CODEWITHSUNDEEP
rspatstat
jbeds
jbeds

Reputation: 17

Can't use mppm on multitype point patterns

I'm trying to fit a MultiStraussHardcore interaction to one of the sample datatsets in spatstat (flu). I'm maintaining the same interaction and hardcore radius for all types and point patterns. I'm running the following block:

library(spatstat)
library("optimbase")

flusubset <- flu[1:4]
typelist <- lapply(lapply(flusubset$pattern, marks), levels)
stopifnot(length(unique(typelist))==1)
num_marks <- length(typelist[[1]])
iradii <- 50*ones(num_marks)
hradii <- 3*ones(num_marks)
Int <- anylist()
for (i in 1:dim(flusubset)[1]) {
  Int[[i]] <- MultiStraussHard(iradii=iradii, hradii=hradii)
}
Int <- as.hyperframe(Int)
multmodel <- mppm(pattern ~ 1, data=flusubset, interaction=Int)

Each time I run mppm, I get the following error

Error in (function (d, tx, tu, par) : data and model do not have the same possible levels of marks

I've included the traceback, too.

12. stop("data and model do not have the same possible levels of marks")
11. (function (d, tx, tu, par) { r <- par$iradii h <- par$hradii ...
10. do.call(fun, usedargs)
9. do.call.matched(pairpot, list(d = matrix(, 0, 0), tx = marks(X)[integer(0)], tu = marks(P)[integer(0)], par = potpars))
8. evalPairPotential(X, U, EqualPairs, pairpot, potpars, Reach)
7. evaluate(X, P, E, interaction$pot, interaction$par, correction = correction, splitInf = splitInf, ..., Reach = Reach, precomputed = precomputed, savecomputed = savecomputed)
6. evalInterEngine(X = X, P = P, E = E, interaction = interaction, correction = correction, splitInf = splitInf, ..., precomputed = precomputed, savecomputed = savecomputed)
5. evalInteraction(X, P, E, interaction, correction, ..., splitInf = splitInf, precomputed = precomputed, savecomputed = savecomputed)
4. mpl.prepare(Q, X, P, trend, interaction, covariates, want.trend, want.inter, correction, rbord, "quadrature points", callstring, subsetexpr = subsetexpr, allcovar = allcovar, precomputed = precomputed, savecomputed = savecomputed, covfunargs = covfunargs, weightfactor = weightfactor, ...
3. mpl.engine(Q, trend = trend, interaction = interaction, ..., covariates = covariates, correction = correction, rbord = rbord, use.gam = use.gam, allcovar = allcovar, preponly = TRUE, forcefit = TRUE)
2. bt.frame(Yi, ~1, inter, ..., covariates = covariates, allcovar = TRUE, use.gam = use.gam, vnamebase = itags[j], vnameprefix = itags[j])
1. mppm(pattern ~ 1, data = flusubset, interaction = Int)

I've tried fitting a MultiStraussHardcore model with ppm for each individual point pattern, and I have no issues. I've confirmed that the possible levels of each point pattern are identical. I've also verified that the interaction and hardcore radii matrices have the correct dimensions (2x2 for both) and that my hyperframe containing the interact objects is the correct dimensions. Thanks!

Upvotes: 1

Views: 107

Answers (2)

Adrian Baddeley
Adrian Baddeley

Reputation: 2973

This has been fixed in the latest development version of spatstat available from the github repository

Upvotes: 0

Ege Rubak
Ege Rubak

Reputation: 4507

Thank you for the well described problem and the reproducible example. It made things very easy for me.

Indeed you have found a minor bug (documentation inconsistency). Your code runs without errors if, in the for loop, you replace

MultiStraussHard(iradii=iradii, hradii=hradii)

by

typ <- levels(marks(flu$pattern[[1]]))
MultiStraussHard(iradii=iradii, hradii=hradii, types=typ)

The documentation for MultiStraussHard says that the argument types is optional, but that is only true for ppm calls at the moment. I will see if it is possible to extend the auto detection of types to mppm, so your original code would work in future versions of spatstat.

Upvotes: 0

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