Remove NLsolve dependency in favor of SimpleNonlinearSolve

Project.toml

@@ -19,7 +19,6 @@ LevyArea = "2d8b4e74-eb68-11e8-0fb9-d5eb67b50637"
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
 Logging = "56ddb016-857b-54e1-b83d-db4d58db5568"
 MuladdMacro = "46d2c3a1-f734-5fdb-9937-b9b9aeba4221"
-NLsolve = "2774e3e8-f4cf-5e23-947b-6d7e65073b56"
 OrdinaryDiffEqCore = "bbf590c4-e513-4bbe-9b18-05decba2e5d8"
 OrdinaryDiffEqDifferentiation = "4302a76b-040a-498a-8c04-15b101fed76b"
 OrdinaryDiffEqNonlinearSolve = "127b3ac7-2247-4354-8eb6-78cf4e7c58e8"
@@ -28,6 +27,7 @@ RecursiveArrayTools = "731186ca-8d62-57ce-b412-fbd966d074cd"
 Reexport = "189a3867-3050-52da-a836-e630ba90ab69"
 SciMLBase = "0bca4576-84f4-4d90-8ffe-ffa030f20462"
 SciMLOperators = "c0aeaf25-5076-4817-a8d5-81caf7dfa961"
+SimpleNonlinearSolve = "727e6d20-b764-4bd8-a329-72de5adea6c7"
 SparseArrays = "2f01184e-e22b-5df5-ae63-d93ebab69eaf"
 StaticArrays = "90137ffa-7385-5640-81b9-e52037218182"
 UnPack = "3a884ed6-31ef-47d7-9d2a-63182c4928ed"
@@ -49,7 +49,6 @@ LinearAlgebra = "1.6"
 Logging = "1.6"
 ModelingToolkit = "10"
 MuladdMacro = "0.2.1"
-NLsolve = "4"
 OrdinaryDiffEq = "6.87"
 OrdinaryDiffEqCore = "1.32.0"
 OrdinaryDiffEqDifferentiation = "1.9"
@@ -59,6 +58,7 @@ RecursiveArrayTools = "2, 3"
 Reexport = "0.2, 1.0"
 SciMLBase = "2.115"
 SciMLOperators = "0.2.9, 0.3, 0.4, 1"
+SimpleNonlinearSolve = "2"
 SparseArrays = "1.6"
 StaticArrays = "0.11, 0.12, 1.0"
 UnPack = "0.1, 1.0"

src/StochasticDiffEq.jl

@@ -21,7 +21,7 @@ import OrdinaryDiffEqCore: default_controller, isstandard, ispredictive,
 
 using UnPack, RecursiveArrayTools, DataStructures
 using DiffEqNoiseProcess, Random, ArrayInterface
-using NLsolve, ForwardDiff, StaticArrays, MuladdMacro, FiniteDiff, Base.Threads
+using SimpleNonlinearSolve, ForwardDiff, StaticArrays, MuladdMacro, FiniteDiff, Base.Threads
 using Adapt
 
 import DiffEqBase: ODE_DEFAULT_NORM, ODE_DEFAULT_ISOUTOFDOMAIN,

src/misc_utils.jl

@@ -32,11 +32,28 @@ end
 struct NLSOLVEJL_SETUP{CS, AD} end
 Base.@pure NLSOLVEJL_SETUP(; chunk_size = 0, autodiff = true) = NLSOLVEJL_SETUP{
     chunk_size, autodiff}()
-(::NLSOLVEJL_SETUP)(f, u0; kwargs...) = (res = NLsolve.nlsolve(f, u0; kwargs...); res.zero)
+
+# Wrapper to store the function for use with SimpleNonlinearSolve
+struct IIFNLSolveFunc{F}
+    f::F
+end
+
+function (p::NLSOLVEJL_SETUP{CS, AD})(f_wrapper::IIFNLSolveFunc, u0; kwargs...) where {
+        CS, AD}
+    f = f_wrapper.f
+    # Create a NonlinearProblem-compatible function
+    # The IIF methods use f(resid, u) signature (in-place)
+    nlf = NonlinearFunction{true}((resid, u, p) -> (f(resid, u); nothing))
+    prob = NonlinearProblem(nlf, u0)
+    ad = AD ? AutoForwardDiff() : AutoFiniteDiff()
+    alg = SimpleTrustRegion(; autodiff = ad)
+    sol = solve(prob, alg)
+    return sol.u
+end
+
 function (p::NLSOLVEJL_SETUP{CS, AD})(::Type{Val{:init}}, f, u0_prototype) where {CS, AD}
-    AD ? autodiff = :forward : autodiff = :central
-    OnceDifferentiable(f, u0_prototype, u0_prototype, autodiff,
-        ForwardDiff.Chunk(determine_chunksize(u0_prototype, CS)))
+    # Return a wrapper that stores the function
+    IIFNLSolveFunc(f)
 end
 
 get_chunksize(x) = 0