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optimization_example.jl
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optimization_example.jl
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using Optim
using Random
function get_optimization_history(;
true_f, test_f, c0, c_bounds, alg=NelderMead(), iterations=10
)
n = 5_000
X = rand(MersenneTwister(0), n) .* 20 .- 10
Y = rand(MersenneTwister(1), n) .* 20 .- 10
Z = rand(MersenneTwister(2), n) .* 20 .- 10
nconst = length(c0)
function f(c; X, Y, Z, c_hist)
push!(c_hist, copy(c))
loss = sum([
abs2(true_f(x, y, z) - test_f(x, y, z; c=c)) for (x, y, z) in zip(X, Y, Z)
])
for i in 1:nconst
low = c_bounds[i][1]
high = c_bounds[i][2]
if c[i] < low
loss += 5 * (c[i] - low)^2
elseif c[i] > high
loss += 5 * (c[i] - high)^2
end
end
return loss
end
c_hist = [copy(c0)]
Random.seed!(3)
res = optimize(
c -> f(c; X, Y, Z, c_hist), c0, alg, Optim.Options(; iterations=iterations)
)
for _ in 1:ceil(Int, 0.1 * length(c_hist))
push!(c_hist, copy(res.minimizer))
end
c_hist = c_hist[findall(
c -> all([ci >= low && ci <= high for (ci, (low, high)) in zip(c, c_bounds)]),
c_hist,
)]
return c_hist
end