galen.jl

using Omega

# Add uncertainty to this if you want
region_size = 30_000 

# The number of groups
ngroups = uniform(1:region_size)

# Produced random Boolean correlation matrix
function correlation_model(rng, nprobes = 10)
  # Sample ids without replacement
  neuron_ids = Int[]

  while length(neuron_ids) < nprobes
    id = uniform(rng, 1:region_size)
    if id ∉ neuron_ids
      push!(neuron_ids, id)
    end
  end

  # Split the ids [1, 2, 3] into groups: [[1,2], ]
  region_id(i) = Int(floor(nprobes*i/region_size))
  issamegroup(i, j) = region_id(i) == region_id(j)

  correlated = [issamegroup(i,j) for i in neuron_ids, j in neuron_ids]
end

# THis is just omega stuff to turn function into random variable
correlation_model = ciid(correlation_model)

rand(correlation_model)