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\name{dgCMatrix-class}
\docType{class}
\title{Compressed, sparse, column-oriented numeric matrices}
\alias{dgCMatrix-class}
\alias{\%*\%,dgCMatrix,dgeMatrix-method}
\alias{\%*\%,dgCMatrix,matrix-method}
\alias{\%*\%,numeric,dgCMatrix-method}
\alias{\%*\%,ddenseMatrix,dgCMatrix-method}
\alias{\%*\%,dgeMatrix,dgCMatrix-method}
\alias{\%*\%,matrix,dgCMatrix-method}
\alias{coerce,matrix,dgCMatrix-method}
\alias{coerce,dgeMatrix,dgCMatrix-method}
\alias{coerce,dgCMatrix,dgTMatrix-method}
\alias{coerce,dgCMatrix,dgBCMatrix-method}
\alias{coerce,dgCMatrix,dsCMatrix-method}
\alias{coerce,dgCMatrix,dtCMatrix-method}
\alias{coerce,dgCMatrix,lgCMatrix-method}
\alias{coerce,dgCMatrix,ngCMatrix-method}
\alias{coerce,dgCMatrix,matrix-method}
\alias{coerce,dgCMatrix,dgeMatrix-method}
\alias{crossprod,dgCMatrix,missing-method}
\alias{crossprod,dgCMatrix,matrix-method}
\alias{crossprod,dgCMatrix,dgeMatrix-method}
\alias{diag,dgCMatrix-method}
\alias{dim,dgCMatrix-method}
\alias{image,dgCMatrix-method}
\alias{lu,dgCMatrix-method}
\alias{t,dgCMatrix-method}
\alias{colMeans,dgCMatrix-method}
\alias{colSums,dgCMatrix-method}
\alias{rowMeans,dgCMatrix-method}
\alias{rowSums,dgCMatrix-method}
\alias{solve,dgCMatrix,matrix-method}
\alias{solve,dgCMatrix,missing-method}
\alias{solve,dgCMatrix,ddenseMatrix-method}
\alias{solve,dgCMatrix,dsparseMatrix-method}
%% Group methods --------- FIXME: These are not tested yet (or documented)
\alias{Arith,numeric,dgCMatrix-method}
\alias{Arith,dgCMatrix,numeric-method}
\alias{Arith,dgCMatrix,dgCMatrix-method}
%\alias{Math2,dgCMatrix,numeric-method}
\alias{Math,dgCMatrix-method}
% for silly reasons, need these 2+3 as well:
\alias{round,dgCMatrix,numeric-method}
\alias{signif,dgCMatrix,numeric-method}
\alias{log,dgCMatrix-method}
\alias{gamma,dgCMatrix-method}
\alias{lgamma,dgCMatrix-method}
%
\description{The \code{dgCMatrix} class is a class of sparse numeric
matrices in the compressed, sparse, column-oriented format. In this
implementation the non-zero elements in the columns are sorted into
increasing row order. \code{dsCMatrix} is the
\emph{\dQuote{standard}} class for sparse numeric matrices in the
\pkg{Matrix} package.
}
\section{Objects from the Class}{
Objects can be created by calls of the form \code{new("dgCMatrix", ...)} or
often more easily via \code{\link{Matrix}(*, sparse = TRUE)}.
}
\section{Slots}{
\describe{
\item{\code{x}:}{Object of class \code{"numeric"} - the non-zero
elements of the matrix.}
\item{\dots}{all other slots are inherited from the superclass
\code{"\linkS4class{CsparseMatrix}"}.
}
}
}
\section{Methods}{
\describe{
\item{coerce}{\code{signature(from = "matrix", to = "dgCMatrix")}}
\item{coerce}{\code{signature(from = "dgCMatrix", to = "matrix")}}
\item{coerce}{\code{signature(from = "dgCMatrix", to = "dgBCMatrix")}}
\item{coerce}{\code{signature(from = "dgCMatrix", to = "dgTMatrix")}}
\item{crossprod}{\code{signature(x = "dgCMatrix", y = "missing")}
returns \code{t(x) \%*\% x} as an \code{dsCMatrix} object.}
\item{crossprod}{\code{signature(x = "dgCMatrix", y = "matrix")}: ... }
\item{crossprod}{\code{signature(x = "dgCMatrix", y = "numeric")}: ... }
\item{diag}{\code{signature(x = "dgCMatrix")}: returns the diagonal
of \code{x}}
\item{dim}{\code{signature(x = "dgCMatrix")}: returns the dimensions
of \code{x}}
\item{image}{\code{signature(x = "dgCMatrix")}: plots an image of
\code{x} using the \code{\link[lattice]{levelplot}} function}
\item{lu}{\code{signature(x = "dgCMatrix")}: computes the LU
decomposition of a square \code{dgCMatrix} object}
}
}
%\references{}
%\author{}
%\note{}
\seealso{
Classes \code{\linkS4class{dsCMatrix}},
\code{\linkS4class{dtCMatrix}}, \code{\link{lu}}
}
\examples{
(m <- Matrix(c(0,0,2:0), 3,5))
str(m)
m[,1]
\dontshow{## regression test: this must give a validity-check error:
stopifnot(inherits(try(new("dgCMatrix", i = 0:1, p = 0:2,
x = c(2,3), Dim = 3:4)),
"try-error"))
}
}
\keyword{classes}
\keyword{algebra}
|
