chore: fix QA testing

SciML · Oct 22, 2024 · 89d76b0 · 89d76b0
1 parent 0b91de7
commit 89d76b0
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Showing 4 changed files with 19 additions and 10 deletions.
diff --git a/lib/BracketingNonlinearSolve/test/qa_tests.jl b/lib/BracketingNonlinearSolve/test/qa_tests.jl
@@ -10,7 +10,8 @@ end
     import ForwardDiff
     using ExplicitImports, BracketingNonlinearSolve
 
-    @test check_no_implicit_imports(BracketingNonlinearSolve; skip = (Base, Core)) === nothing
+    @test check_no_implicit_imports(BracketingNonlinearSolve; skip = (Base, Core)) ===
+          nothing
     @test check_no_stale_explicit_imports(BracketingNonlinearSolve) === nothing
     @test check_all_qualified_accesses_via_owners(BracketingNonlinearSolve) === nothing
 end
diff --git a/src/NonlinearSolve.jl b/src/NonlinearSolve.jl
@@ -13,14 +13,14 @@ using LinearAlgebra: LinearAlgebra, ColumnNorm, Diagonal, I, LowerTriangular, Sy
                      UpperTriangular, axpy!, cond, diag, diagind, dot, issuccess, istril,
                      istriu, lu, mul!, norm, pinv, tril!, triu!
 using LineSearch: LineSearch, AbstractLineSearchCache, LineSearchesJL, NoLineSearch,
-                  RobustNonMonotoneLineSearch, BackTracking,  LiFukushimaLineSearch
+                  RobustNonMonotoneLineSearch, BackTracking, LiFukushimaLineSearch
 using LinearSolve: LinearSolve, QRFactorization, needs_concrete_A, AbstractFactorization,
                    DefaultAlgorithmChoice, DefaultLinearSolver
 using MaybeInplace: @bb
 using NonlinearSolveBase: NonlinearSolveBase, nonlinearsolve_forwarddiff_solve,
                           nonlinearsolve_dual_solution, nonlinearsolve_∂f_∂p,
-                          nonlinearsolve_∂f_∂u, L2_NORM, AbstractNonlinearTerminationMode,
-                          AbstractSafeNonlinearTerminationMode,
+                          nonlinearsolve_∂f_∂u, L2_NORM, AbsNormTerminationMode,
+                          AbstractNonlinearTerminationMode,
                           AbstractSafeBestNonlinearTerminationMode
 using Printf: @printf
 using Preferences: Preferences, @load_preference, @set_preferences!

diff --git a/src/abstract_types.jl b/src/abstract_types.jl
@@ -382,7 +382,8 @@ Abstract Type for all Approximate Jacobian Update Rules used in NonlinearSolve.j
 ```julia
 __internal_init(
     prob::AbstractNonlinearProblem, alg::AbstractApproximateJacobianUpdateRule, J, fu, u,
-    du, args...; internalnorm::F = L2_NORM, kwargs...) where {F} --> AbstractApproximateJacobianUpdateRuleCache{INV}
+    du, args...; internalnorm::F = L2_NORM, kwargs...) where {F} -->
+AbstractApproximateJacobianUpdateRuleCache{INV}
 ```
 """
 abstract type AbstractApproximateJacobianUpdateRule{INV} end

diff --git a/test/core/rootfind_tests.jl b/test/core/rootfind_tests.jl
@@ -1,8 +1,8 @@
 @testsetup module CoreRootfindTesting
 using Reexport
 @reexport using BenchmarkTools, LinearSolve, NonlinearSolve, StaticArrays, Random,
-                LinearAlgebra, ForwardDiff, Zygote, Enzyme, DiffEqBase,
-                SparseConnectivityTracer
+                LinearAlgebra, ForwardDiff, Zygote, Enzyme, SparseConnectivityTracer,
+                NonlinearSolveBase
 using LineSearches: LineSearches
 
 _nameof(x) = applicable(nameof, x) ? nameof(x) : _nameof(typeof(x))
@@ -22,9 +22,16 @@ function newton_fails(u, p)
 end
 
 const TERMINATION_CONDITIONS = [
-    NormTerminationMode(), RelTerminationMode(), RelNormTerminationMode(),
-    AbsTerminationMode(), AbsNormTerminationMode(), RelSafeTerminationMode(),
-    AbsSafeTerminationMode(), RelSafeBestTerminationMode(), AbsSafeBestTerminationMode()]
+    NormTerminationMode(Base.Fix1(maximum, abs)),
+    RelTerminationMode(),
+    RelNormTerminationMode(Base.Fix1(maximum, abs)),
+    RelNormSafeTerminationMode(Base.Fix1(maximum, abs)),
+    RelNormSafeBestTerminationMode(Base.Fix1(maximum, abs)),
+    AbsTerminationMode(),
+    AbsNormTerminationMode(Base.Fix1(maximum, abs)),
+    AbsNormSafeTerminationMode(Base.Fix1(maximum, abs)),
+    AbsNormSafeBestTerminationMode(Base.Fix1(maximum, abs))
+]
 
 function benchmark_nlsolve_oop(f, u0, p = 2.0; solver, kwargs...)
     prob = NonlinearProblem{false}(f, u0, p)