Obtain values from simulated mppm in spatstat - r

Question

I have obtained an mppm object by fitting a model on several independent datasets using the mppm function from the R package spatstat. How can I generate simulated realisations of this model and obtain the x, y, and marks attributes of the simulations ?
I fitted my model as such:
data <- listof(NMJ1,NMJ2,NMJ3)
data <- hyperframe(X=1:3, Points=data)
model <- mppm(Points ~marks*sqrt(x^2+y^2), data)
where NMJ1, NMJ2, and NMJ3 are marked ppp and are independent realisations of the same experiment.
sim <- simulate(model) allows me to generate simulated realisations of this model, and plot(sim,axes = TRUE) to plot them. sim itself is an hyperframe object:
> sim
Hyperframe:
Sim1
1 (ppp)
2 (ppp)
3 (ppp)
How can I access the values (x, y, and marks) in this hyperframe ? My goal is to generate a large number of independent realisations from my model, and to use the simulated values for another task. Is there a practical way to obtain, retrieve and save these values ?

Answer 1

Since you say you want to simulate this many times I have here shown the code
with two simulations (rather than one as you have in the question):
library(spatstat)
data <- list(amacrine, amacrine, amacrine)
data <- hyperframe(X=1:3, Points=data)
model <- mppm(Points ~marks*sqrt(x^2+y^2), data)
sim <- simulate(model, nsim = 2)
#> Generating simulated realisations of 3 models..
#> 1, 2, 3.
Now sim is a hyperframe with 2 columns (one for each simulation). Each
column is a list of 3 point patterns. To get the three sets of coordinates
and marks for the first simulation use as.data.frame on each point pattern:
co1 <- lapply(sim$Sim1, as.data.frame)
Then co1 is a list of length 3, and we can print out the first few
coordinates with the head() command, e.g. the coordinates of the third
point pattern:
head(co1[[3]])
#> x y marks
#> 1 0.4942587 0.7889985 off
#> 2 0.6987270 0.7637359 on
#> 3 0.3926415 0.6819965 on
#> 4 0.7982686 0.9060733 off
#> 5 1.3507722 0.9731363 on
#> 6 0.6450985 0.6924126 on
We can extract the coordinates and marks for each simulation by another lapply that
runs over every simulation (in this case 2):
co <- lapply(sim, function(x) lapply(x, as.data.frame))
Now co is a list with 2 elements, and each element is a list of 3 sets of
coordinates:
length(co)
#> [1] 2
length(co[[2]])
#> [1] 3
head(co[[2]][[3]])
#> x y marks
#> 1 0.1660580 0.04180501 on
#> 2 0.7840025 0.71727782 on
#> 3 1.2011733 0.17109112 on
#> 4 1.0429867 0.49284639 on
#> 5 1.1411869 0.86711072 off
#> 6 1.0375942 0.06427601 on