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\name{spMatrix}
\title{Sparse Matrix Constructor From Triplet}
%
\keyword{array}
\keyword{utilities}
%
\alias{spMatrix}
%
\description{
User friendly construction of a sparse matrix (inheriting from class
\code{\linkS4class{TsparseMatrix}}) from the triplet representation.
This is much less flexible than \code{\link{sparseMatrix}()} and hence
somewhat \emph{deprecated}.
}
\usage{
spMatrix(nrow, ncol, i = integer(0L), j = integer(0L), x = double(0L))
}
\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}(*, sparse=TRUE)} for the more usual
constructor of such matrices. Then, \code{\link{sparseMatrix}}
is more general and flexible than \code{spMatrix()} and by default
returns a \code{\linkS4class{CsparseMatrix}} which is often slightly
more desirable. Further, \code{\link{bdiag}} and
\code{\link{Diagonal}} for (block-)diagonal matrix constructors.
Consider \code{\linkS4class{TsparseMatrix}} and similar class
definition help files.
}
\examples{
\dontshow{ % for R_DEFAULT_PACKAGES=NULL
library(stats, pos = "package:base", verbose = FALSE)
library(utils, pos = "package:base", verbose = FALSE)
}
## 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)
}
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