Search for Euclidean distance in R {spartstat} between points bounded by an irregular polygonal window

Question

I am trying to find the Euclidean distance between two points bounded by an irregular polygon. (i.e. the distance should be calculated as a route through the specified window)

Here is an example of reproducibility:

library(spatstat)

#Simple example of a polygon and points.
ex.poly <- data.frame(x=c(0,5,5,2.5,0), y=c(0,0,5,2.5,5))
points <- data.frame(x=c(0.5, 2.5, 4.5), y=c(4,1,4))

bound <- owin(poly=data.frame(x=ex.poly$x, y=ex.poly$y))

test.ppp <- ppp(x=points$x, y=points$y, window=bound)

pairdist.ppp(test.ppp)#distance between every point
#The distance result from this function between point 1 and point 3, is given as 4.0

However, we only know from the construction of points

plot(test.ppp)

that the distance at which the route is limited to the polygon should be greater (in this case 5.00).

Is there any other function that I don't know about in {spartstat} that will do this? Or does anyone have other suggestions for another package that could do this?

I am trying to find the distance between two points in a pond, so the irregular polygon in my actual data is more complicated.

Any help is much appreciated!

Greetings

Answer 1

, gdistance, . , , , 16 ( ). , 2% ( ) .

library(maptools)  ## To convert spatstat objects to sp objects
library(gdistance) ## Loads raster and provides cost-surface functions

## Convert *.ppp points to SpatialPoints object
Pts <- as(test.ppp, "SpatialPoints")

## Convert the lake boundary to a raster, with values of 1 for
## cells within the lake and values of 0 for cells on land
Poly <- as(bound, "SpatialPolygons")           ## 1st to SpatialPolygons-object
R <- raster(extent(Poly), nrow=100,  ncol=100) ## 2nd to RasterLayer ...
RR <- rasterize(Poly, R)                       ## ...
RR[is.na(RR)]<-0                               ## Set cells on land to "0"

## gdistance requires that you 1st prepare a sparse "transition matrix"
## whose values give the "conductance" of movement between pairs of
## adjacent and next-to-adjacent cells (when using directions=16)
tr1 <- transition(RR, transitionFunction=mean, directions=16)
tr1 <- geoCorrection(tr1,type="c")

## Compute a matrix of pairwise distances between points
## (These should be 5.00 and 3.605; all are within 2% of actual value).  
costDistance(tr1, Pts)
##          1        2
## 2 3.650282         
## 3 5.005259 3.650282

## View the selected paths
plot(RR)
plot(Pts, pch=16, col="gold", cex=1.5, add=TRUE)
SL12 <- shortestPath(tr1, Pts[1,], Pts[2,], output="SpatialLines")
SL13 <- shortestPath(tr1, Pts[1,], Pts[3,], output="SpatialLines")
SL23 <- shortestPath(tr1, Pts[2,], Pts[3,], output="SpatialLines")
lapply(list(SL12, SL13, SL23), function(X) plot(X, col="red", add=TRUE, lwd=2))