A better way to chose a random neighbor

I am building a kind of cellular automata and I have a matrix and I would like to choose a random neighbour of a random position, the following is the way I found I wonder if there is a better more efficient way of doing it:

fil = 10
col = 10
m =  zeros(Int16,fil,col)
m[:,1] .= 1

neighborhood = ((0,1),(0,-1),(1,0),(-1,0) )

for z in 1:length(m)
    i= rand(1:fil) 
    j= rand(1:col)
    if m[i,j]==1
        x=[i,j] .+  rand(neighborhood)

        # check boundaries
        if !(x[1] > fil || x[1] <1 || x[2] > col || x[2]<1)
           m[x[1],x[2]] =  1 

This allocates an array [i,j] on every iteration. Better to use a tuple (i,j) .+ rand(neighborhood).

I would usually recommend employing ghost cells to avoid these kinds of boundary checks in inner loops.


Thanks! is there an example of how to implement ghost cells?

Anyways that would work for closest neighbours if I have a function that gives a random position with an arbitrary maximum distance e.g.

 x=(i,j) .+  rand_max_distance(fil)

will be more difficult to avoid boundary checks, and something similar would happen with periodic boundary conditions, you would need to use getindex(a, i) = a.a[i % n] as you suggested to avoid in Arrays with periodic boundaries - #4 by stevengj

The “ghost cells” link above has an example. Here is another example, and here is another.

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