spMatrix
Sparse Matrix Constructor From Triplet
Description
User friendly construction of a sparse matrix (inheriting from class TsparseMatrix
) from the triplet representation.
This is much less flexible than sparseMatrix()
and hence somewhat deprecated.
Usage
spMatrix(nrow, ncol, i = integer(), j = integer(), x = numeric())
Arguments
nrow, ncol | integers specifying the desired number of rows and columns. |
i,j | integer vectors of the same length specifying the locations of the non-zero (or non- |
x | atomic vector of the same length as |
Value
A sparse matrix in triplet form, as an R object inheriting from both TsparseMatrix
and generalMatrix
.
The matrix M will have M[i[k], j[k]] == x[k]
, for k = 1,2,…, n, where n = length(i)
and M[ i', j' ] == 0
for all other pairs (i',j').
See Also
Matrix(*, sparse=TRUE)
for the more usual constructor of such matrices. Then, sparseMatrix
is more general and flexible than spMatrix()
and by default returns a CsparseMatrix
which is often slightly more desirable. Further, bdiag
and Diagonal
for (block-)diagonal matrix constructors.
Consider TsparseMatrix
and similar class definition help files.
Examples
## simple example A <- spMatrix(10,20, i = c(1,3:8), j = c(2,9,6:10), x = 7 * (1:7)) A # a "dgTMatrix" summary(A) str(A) # note that *internally* 0-based indices (i,j) are used L <- spMatrix(9, 30, i = rep(1:9, 3), 1:27, (1:27) %% 4 != 1) L # an "lgTMatrix" ## A simplified predecessor of Matrix' rsparsematrix() function : rSpMatrix <- function(nrow, ncol, nnz, rand.x = function(n) round(rnorm(nnz), 2)) { ## Purpose: random sparse matrix ## -------------------------------------------------------------- ## Arguments: (nrow,ncol): dimension ## nnz : number of non-zero entries ## rand.x: random number generator for 'x' slot ## -------------------------------------------------------------- ## Author: Martin Maechler, Date: 14.-16. May 2007 stopifnot((nnz <- as.integer(nnz)) >= 0, nrow >= 0, ncol >= 0, nnz <= nrow * ncol) spMatrix(nrow, ncol, i = sample(nrow, nnz, replace = TRUE), j = sample(ncol, nnz, replace = TRUE), x = rand.x(nnz)) } M1 <- rSpMatrix(100000, 20, nnz = 200) summary(M1)
Copyright (©) 1999–2012 R Foundation for Statistical Computing.
Licensed under the GNU General Public License.