Arno Strouwen
Arno Strouwen
Should configurable options for outer solve such as "outer_iterations" be documented here? https://julianlsolvers.github.io/Optim.jl/stable/#user/config/
Is there any documentation on the KrylovTrustRegion method? I can only find NewtonTrustRegion.
Some packages such as `DifferentialEquations.jl` require you to manually provide `Dual` numbers for trickier problems. When you have nested differentiation in such a situation you also need to provide ordering...
Is it possible to use jacobian coloring from SparseDiffTools in places like https://github.com/SciML/Optimization.jl/blob/24ad25d3e75816d454349156a7ac6bb094223ad2/src/function/zygote.jl#L44-L45
https://galacticoptim.sciml.ai/stable/API/optimization_function/#Defining-Optimization-Functions-Via-AD ```jl julia> GalacticOptim.AutoReverseDiff(compile=true) ERROR: MethodError: no method matching GalacticOptim.AutoReverseDiff(; compile=true) Closest candidates are: GalacticOptim.AutoReverseDiff() at C:\Users\arno\.julia\packages\GalacticOptim\lVdNA\src\function\reversediff.jl:1 got unsupported keyword argument "compile" Stacktrace: [1] top-level scope @ REPL[172]:1 ```
From the documentation: _batch: The preferred number of points to batch. This allows user-side parallelization of the integrand. If batch != 0, then each x[:,i] is a different point of...
```jl function update_func(A,u,p,t) A[1,1] = 0 A[2,1] = sin(u[1]) A[1,2] = -1 A[2,2] = 0 end A = DiffEqArrayOperator(ones(2,2),update_func=update_func) prob = ODEProblem(A, ones(2), (0, 30.)) sol = solve(prob,LieRK4(),dt=1/4) # works...
Should it work like this? ```jl using OrdinaryDiffEq f(u,p,t) = 1.01*u u0 = 1/2 tspan = (0.0,1.0) prob = ODEProblem(f,u0,tspan) sol = solve(prob, Tsit5(), saveat=[0.0,0.0,0.5,0.5,1.0,1.0]) println(sol.t) [0.0, 0.5, 0.5, 1.0,...