Fix SpeedMapping 0.4 compatibility (#747)

* CompatHelper: bump compat for SpeedMapping in [extras] to 0.4, (keep existing compat)

* Fix SpeedMapping 0.4 compatibility (drop 0.3 support)

SpeedMapping 0.4 introduced breaking API changes:
- `converged::Bool` -> `status::Symbol` in return type
- `tol` -> `abstol`
- `Lp` -> `pnorm`
- `store_info` -> `store_trace`
- `σ_min` -> `initial_learning_rate`
- `orders::Vector{Int}` -> `orders::Tuple`

This commit updates the extension to use the 0.4 API exclusively
and changes the compat entry from "0.3, 0.4" to "0.4".

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

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>

---------

Co-authored-by: CompatHelper Julia <compathelper_noreply@julialang.org>
Co-authored-by: ChrisRackauckas <me@chrisrackauckas.com>
Co-authored-by: Claude Opus 4.5 <noreply@anthropic.com>

Author: 4 people

Project.toml

@@ -1,7 +1,7 @@
 name = "NonlinearSolve"
 uuid = "8913a72c-1f9b-4ce2-8d82-65094dcecaec"
-authors = ["SciML"]
 version = "4.13.0"
+authors = ["SciML"]
 
 [deps]
 ADTypes = "47edcb42-4c32-4615-8424-f2b9edc5f35b"
@@ -43,13 +43,23 @@ SparseArrays = "2f01184e-e22b-5df5-ae63-d93ebab69eaf"
 SpeedMapping = "f1835b91-879b-4a3f-a438-e4baacf14412"
 Sundials = "c3572dad-4567-51f8-b174-8c6c989267f4"
 
-[sources]
-BracketingNonlinearSolve = {path = "lib/BracketingNonlinearSolve"}
-NonlinearSolveBase = {path = "lib/NonlinearSolveBase"}
-NonlinearSolveFirstOrder = {path = "lib/NonlinearSolveFirstOrder"}
-NonlinearSolveQuasiNewton = {path = "lib/NonlinearSolveQuasiNewton"}
-NonlinearSolveSpectralMethods = {path = "lib/NonlinearSolveSpectralMethods"}
-SimpleNonlinearSolve = {path = "lib/SimpleNonlinearSolve"}
+[sources.BracketingNonlinearSolve]
+path = "lib/BracketingNonlinearSolve"
+
+[sources.NonlinearSolveBase]
+path = "lib/NonlinearSolveBase"
+
+[sources.NonlinearSolveFirstOrder]
+path = "lib/NonlinearSolveFirstOrder"
+
+[sources.NonlinearSolveQuasiNewton]
+path = "lib/NonlinearSolveQuasiNewton"
+
+[sources.NonlinearSolveSpectralMethods]
+path = "lib/NonlinearSolveSpectralMethods"
+
+[sources.SimpleNonlinearSolve]
+path = "lib/SimpleNonlinearSolve"
 
 [extensions]
 NonlinearSolveFastLevenbergMarquardtExt = "FastLevenbergMarquardt"
@@ -106,14 +116,14 @@ Random = "1.10"
 ReTestItems = "1.24"
 Reexport = "1.2.2"
 ReverseDiff = "1.15"
-SciMLLogging = "1.3"
 SIAMFANLEquations = "1.0.1"
 SciMLBase = "2.127"
+SciMLLogging = "1.3"
 SimpleNonlinearSolve = "2.11"
 SparseArrays = "1.10"
 SparseConnectivityTracer = "1"
 SparseMatrixColorings = "0.4.5"
-SpeedMapping = "0.3"
+SpeedMapping = "0.4"
 StableRNGs = "1"
 StaticArrays = "1.9"
 StaticArraysCore = "1.4"
@@ -146,9 +156,9 @@ PolyesterForwardDiff = "98d1487c-24ca-40b6-b7ab-df2af84e126b"
 Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
 ReTestItems = "817f1d60-ba6b-4fd5-9520-3cf149f6a823"
 ReverseDiff = "37e2e3b7-166d-5795-8a7a-e32c996b4267"
-SciMLLogging = "a6db7da4-7206-11f0-1eab-35f2a5dbe1d1"
 SIAMFANLEquations = "084e46ad-d928-497d-ad5e-07fa361a48c4"
 SafeTestsets = "1bc83da4-3b8d-516f-aca4-4fe02f6d838f"
+SciMLLogging = "a6db7da4-7206-11f0-1eab-35f2a5dbe1d1"
 SparseConnectivityTracer = "9f842d2f-2579-4b1d-911e-f412cf18a3f5"
 SparseMatrixColorings = "0a514795-09f3-496d-8182-132a7b665d35"
 SpeedMapping = "f1835b91-879b-4a3f-a438-e4baacf14412"

ext/NonlinearSolveSpeedMappingExt.jl

@@ -29,8 +29,10 @@ function SciMLBase.__solve(
     time_limit = ifelse(maxtime === nothing, 1000, maxtime)
 
     sol = speedmapping(
-        u; m!, tol, Lp = Inf, maps_limit = maxiters, alg.orders,
-        alg.check_obj, store_info = store_trace isa Val{true}, alg.σ_min, alg.stabilize,
+        u; m!, abstol = tol, pnorm = Inf, maps_limit = maxiters,
+        orders = Tuple(alg.orders),
+        initial_learning_rate = alg.σ_min == 0.0 ? 1.0 : alg.σ_min,
+        store_trace = store_trace isa Val{true},
         time_limit
     )
     res = prob.u0 isa Number ? first(sol.minimizer) : sol.minimizer
@@ -39,7 +41,7 @@ function SciMLBase.__solve(
     return SciMLBase.build_solution(
         prob, alg, res, resid;
         original = sol, stats = SciMLBase.NLStats(sol.maps, 0, 0, 0, sol.maps),
-        retcode = ifelse(sol.converged, ReturnCode.Success, ReturnCode.Failure)
+        retcode = ifelse(sol.status == :first_order, ReturnCode.Success, ReturnCode.Failure)
     )
 end