if(dev.cur() <= 1) get(getOption("device"))() oldpar <- par(ask = interactive() && (.Device %in% c("X11", "GTK", "windows", "Macintosh"))) oldoptions <- options(warn=-1) data(swedishpines) plot(swedishpines, main="Point pattern") data(demopat) plot(demopat, cols=c("green", "blue"), main="Multitype point pattern") data(longleaf) plot(longleaf, fg="blue", main="Marked point pattern") data(lansing) plot(lansing, "Lansing Woods data") plot(split(lansing)) data(letterR) plot(letterR) lambda <- 10/area.owin(letterR) points(rpoispp(lambda, win=letterR)) points(rpoispp(9 * lambda, win=letterR)) points(rpoispp(90 * lambda, win=letterR)) X <- swedishpines subset <- 1:20 plot(X[subset]) subwindow <- owin(poly=list(x=c(0,96,96,40,40,0),y=c(0,0,100,100,50,0))) plot(X[,subwindow]) K <- Kest(swedishpines) plot(K) title(main="K function for Swedish Pines") en <- envelope(swedishpines, fun=Kest, nsim=10, correction="translate") plot(en, main="Envelopes of K function based on CSR") pc <- pcf(swedishpines) plot(pc) title(main="Pair correlation function") plot(swedishpines %mark% (nndist(swedishpines)/2), markscale=1, main="Stienen diagram") plot(swedishpines$window, main="Distance map") dis <- distmap(swedishpines) plot(dis, add=TRUE) points(swedishpines) plot(swedishpines$window, main="Thresholded distance") dis$v <- (dis$v < 4.5) plot(dis, add=TRUE) points(swedishpines) plot(allstats(swedishpines)) fit <- ppm(swedishpines, ~1, Strauss(r=7)) print(fit) Xsim <- rmh(model=fit, start=list(n.start=80), control=list(nrep=100)) plot(Xsim, main="Simulation from fitted Strauss model") data(demopat) plot(demopat, cols=c("red", "blue")) plot(alltypes(demopat, "K")) fit <- ppm(demopat, ~marks + polynom(x,y,2), Poisson()) plot(fit) plot(rpoispp(100)) plot(rpoispp(function(x,y){1000 * exp(-3*x)}, 1000)) plot(rMaternII(200, 0.05)) plot(rSSI(0.05, 200)) plot(rThomas(10, 0.2, 5)) plot(rMatClust(10, 0.05, 4)) Xg <- rmh(list(cif="geyer", par=c(beta=1.25, gamma=1.6, r=0.2, sat=4.5), w=c(0,10,0,10)), control=list(nrep=1e4), start=list(n.start=200)) plot(Xg, main=paste("Geyer saturation process\n", "rmh() with cif=\"geyer\"")) par(oldpar) showoffK <- function(Y, current, ..., fullpicture,rad) { plot(fullpicture, main="Animation using \`applynbd\'\n explaining the K function") points(Y, cex=2) u <- current points(u[1],u[2],pch="+",cex=3) theta <- seq(0,2*pi,length=100) polygon(u[1]+ rad * cos(theta),u[2]+rad*sin(theta)) text(u[1]+rad/3,u[2]+rad/2,Y$n-1,cex=3) Sys.sleep(if(runif(1) < 0.05) 1.2 else 0.25) return(Y$n) } data(redwood) applynbd(redwood, R=0.2, showoffK, fullpicture=redwood, rad=0.2, exclude=TRUE) options(oldoptions)