bandSparse  R Documentation 
Construct a sparse banded matrix by specifying its nonzero sup and superdiagonals.
bandSparse(n, m = n, k, diagonals, symmetric = FALSE, repr = "C", giveCsparse = (repr == "C"))
n,m 
the matrix dimension (n,m) = (nrow, ncol). 
k 
integer vector of “diagonal numbers”, with identical
meaning as in 
diagonals 
optional list of sub/super diagonals; if missing,
the result will be a pattern matrix, i.e., inheriting from
class

symmetric 
logical; if true the result will be symmetric
(inheriting from class 
repr 

giveCsparse 
(deprecated, replaced with 
a sparse matrix (of class
CsparseMatrix
) of dimension n x m
with diagonal “bands” as specified.
band
, for extraction of matrix bands;
bdiag
, diag
,
sparseMatrix
,
Matrix
.
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)) , inherits(B, "dtCMatrix") # triangular! )
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