Matrix (version 0.999375-46)

bandSparse: Construct Sparse Banded Matrix from (Sup-/Super-) Diagonals

Description

Construct a sparse banded matrix by specifying its non-zero sup- and super-diagonals.

Usage

bandSparse(n, m = n, k, diagonals, symmetric = FALSE)

Arguments

n,m

the matrix dimension $(n,m) = (nrow, ncol)$.

k

integer vector of diagonal numbers, with identical meaning as in band(*, k).

diagonals

optional list of sub-/super- diagonals; if missing, the result will be a pattern matrix, i.e., inheriting from class nMatrix.

diagonals can also be $n' \times d$ matrix, where

symmetric

logical; if true the result will be symmetric (inheriting from class symmetricMatrix) and only the upper or lower triangle must be specified (via k and diagonals).

Value

• a sparse matrix (of class CsparseMatrix) of dimension $n \times m$ with diagonal bands as specified.

See Also

band, for extraction of matrix bands; bdiag, diag, sparseMatrix, Matrix.

Examples

diags <- list(1:30, 10*(1:20), 100*(1:20))
s1 <- bandSparse(13, k = -c(0:2, 6), diag = c(diags, diags[2]), symm=TRUE)
s1
s2 <- bandSparse(13, k =  c(0:2, 6), diag = c(diags, diags[2]), symm=TRUE)
stopifnot(identical(s1, t(s2)), is(s1,"dsCMatrix"))

## a pattern Matrix of *full* (sub-)diagonals:
bk <- c(0:4, 7,9)
(s3 <- bandSparse(30, k = bk, symm = TRUE))

## If you want a pattern matrix, but with "sparse"-diagonals,
## you currently need to go via logical sparse:
lLis <- lapply(list(rpois(20, 2), rpois(20,1), rpois(20,3))[c(1:3,2:3,3:2)],
               as.logical)
(s4 <- bandSparse(20, k = bk, symm = TRUE, diag = lLis))
(s4. <- as(drop0(s4), "nsparseMatrix"))

n <- 1e4
bk <- c(0:5, 7,11)
bMat <- matrix(1:8, n, 8, byrow=TRUE)
bLis <- as.data.frame(bMat)
B  <- bandSparse(n, k = bk, diag = bLis)
Bs <- bandSparse(n, k = bk, diag = bLis, symmetric=TRUE)
B [1:15, 1:30]
Bs[1:15, 1:30]
## can use a list *or* a matrix for specifying the diagonals:
stopifnot(identical(B,  bandSparse(n, k = bk, diag = bMat)),
	  identical(Bs, bandSparse(n, k = bk, diag = bMat, symmetric=TRUE)))