\name{spMatrix} \alias{spMatrix} \title{Sparse Matrix Constructor From Triplet} \description{ User friendly construction of a sparse matrix (inheriting from class \code{\linkS4class{TsparseMatrix}}) from the triplet representation. } \usage{ spMatrix(nrow, ncol, i, j, x) } \arguments{ \item{nrow, ncol}{integers specifying the desired number of rows and columns.} \item{i,j}{integer vectors of the same length specifying the locations of the non-zero (or non-\code{TRUE}) entries of the matrix.} \item{x}{atomic vector of the same length as \code{i} and \code{j}, specifying the values of the non-zero entries.} } \value{ A sparse matrix in triplet form, as an \R object inheriting from both \code{\linkS4class{TsparseMatrix}} and \code{\linkS4class{generalMatrix}}. The matrix \eqn{M} will have \code{M[i[k], j[k]] == x[k]}, for \eqn{k = 1,2,\ldots, n}, where \code{n = length(i)} and \code{M[ i', j' ] == 0} for all other pairs \eqn{(i',j')}. } \seealso{\code{\link{Matrix}} for the more usual constructor of such matrices; \code{\linkS4class{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" ### This is a useful utility, to be used for experiments : 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) } \keyword{array}