Depend only on NonlinearSolveFirstOrder

This has everything needed for the default polyalgorithm.

Author: JamesWrigley

Project.toml

@@ -1,6 +1,6 @@
 name = "CurveFit"
 uuid = "5a033b19-8c74-5913-a970-47c3779ef25c"
-version = "1.4.0"
+version = "1.4.1"
 authors = ["Paulo José Saiz Jabardo <pjabardo@gmail.com>, Avik Pal <avikpal@mit.edu> and contributors"]
 
 [deps]
@@ -15,8 +15,8 @@ InverseFunctions = "3587e190-3f89-42d0-90ee-14403ec27112"
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
 LinearSolve = "7ed4a6bd-45f5-4d41-b270-4a48e9bafcae"
 Markdown = "d6f4376e-aef5-505a-96c1-9c027394607a"
-NonlinearSolve = "8913a72c-1f9b-4ce2-8d82-65094dcecaec"
 NonlinearSolveBase = "be0214bd-f91f-a760-ac4e-3421ce2b2da0"
+NonlinearSolveFirstOrder = "5959db7a-ea39-4486-b5fe-2dd0bf03d60d"
 RecursiveArrayTools = "731186ca-8d62-57ce-b412-fbd966d074cd"
 SciMLBase = "0bca4576-84f4-4d90-8ffe-ffa030f20462"
 Setfield = "efcf1570-3423-57d1-acb7-fd33fddbac46"
@@ -36,8 +36,8 @@ InverseFunctions = "0.1"
 LinearAlgebra = "1.10"
 LinearSolve = "3.15.0"
 Markdown = "1.10.0"
-NonlinearSolve = "4.12.0"
 NonlinearSolveBase = "2.0"
+NonlinearSolveFirstOrder = "1.12"
 RecursiveArrayTools = "3.33.0"
 SciMLBase = "2.90"
 Setfield = "1.1.2"

docs/src/_changelog.md

@@ -7,6 +7,12 @@ CurrentModule = CurveFit
 This documents notable changes in CurveFit.jl. The format is based on [Keep a
 Changelog](https://keepachangelog.com).
 
+## [v1.4.1] - 2026-02-14
+
+### Changed
+- CurveFit now depends only on NonlinearSolveFirstOrder.jl to reduce
+  dependencies ([#85]). The default algorithm remains the same.
+
 ## [v1.4.0] - 2026-01-31
 
 ### Added

src/CurveFit.jl

@@ -9,8 +9,7 @@ using Setfield: @set!
 using RecursiveArrayTools: NamedArrayPartition
 using FastRationals: FastRational
 using LinearAlgebra: LinearAlgebra, eigvals!, diagm, qr!, lu!, ldiv!
-using LinearSolve: LinearSolve
-using NonlinearSolve: NonlinearSolve
+using NonlinearSolveFirstOrder: NonlinearSolveFirstOrder
 using NonlinearSolveBase: NonlinearSolveBase
 using SciMLBase: SciMLBase, AbstractNonlinearAlgorithm, AbstractLinearAlgorithm, ReturnCode,
     NonlinearFunction, LinearProblem, NonlinearLeastSquaresProblem, reinit!

test/generic.jl

@@ -17,7 +17,7 @@ end
 @testitem "GenericNonlinearCurveFitCache show" begin
     using CurveFit
     using SciMLBase
-    using NonlinearSolve: LevenbergMarquardt, GaussNewton, TrustRegion
+    using NonlinearSolveFirstOrder: LevenbergMarquardt, GaussNewton, TrustRegion
 
     x = collect(1.0:10.0)
     fn(a, x) = @. a[1] + a[2] * x

test/king.jl

@@ -20,7 +20,7 @@
 end
 
 @testitem "Modified King's Law" begin
-    using NonlinearSolve
+    using NonlinearSolveFirstOrder
 
     U = range(1, stop = 20, length = 20)
     A = 5.0

test/lin_choice.jl

@@ -1,7 +1,8 @@
 @testitem "Linear solver choice testing" begin
     @testset "LUFactorization" begin
         using CurveFit
-        using NonlinearSolve
+        using LinearSolve
+        using NonlinearSolveFirstOrder
 
         X = collect(1.0:10.0)
         θ_true = [3.0, 2.0]
@@ -23,7 +24,8 @@
 
     @testset "QRFactorization" begin
         using CurveFit
-        using NonlinearSolve
+        using LinearSolve
+        using NonlinearSolveFirstOrder
 
         X = collect(1.0:10.0)
         θ_true = [3.0, 2.0]
@@ -45,7 +47,8 @@
 
     @testset "CholeskyFactorization" begin
         using CurveFit
-        using NonlinearSolve
+        using LinearSolve
+        using NonlinearSolveFirstOrder
 
         X = collect(1.0:10.0)
         θ_true = [3.0, 2.0]

test/rationalfit.jl

@@ -16,7 +16,7 @@
 end
 
 @testitem "Nonlinear Rational fit" begin
-    using NonlinearSolve
+    using NonlinearSolveFirstOrder
 
     x = range(1, stop = 10, length = 10)
     r = CurveFit.RationalPolynomial([1.0, 0.0, -2.0], [1.0, 2.0, 3.0])

test/stats.jl

@@ -1,6 +1,6 @@
 @testitem "StatsAPI Integration" begin
     using StatsAPI
-    using NonlinearSolve
+    using NonlinearSolveFirstOrder
     using LinearAlgebra
     using LinearSolve