I am using the coala R-package to do coalescent simulations, and I was wondering if someone knows how to easily implement a stepping-stone migration model?

A reproducible example: 4 linearly distributed populations exchange migrants according to stepping-stone pattern (only the adjacent populations).

model <- coal_model(sample_size = c(5, 5, 5, 5), # sample 5 ind from every pop
                                   loci_number = 1,
                                   loci_length = 10,
                                    ploidy = 1) +
feat_mutation(rate = mut_rate, # e.g. 0.1
                       model = "HKY",
                       base_frequencies = c(0.25,0.25,0.25,0.25),
                       tstv_ratio = 4) +
feat_migration(mig_rate, 1, 2) + # mig_rate can be e.g. 0.5
feat_migration(mig_rate, 2, 1) +
feat_migration(mig_rate, 2, 3) +
feat_migration(mig_rate, 3, 2) +
feat_migration(mig_rate, 3, 4) +
feat_migration(mig_rate, 4, 3) +
sumstat_dna(name = "dna", transformation = identity)

This example works, but the downside is that I have to write two new lines for every pair of populations that exchange individuals. It is fine for a small number of populations, but I want to do a large simulation with about 70 populations. Does someone has a good idea how to automate this? The documentation has not helped me so far.

I tried two things that didn't work:

feat_migration(mig_rate, c(1,2,2,3,3,4), c(2,1,3,2,4,3))

and something like this:

migration_model <- function(){
  for(i in 1:n_pops){
    feat_migration(mig_rate, i, i+1) +
    feat_migration(mig_rate, i+1, i))
}

In the latter case, I don't really know how I can correctly create and parse all functions correctly into my model.

Good ideas are very welcome! :)