What are the rules for ppp objects? Is selecting two variables possible for an sapply function?

Question

Working with code that describes a poisson cluster process in spatstat. Breaking down each line of code one at a time to understand. Easy to begin.

library(spatstat)
lambda<-100
win<-owin(c(0,1),c(0,1))
n.seeds<-lambda*win$xrange[2]*win$yrange[2]

Once the window is defined I then generate my points using a random generation function

x=runif(min=win$xrange[1],max=win$xrange[2],n=pmax(1,n.seeds))
y=runif(min=win$yrange[1],max=win$yrange[2],n=pmax(1,n.seeds))

This can be plotted straight away I know using the ppp function

seeds<-ppp(x=x,
y=y,
window=win)

plot(seeds)

The next line I add marks to the ppp object, it is apparently describing the angle of rotation of the points, I don't understand how this works right now but that is okay, I will figure out later.

marks<-data.frame(angles=runif(n=pmax(1,n.seeds),min=0,max=2*pi))
seeds1<-ppp(x=x,
           y=y,
           window=win,
           marks=marks)

The first problem I encounter is that an objects called pops, describing the populations of the window, is added to the ppp object. I understand how the values are derived, it is a poisson distribution given the input value mu, which can be any value and the total number of observations equal to points in the window.

seeds2<-ppp(x=x,
            y=y,
            window=win,
            marks=marks,
            pops=rpois(lambda=5,n=pmax(1,n.seeds)))

My first question is, how is it possible to add a variable that has no classification in the ppp object? I checked the ppp documentation and there is no mention of pops.

The second question I have is about using double variables, the next line requires an sapply function to define dimensions.

dim1<-pmax(1,sapply(seeds1$marks$pops, FUN=function(x)rpois(n=1,sqrt(x))))

I have never seen the $ function being used twice, and seeds2$marks$pop returns $ operator is invalid for atomic vectors. Could you explain what is going on here?

Many thanks.

Answer 1

That's several questions - please ask one question at a time.

From your post it is not clear whether you are trying to understand someone else's code, or developing code yourself. This makes a difference to the answer.

Just to clarify, this code does not come from inside the spatstat package; it is someone's code using the spatstat package to generate data. There is code in the spatstat package to generate simulated realisations of a Poisson cluster process (which is I think what you want to do), and you could look at the spatstat code for rPoissonCluster to see how it can be done correctly and efficiently.

The code you have shown here has numerous errors. But I will start by answering the two questions in your title.

1. The rules for creating ppp objects are set out in the help file for ppp. The help says that if the argument window is given, then unmatched arguments ... are ignored. This means that in the line seeds2<-ppp(x=x,y=y,window=win,marks=marks,pops=rpois(lambda=5,n=pmax(1,n.seeds))) the argument pops will be ignored.
2. The idiom sapply(seeds1$marks$pops, FUN=f) is perfectly valid syntax in R. If the object seeds1 is a structure or list which has a component named marks, which in turn is a structure or list which has a component named pops, then the idiom seeds1$marks$pops would extract it. This has nothing particularly to do with sapply.

Now turning to errors in the code,

• The line n.seeds<-lambda*win$xrange[2]*win$yrange[2] is presumably meant to calculate the expected number of cluster parents (cluster seeds) in the window. This would only work if the window is a rectangle with bottom left corner at the origin (0,0). It would be safer to write n.seeds <- lambda * area(win).
• However, the variable n.seeds is used later as it it were the number of cluster parents (cluster seeds). The author has forgotten that the number of seeds is random with a Poisson distribution. So, the more correct calculation would be n.seeds <- rpois(1, lambda * area(win))
• However this is still not correct because cluster parents (seed points) outside the window can also generate offspring points inside the window. So, seed points must actually be generated in a larger window obtained by expanding win. The appropriate command used inside spatstat to generate the cluster parents is bigwin <- grow.rectangle(Frame(win), cluster_diameter) ; Parents <- rpoispp(lambda, bigwin)
• The author apparently wants to assign two mark values to each parent point: a random angle and a random number pops. The correct way to do this is to make the marks a data frame with two columns, for example marks(seeds1) <- data.frame(angles=runif(n.seeds, max=2*pi), pops=rpois(n.seeds, 5))