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\name{sparseMatrix-class}
\title{Virtual Class "sparseMatrix" --- Mother of Sparse Matrices}
%
\docType{class}
\keyword{array}
\keyword{classes}
%
\alias{sparseMatrix-class}
%
\alias{-,sparseMatrix,missing-method}
\alias{Math,sparseMatrix-method}
\alias{Ops,numeric,sparseMatrix-method}
\alias{Ops,sparseMatrix,ddiMatrix-method}
\alias{Ops,sparseMatrix,ldiMatrix-method}
\alias{Ops,sparseMatrix,nsparseMatrix-method}
\alias{Ops,sparseMatrix,numeric-method}
\alias{Ops,sparseMatrix,sparseMatrix-method}
\alias{Summary,sparseMatrix-method}
\alias{coerce,ANY,sparseMatrix-method}
\alias{coerce,factor,sparseMatrix-method}
\alias{coerce,matrix,sparseMatrix-method}
\alias{coerce,vector,sparseMatrix-method}
\alias{cov2cor,sparseMatrix-method}
\alias{diff,sparseMatrix-method}
\alias{dim<-,sparseMatrix-method}
\alias{format,sparseMatrix-method}
\alias{log,sparseMatrix-method}
\alias{mean,sparseMatrix-method}
\alias{print,sparseMatrix-method}
\alias{rep,sparseMatrix-method}
\alias{show,sparseMatrix-method}
\alias{summary,sparseMatrix-method}
%
\alias{print.sparseMatrix} % spoof, only so that users find this topic
%
\description{Virtual Mother Class of All Sparse Matrices}
\section{Slots}{
\describe{
\item{\code{Dim}:}{Object of class \code{"integer"} - the dimensions
of the matrix - must be an integer vector with exactly two
non-negative values.}
\item{\code{Dimnames}:}{a list of length two - inherited from class
\code{Matrix}, see \code{\linkS4class{Matrix}}.}
}
}
\section{Extends}{
Class \code{"Matrix"}, directly.
}
\section{Methods}{
\describe{
\item{show}{\code{(object = "sparseMatrix")}: The
\code{\link{show}} method for sparse matrices prints
\emph{\dQuote{structural}} zeroes as \code{"."} using
\code{\link{printSpMatrix}()} which allows further customization.}
\item{print}{\code{signature(x = "sparseMatrix")}, ....\cr
The \code{\link{print}} method for sparse matrices by default is the
same as \code{show()} but can be called with extra optional
arguments, see \code{\link{printSpMatrix}()}.}
\item{format}{\code{signature(x = "sparseMatrix")}, ....\cr
The \code{\link{format}} method for sparse matrices, see
\code{\link{formatSpMatrix}()} for details such as the extra
optional arguments.}
\item{summary}{\code{(object = "sparseMatrix", uniqT=FALSE)}: Returns
an object of S3 class \code{"sparseSummary"} which is basically a
\code{\link{data.frame}} with columns \code{(i,j,x)} (or just
\code{(i,j)} for \code{\linkS4class{nsparseMatrix}} class objects)
with the stored (typically non-zero) entries. The
\code{\link{print}} method resembles Matlab's way of printing
sparse matrices, and also the MatrixMarket format, see
\code{\link{writeMM}}.}
\item{cbind2}{\code{(x = *, y = *)}: several methods for binding
matrices together, column-wise, see the basic \code{\link{cbind}}
and \code{\link{rbind}} functions.\cr
Note that the result will typically be sparse, even when one
argument is dense and larger than the sparse one.
}
\item{rbind2}{\code{(x = *, y = *)}: binding matrices together
row-wise, see \code{cbind2} above.}
\item{determinant}{\code{(x = "sparseMatrix", logarithm=TRUE)}:
\code{\link{determinant}()} methods for sparse matrices typically
work via \code{\link{Cholesky}} or \code{\link{lu}} decompositions.}
\item{diag}{\code{(x = "sparseMatrix")}: extracts the diagonal of a
sparse matrix.}
\item{dim<-}{\code{signature(x = "sparseMatrix", value = "ANY")}:
allows to \emph{reshape} a sparse matrix to a sparse matrix with
the same entries but different dimensions. \code{value} must be of
length two and fulfill \code{prod(value) == prod(dim(x))}.}
\item{coerce}{\code{signature(from = "factor", to = "sparseMatrix")}:
Coercion of a factor to \code{"sparseMatrix"} produces the matrix
of indicator \bold{rows} stored as an object of class
\code{"dgCMatrix"}. To obtain columns representing the interaction
of the factor and a numeric covariate, replace the \code{"x"} slot
of the result by the numeric covariate then take the transpose.
Missing values (\code{\link{NA}}) from the factor are translated
to columns of all \code{0}s.}
}
See also \code{\link{colSums}}, \code{\link{norm}},
... %% FIXME
for methods with separate help pages.
}
\seealso{
\code{\link{sparseMatrix}}, and its references, such as
\code{\link{xtabs}(*, sparse=TRUE)}, or
\code{\link{sparse.model.matrix}()},
for constructing sparse matrices.
\code{\link{T2graph}} for conversion of \code{"graph"} objects
(package \pkg{graph}) to and from sparse matrices.
}
\note{
In method selection for multiplication operations (i.e. \code{\%*\%}
and the two-argument form of \code{\link[base]{crossprod}})
the sparseMatrix class takes precedence in the sense that if one
operand is a sparse matrix and the other is any type of dense matrix
then the dense matrix is coerced to a \code{dgeMatrix} and the
appropriate sparse matrix method is used.
}
%\author{Martin}
\examples{
\dontshow{ % for R_DEFAULT_PACKAGES=NULL
library(utils, pos = "package:base", verbose = FALSE)
}
showClass("sparseMatrix") ## and look at the help() of its subclasses
M <- Matrix(0, 10000, 100)
M[1,1] <- M[2,3] <- 3.14
M ## show(.) method suppresses printing of the majority of rows
data(CAex, package = "Matrix")
dim(CAex) # 72 x 72 matrix
determinant(CAex) # works via sparse lu(.)
## factor -> t( <sparse design matrix> ) :
(fact <- gl(5, 3, 30, labels = LETTERS[1:5]))
(Xt <- as(fact, "sparseMatrix")) # indicator rows
## missing values --> all-0 columns:
f.mis <- fact
i.mis <- c(3:5, 17)
is.na(f.mis) <- i.mis
Xt != (X. <- as(f.mis, "sparseMatrix")) # differ only in columns 3:5,17
stopifnot(all(X.[,i.mis] == 0), all(Xt[,-i.mis] == X.[,-i.mis]))
}
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