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Created Aug 10, 2019
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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)
# 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]
# THis is just omega stuff to turn function into random variable
correlation_model = ciid(correlation_model)
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