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fix: misc test group
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avik-pal committed Oct 21, 2024
1 parent e7b1a30 commit 29bd85c
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Showing 2 changed files with 3 additions and 15 deletions.
13 changes: 3 additions & 10 deletions src/NonlinearSolve.jl
Original file line number Diff line number Diff line change
Expand Up @@ -17,11 +17,9 @@ using LazyArrays: LazyArrays, ApplyArray, cache
using LinearAlgebra: LinearAlgebra, ColumnNorm, Diagonal, I, LowerTriangular, Symmetric,
UpperTriangular, axpy!, cond, diag, diagind, dot, issuccess, istril,
istriu, lu, mul!, norm, pinv, tril!, triu!
using LineSearch: LineSearch, AbstractLineSearchAlgorithm, AbstractLineSearchCache,
NoLineSearch, RobustNonMonotoneLineSearch, BackTracking, LineSearchesJL,
LiFukushimaLineSearch
using LinearSolve: LinearSolve, LUFactorization, QRFactorization,
needs_concrete_A, AbstractFactorization,
using LineSearch: LineSearch, AbstractLineSearchCache, LineSearchesJL, NoLineSearch,
RobustNonMonotoneLineSearch, BackTracking, LiFukushimaLineSearch
using LinearSolve: LinearSolve, QRFactorization, needs_concrete_A, AbstractFactorization,
DefaultAlgorithmChoice, DefaultLinearSolver
using MaybeInplace: @bb
using Printf: @printf
Expand Down Expand Up @@ -110,10 +108,8 @@ include("default.jl")
NewtonRaphson(),
TrustRegion(),
LevenbergMarquardt(),
# PseudoTransient(),
Broyden(),
Klement(),
# DFSane(),
nothing
)

Expand All @@ -139,9 +135,6 @@ include("default.jl")
LevenbergMarquardt(),
GaussNewton(),
TrustRegion(),
# LevenbergMarquardt(; linsolve = LUFactorization()),
# GaussNewton(; linsolve = LUFactorization()),
# TrustRegion(; linsolve = LUFactorization()),
nothing
)

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5 changes: 0 additions & 5 deletions test/misc/bruss_tests.jl
Original file line number Diff line number Diff line change
Expand Up @@ -52,11 +52,6 @@
sol = solve(prob_brusselator_2d_sparse, NewtonRaphson(); abstol = 1e-8)
@test norm(sol.resid, Inf) < 1e-8

# Deprecated
sol = solve(prob_brusselator_2d,
NewtonRaphson(autodiff = AutoSparse(AutoFiniteDiff())); abstol = 1e-8)
@test norm(sol.resid, Inf) < 1e-8

f! = (du, u) -> brusselator_2d_loop(du, u, p)
du0 = similar(u0)
jac_prototype = ADTypes.jacobian_sparsity(f!, du0, u0, TracerSparsityDetector())
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