\name{as.rectangle}
\alias{as.rectangle}
\title{Window Frame}
\description{
Extract the window frame of a window
or other spatial dataset
}
\usage{
as.rectangle(w, \dots)
}
\arguments{
\item{w}{A window, or a dataset that has a window.
Either a window (object of class \code{"owin"}),
a pixel image (object of class \code{"im"})
or other data determining such a window.
}
\item{\dots}{
Optional. Auxiliary data to help determine the window. If
\code{w} does not belong to a recognised class,
the arguments \code{w} and \code{\dots}
are passed to \code{\link{as.owin}} to determine the window.
}
}
\value{
A window (object of class \code{"owin"})
of type \code{"rectangle"} representing a rectangle.
}
\details{
This function is the quickest way to determine a bounding rectangle
for a spatial dataset.
If \code{w} is a window, the function
just extracts the outer bounding rectangle
of \code{w} as given by its elements \code{xrange,yrange}.
The function can also be applied to any spatial dataset that has a window:
for example, a point pattern (object of class \code{"ppp"}) or
a line segment pattern (object of class \code{"psp"}).
The bounding rectangle of the window of the dataset is extracted.
Use the function \code{\link{bounding.box}} to compute the \emph{smallest}
bounding rectangle of a dataset.
}
\seealso{
\code{\link{owin}},
\code{\link{as.owin}},
\code{\link{bounding.box}}
}
\examples{
w <- owin(c(0,10),c(0,10), poly=list(x=c(1,2,3,2,1), y=c(2,3,4,6,7)))
r <- as.rectangle(w)
# returns a 10 x 10 rectangle
data(lansing)
as.rectangle(lansing)
data(copper)
as.rectangle(copper$SouthLines)
}
\author{Adrian Baddeley
\email{adrian@maths.uwa.edu.au}
\url{http://www.maths.uwa.edu.au/~adrian/}
and Rolf Turner
\email{r.turner@auckland.ac.nz}
}
\keyword{spatial}
\keyword{manip}