Revamp AnimalBreeding platform implementation - #8
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| animals = sort!(collect(ancestors); by = x -> (_pedigree_depth(x, pedmap), x)) | ||
| index = Dict(animal => i for (i, animal) in enumerate(animals)) | ||
| n = length(animals) | ||
| A = zeros(Float64, n, n) | ||
| for (animal, i) in pairs(index) | ||
| sire, dam = get(pedmap, animal, (nothing, nothing)) | ||
| sidx = sire === nothing ? 0 : get(index, sire, 0) | ||
| didx = dam === nothing ? 0 : get(index, dam, 0) | ||
| for j in 1:i-1 | ||
| val = 0.5 * ((sidx == 0 ? 0.0 : A[sidx, j]) + (didx == 0 ? 0.0 : A[didx, j])) |
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The additive relationship matrix is built by looping over pairs(index), but dictionaries in Julia are unordered. When an offspring row is processed before its parents, the loop uses zero rows for the parents in A[sidx, :] and A[didx, :], producing incorrect relationship coefficients that are never corrected later. Iterating the animals vector directly (which was already sorted by pedigree depth) avoids this nondeterministic ordering and ensures ancestors are filled before descendants.
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Summary
AnimalBreedingand rewrite the data management, modeling, evaluation, Bayesian, machine learning, interface, and performance modules into production-ready implementationsTesting
julia --project -e 'using Pkg; Pkg.test()'(fails: julia binary not available in container)https://chatgpt.com/codex/tasks/task_e_68dca407c6ec8321b696c1ef8e260d01