NonlinearSolve.jl
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SciML
High-performance and differentiation-enabled nonlinear solvers (Newton methods), bracketed rootfinding (bisection, Falsi), with sparsity and Newton-Krylov support.
```jl using NonlinearSolve f(u, p) = u .* u .- 2.0 u0 = (1.0, 2.0) # brackets probB = NonlinearProblem(f, u0) solver = init(probB, Falsi()) # Can iterate the solver...
On 1.7 rc1: ```julia ┌ Warning: `vendor()` is deprecated, use `BLAS.get_config()` and inspect the output instead │ caller = (::NonlinearSolve.DefaultLinSolve)(x::Vector{Float64}, A::Matrix{Float64}, b::Vector{Float64}, update_matrix::Bool; tol::Nothing, kwargs::Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}) at...
Maybe NonlinearSolve.jl should wrap https://github.com/JuliaNLSolvers/NLSolvers.jl?
The link to the stable docs in the ReadMe, https://nonlinearsolve.sciml.ai/stable/, is broken (404). The dev link works, as does https://nonlinearsolve.sciml.ai/.
It seems that (parts of) the library won't work with 1D CUDA arrays, but with higher dimensional arrays it does. ```Julia using NonlinearSolve, CUDA CUDA.allowscalar(false) f(u,p) = u .* u...
It would be nice to have a section in the documentation for different stopping conditions. The only way I was able to dig the information out was with `methods(solve)`. Things...
Check out the following example: ``` julia> using NonlinearSolve, LinearAlgebra julia> f(u,p) = u .* u .- p; julia> u0 = [1.0, 1.0]; julia> p = 2.0; julia> probN =...