . . . -0.19 . . -0.35 .
[7,] . . . . . . . . . . .
[8,] . . . . . . . . . . .
[9,] . . . . . . . . . . 0.48
dM <- dmperm(M); with(dM, M[p, q])
9 x 11 sparse Matrix of class "dgCMatrix"
[1,] . . . . 0.02 -0.19 . 1.5000 . -0.22 .
[2,] . . . . . -0.61 -0.34 . -0.44 . -0.94
[3,] . . . . . . 0.89 0.0072 . . .
[4,] . . . . . . . -1.6000 . . 0.89
[5,] . . . . . . . . -0.19 -0.35 .
[6,] . . . . . . . . . -0.98 .
[7,] . . . . . . . . . . 0.48
[8,] . . . . . . . . . . .
[9,] . . . . . . . . . . .
(Mp <- M[sample.int(nrow(M)), sample.int(ncol(M))])
9 x 11 sparse Matrix of class "dgCMatrix"
[1,] 0.89 -1.6000 . . . . . . . . .
[2,] 0.48 . . . . . . . . . .
[3,] . 1.5000 . . 0.02 . . . -0.22 -0.19 .
[4,] . . . . . . . . . . .
[5,] . . . . . . . . -0.35 . -0.19
[6,] . . . . . . . . -0.98 . .
[7,] . . . . . . . . . . .
[8,] -0.94 . . . . -0.34 . . . -0.61 -0.44
[9,] . 0.0072 . . . 0.89 . . . . .
dMp <- dmperm(Mp); with(dMp, Mp[p, q])
9 x 11 sparse Matrix of class "dgCMatrix"
[1,] . . . . 0.02 -0.19 . 1.5000 . . -0.22
[2,] . . . . . -0.61 -0.34 . -0.94 -0.44 .
[3,] . . . . . . 0.89 0.0072 . . .
[4,] . . . . . . . -1.6000 0.89 . .
[5,] . . . . . . . . 0.48 . .
[6,] . . . . . . . . . -0.19 -0.35
[7,] . . . . . . . . . . -0.98
[8,] . . . . . . . . . . .
[9,] . . . . . . . . . . .
set.seed(7) (n7 <- rsparsematrix(5, 12, nnz = 10, rand.x = NULL))
5 x 12 sparse Matrix of class "ngCMatrix"
[1,] . . . . . | | . . . . .
[2,] | . . . . . . . | . . .
[3,] | | . . . | . . . . . .
[4,] . . . | . . . | . . . .
[5,] . . | . . . . . . . . .
str( dm.7 <- dmperm(n7) )
List of 6 $ p : int [1:5] 2 3 4 1 5 $ q : int [1:12] 5 7 8 9 10 11 12 1 2 4 ... $ r : int [1:3] 0 4 5 $ s : int [1:3] 0 11 12 $ rr5: int [1:5] 0 4 5 5 5 $ cc5: int [1:5] 0 7 11 12 12
stopifnot(exprs = { lengths(dm.7[1:2]) == dim(n7) identical(dm.7, dmperm(as(n7, "dMatrix"))) identical(dm.7[1:4], dmperm(n7, nAns=4)) identical(dm.7[1:2], dmperm(n7, nAns=2)) })