https://github.com/cran/spatstat
Tip revision: 1a4b153dab7a7656ab810d53e156a13a67e4eea5 authored by Adrian Baddeley on 01 August 2018, 14:50:03 UTC
version 1.56-1
version 1.56-1
Tip revision: 1a4b153
distfun.lpp.Rd
\name{distfun.lpp}
\Rdversion{1.1}
\alias{distfun.lpp}
\title{
Distance Map on Linear Network
}
\description{
Compute the distance function of a point pattern on a linear network.
}
\usage{
\method{distfun}{lpp}(X, ..., k=1)
}
\arguments{
\item{X}{
A point pattern on a linear network
(object of class \code{"lpp"}).
}
\item{k}{
An integer. The distance to the \code{k}th nearest point
will be computed.
}
\item{\dots}{
Extra arguments are ignored.
}
}
\details{
On a linear network \eqn{L}, the \dQuote{geodesic distance function}
of a set of points \eqn{A} in \eqn{L} is the
mathematical function \eqn{f} such that, for any
location \eqn{s} on \eqn{L},
the function value \code{f(s)}
is the shortest-path distance from \eqn{s} to \eqn{A}.
The command \code{distfun.lpp} is a method for the generic command
\code{\link{distfun}}
for the class \code{"lpp"} of point patterns on a linear network.
If \code{X} is a point pattern on a linear network,
\code{f <- distfun(X)} returns a \emph{function}
in the \R language that represents the
distance function of \code{X}. Evaluating the function \code{f}
in the form \code{v <- f(x,y)}, where \code{x} and \code{y}
are any numeric vectors of equal length containing coordinates of
spatial locations, yields the values of the distance function at these
locations. More efficiently \code{f} can be called in the form
\code{v <- f(x, y, seg, tp)} where \code{seg} and \code{tp} are the local
coordinates on the network. It can also be called as
\code{v <- f(x)} where \code{x} is a point pattern on the same linear
network.
The function \code{f} obtained from \code{f <- distfun(X)}
also belongs to the class \code{"linfun"}.
It can be printed and plotted immediately as shown in the Examples.
It can be
converted to a pixel image using \code{\link{as.linim}}.
}
\value{
A \code{function} with arguments \code{x,y} and optional
arguments \code{seg,tp}.
It also belongs to the class \code{"linfun"} which has methods
for \code{plot}, \code{print} etc.
}
\seealso{
\code{\link{linfun}},
\code{\link{methods.linfun}}.
To identify \emph{which} point is the nearest neighbour, see
\code{\link{nnfun.lpp}}.
}
\examples{
data(letterR)
X <- runiflpp(3, simplenet)
f <- distfun(X)
f
plot(f)
# using a distfun as a covariate in a point process model:
Y <- runiflpp(4, simplenet)
fit <- lppm(Y ~D, covariates=list(D=f))
f(Y)
}
\author{
\spatstatAuthors.
}
\keyword{spatial}
\keyword{math}