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Merge pull request #538 from SciML/nllstoopt
Add constructor to convert NLLS to OptimizationProblem
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using NonlinearSolve, Optimization, OptimizationNLopt, ForwardDiff | ||
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true_function(x, θ) = @. θ[1] * exp(θ[2] * x) * cos(θ[3] * x + θ[4]) | ||
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θ_true = [1.0, 0.1, 2.0, 0.5] | ||
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x = [-1.0, -0.5, 0.0, 0.5, 1.0] | ||
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y_target = true_function(x, θ_true) | ||
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function loss_function(θ, p) | ||
ŷ = true_function(p, θ) | ||
return ŷ .- y_target | ||
end | ||
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θ_init = θ_true .+ randn!(similar(θ_true)) * 0.1 | ||
prob_oop = NonlinearLeastSquaresProblem{false}(loss_function, θ_init, x) | ||
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solver = LevenbergMarquardt() | ||
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@time sol = solve(prob, solver; maxiters = 10000, abstol = 1e-8) | ||
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optf = OptimizationFunction(prob_oop.f, AutoForwardDiff()) | ||
optprob = OptimizationProblem(optf, prob_oop.u0, prob_oop.p) | ||
@time sol = solve(optprob, NLopt.LD_LBFGS(); maxiters = 10000, abstol = 1e-8) | ||
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optprob = OptimizationProblem(prob_oop, AutoForwardDiff()) | ||
@time sol = solve(optprob, NLopt.LD_LBFGS(); maxiters = 10000, abstol = 1e-8) |