From f7cb759c42b8a5ef3a8fe5615dbd698bde0310d2 Mon Sep 17 00:00:00 2001
From: ChrisRackauckas <me@chrisrackauckas.com>
Date: Wed, 3 Dec 2025 19:33:25 -0500
Subject: [PATCH] Remove NLsolve dependency in favor of SimpleNonlinearSolve
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Replace the direct NLsolve.jl dependency with SimpleNonlinearSolve.jl
for the IIF methods (IIF1M, IIF2M, IIF1Mil). This follows the same
approach taken in OrdinaryDiffEq.jl (PR #2081).

Changes:
- Remove NLsolve from dependencies and compat
- Add SimpleNonlinearSolve to dependencies and compat
- Update NLSOLVEJL_SETUP to use SimpleTrustRegion instead of NLsolve.nlsolve
- Replace OnceDifferentiable wrapper with a simple function wrapper

The implicit methods that use OrdinaryDiffEqNonlinearSolve (ImplicitEM,
ISSEM, SKenCarp, etc.) are unaffected as they already use NonlinearSolve
internally.

Closes #642

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>
---
 Project.toml            |  4 ++--
 src/StochasticDiffEq.jl |  2 +-
 src/misc_utils.jl       | 25 +++++++++++++++++++++----
 3 files changed, 24 insertions(+), 7 deletions(-)

diff --git a/Project.toml b/Project.toml
index 12d5b5dfd..0a4285155 100644
--- a/Project.toml
+++ b/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"
diff --git a/src/StochasticDiffEq.jl b/src/StochasticDiffEq.jl
index 9382ced4f..038d972ae 100644
--- a/src/StochasticDiffEq.jl
+++ b/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,
diff --git a/src/misc_utils.jl b/src/misc_utils.jl
index 9ab52ac24..5d252b77a 100644
--- a/src/misc_utils.jl
+++ b/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