Oscar Dowson
Oscar Dowson
Closing as a duplicate of https://github.com/JuliaDocs/Documenter.jl/issues/858
@eggix: it might step out of bounds during the search, but the final solution respects the bounds? I still can't reproduce the original error in the first post.
You could try pass `Inf` as the objective value when the solution is out of bounds. But for some algorithms that might cause issues. In general though, you should expect...
Closing as stale, and because the error has since been improved. It is now: ```julia julia> using NLopt julia> count = 0 # keep track of # function evaluations 0...
Closing because this seems to work fine. ```julia julia> count = 0 0 julia> using NLopt julia> function myfunc(x::Vector, grad::Vector) global count count::Int += 1 res = sqrt(x[2]) return res...
Closing as a duplicate of https://github.com/JuliaOpt/NLopt.jl/issues/186.
Here's a similar issue with a example using pmap https://github.com/JuliaOpt/NLopt.jl/issues/146
Closing in favor of #194
So the issue is that the derivatives aren't defined at the default starting point of `0.0`. It seems like for this algorithm NLopt just lets NaN accumulate and doesn't error....
> What should I do when fx, gx and hx come from one calculation Use a closure or some sort of cache. ```julia using NLopt function f_and_g(x::Vector, ∇f::Vector, g::Vector, ∇g::Matrix)...