Format for JuliaFormatter v2 #613

ChrisRackauckas · 2025-05-13T02:38:28Z

No description provided.

github-actions

Remaining comments which cannot be posted as a review comment to avoid GitHub Rate Limit

JuliaFormatter

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/lib/NonlinearSolveFirstOrder/test/rootfind_tests.jl

Line 157 in 8fdee10

p=range(0.01, 2, length = 200)

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/lib/NonlinearSolveFirstOrder/test/rootfind_tests.jl

Lines 169 to 171 in 8fdee10

    
           @testset "TC: $(nameof(typeof(termination_condition)))" for termination_condition in 
        
                                                                       TERMINATION_CONDITIONS

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/lib/NonlinearSolveFirstOrder/test/rootfind_tests.jl

Line 187 in 8fdee10

radius_update_schemes=[

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/lib/NonlinearSolveFirstOrder/test/rootfind_tests.jl

Line 228 in 8fdee10

p=range(0.01, 2, length = 200)

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/lib/NonlinearSolveFirstOrder/test/rootfind_tests.jl

Lines 234 to 236 in 8fdee10

    
           u0=[-10.0, -1.0, 1.0, 2.0, 3.0, 4.0, 10.0] 
        
           p=[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0] 
        
           sol=solve_oop(newton_fails, u0, p; solver = TrustRegion())

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/lib/NonlinearSolveFirstOrder/test/rootfind_tests.jl

Lines 242 to 251 in 8fdee10

    
           max_trust_radius=[10.0, 100.0, 1000.0] 
        
           initial_trust_radius=[10.0, 1.0, 0.1] 
        
           step_threshold=[0.0, 0.01, 0.25] 
        
           shrink_threshold=[0.25, 0.3, 0.5] 
        
           expand_threshold=[0.5, 0.8, 0.9] 
        
           shrink_factor=[0.1, 0.3, 0.5] 
        
           expand_factor=[1.5, 2.0, 3.0] 
        
           max_shrink_times=[10, 20, 30] 
        
           list_of_options=zip(

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/lib/NonlinearSolveFirstOrder/test/rootfind_tests.jl

Line 257 in 8fdee10

alg=TrustRegion(;

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/lib/NonlinearSolveFirstOrder/test/rootfind_tests.jl

Line 264 in 8fdee10

sol=solve_oop(quadratic_f, [1.0, 1.0], 2.0; solver = alg)

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/lib/NonlinearSolveFirstOrder/test/rootfind_tests.jl

Line 266 in 8fdee10

err=maximum(abs, quadratic_f(sol.u, 2.0))

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/lib/NonlinearSolveFirstOrder/test/rootfind_tests.jl

Lines 272 to 273 in 8fdee10

    
           maxiterations=[2, 3, 4, 5] 
        
           u0=[1.0, 1.0]

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/lib/NonlinearSolveFirstOrder/test/rootfind_tests.jl

Lines 291 to 293 in 8fdee10

    
           @testset "TC: $(nameof(typeof(termination_condition)))" for termination_condition in 
        
                                                                       TERMINATION_CONDITIONS

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/lib/NonlinearSolveFirstOrder/test/rootfind_tests.jl

Lines 349 to 351 in 8fdee10

    
           u0=[-10.0, -1.0, 1.0, 2.0, 3.0, 4.0, 10.0] 
        
           p=[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0] 
        
           sol=solve_oop(newton_fails, u0, p; solver = LevenbergMarquardt())

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/lib/NonlinearSolveFirstOrder/test/rootfind_tests.jl

Line 357 in 8fdee10

p=range(0.01, 2, length = 200)

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/lib/NonlinearSolveFirstOrder/test/rootfind_tests.jl

Lines 365 to 367 in 8fdee10

    
           @testset "TC: $(nameof(typeof(termination_condition)))" for termination_condition in 
        
                                                                       TERMINATION_CONDITIONS

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/lib/NonlinearSolveFirstOrder/test/rootfind_tests.jl

Lines 378 to 386 in 8fdee10

    
           damping_initial=[0.5, 2.0, 5.0] 
        
           damping_increase_factor=[1.5, 3.0, 10.0] 
        
           damping_decrease_factor=Float64[2, 5, 10.0] 
        
           finite_diff_step_geodesic=[0.02, 0.2, 0.3] 
        
           α_geodesic=[0.6, 0.8, 0.9] 
        
           b_uphill=Float64[0, 1, 2] 
        
           min_damping_D=[1e-12, 1e-9, 1e-4] 
        
           list_of_options=zip(

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/lib/NonlinearSolveFirstOrder/test/rootfind_tests.jl

Line 391 in 8fdee10

alg=LevenbergMarquardt(;

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/lib/NonlinearSolveFirstOrder/test/rootfind_tests.jl

Line 398 in 8fdee10

sol=solve_oop(quadratic_f, [1.0, 1.0], 2.0; solver = alg, maxiters = 10000)

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/lib/NonlinearSolveFirstOrder/test/rootfind_tests.jl

Line 400 in 8fdee10

err=maximum(abs, quadratic_f(sol.u, 2.0))

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/lib/NonlinearSolveFirstOrder/test/rootfind_tests.jl

Lines 433 to 434 in 8fdee10

    
           Δ=Tridiagonal(-ones(99), 2*ones(100), -ones(99)) 
        
           return u+0.1*u .* Δ*u-p

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/lib/NonlinearSolveFirstOrder/test/rootfind_tests.jl

Lines 438 to 439 in 8fdee10

    
           Δ=Tridiagonal(-ones(99), 2*ones(100), -ones(99)) 
        
           du.=u+0.1*u .* Δ*u-p

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/lib/NonlinearSolveFirstOrder/test/rootfind_tests.jl

Lines 444 to 445 in 8fdee10

    
           Δ=Tridiagonal(-ones(99), 2*ones(100), -ones(99)) 
        
           return v+0.1*(u .* Δ*v+v .* Δ*u)

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/lib/NonlinearSolveFirstOrder/test/rootfind_tests.jl

Lines 450 to 451 in 8fdee10

    
           Δ=Tridiagonal(-ones(99), 2*ones(100), -ones(99)) 
        
           du.=v+0.1*(u .* Δ*v+v .* Δ*u)

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/lib/NonlinearSolveFirstOrder/test/rootfind_tests.jl

Line 455 in 8fdee10

u0=rand(100)

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/lib/NonlinearSolveFirstOrder/test/rootfind_tests.jl

Lines 457 to 459 in 8fdee10

    
           prob=NonlinearProblem(NonlinearFunction{false}(F; jvp = JVP), u0, u0) 
        
           sol=solve(prob, NewtonRaphson(; linsolve = KrylovJL_GMRES()); abstol = 1e-13) 
        
           err=maximum(abs, sol.resid)

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/lib/NonlinearSolveFirstOrder/test/rootfind_tests.jl

Line 462 in 8fdee10

sol=solve(

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/lib/NonlinearSolveFirstOrder/test/rootfind_tests.jl

Line 466 in 8fdee10

err=maximum(abs, sol.resid)

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/lib/NonlinearSolveFirstOrder/test/rootfind_tests.jl

Lines 469 to 471 in 8fdee10

    
           prob=NonlinearProblem(NonlinearFunction{true}(F!; jvp = JVP!), u0, u0) 
        
           sol=solve(prob, NewtonRaphson(; linsolve = KrylovJL_GMRES()); abstol = 1e-13) 
        
           err=maximum(abs, sol.resid)

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/lib/NonlinearSolveFirstOrder/test/rootfind_tests.jl

Line 474 in 8fdee10

sol=solve(

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/lib/NonlinearSolveFirstOrder/test/rootfind_tests.jl

Line 478 in 8fdee10

err=maximum(abs, sol.resid)

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/lib/NonlinearSolveFirstOrder/test/sparsity_tests.jl

Lines 21 to 27 in 8fdee10

    
           j, 
        
           1] = alpha * 
        
                (u[im1, j, 1] + u[ip1, j, 1] + u[i, jp1, 1] + u[i, jm1, 1] - 
        
                 4u[i, j, 1]) + 
        
                B + 
        
                u[i, j, 1]^2 * u[i, j, 2] - (A + 1) * u[i, j, 1] + 
        
                brusselator_f(x, y)

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/lib/NonlinearSolveFirstOrder/test/sparsity_tests.jl

Lines 29 to 32 in 8fdee10

    
           j, 
        
           2] = alpha * 
        
                (u[im1, j, 2] + u[ip1, j, 2] + u[i, jp1, 2] + u[i, jm1, 2] - 
        
                 4u[i, j, 2]) + A * u[i, j, 1] - u[i, j, 1]^2 * u[i, j, 2]

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/lib/NonlinearSolveQuasiNewton/src/NonlinearSolveQuasiNewton.jl

Line 53 in 8fdee10

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/lib/NonlinearSolveQuasiNewton/test/core_tests.jl

Line 14 in 8fdee10

u0s=([1.0, 1.0], @SVector[1.0, 1.0], 1.0)

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/lib/NonlinearSolveQuasiNewton/test/core_tests.jl

Line 64 in 8fdee10

p=range(0.01, 2, length = 200)

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/lib/NonlinearSolveQuasiNewton/test/core_tests.jl

Lines 72 to 74 in 8fdee10

    
           @testset "TC: $(nameof(typeof(termination_condition)))" for termination_condition in 
        
                                                                       TERMINATION_CONDITIONS

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/lib/NonlinearSolveQuasiNewton/test/core_tests.jl

Line 139 in 8fdee10

p=range(0.01, 2, length = 200)

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/lib/NonlinearSolveQuasiNewton/test/core_tests.jl

Lines 147 to 149 in 8fdee10

    
           @testset "TC: $(nameof(typeof(termination_condition)))" for termination_condition in 
        
                                                                       TERMINATION_CONDITIONS

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/lib/NonlinearSolveQuasiNewton/test/core_tests.jl

Line 214 in 8fdee10

p=range(0.01, 2, length = 200)

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/lib/NonlinearSolveQuasiNewton/test/core_tests.jl

Lines 224 to 226 in 8fdee10

    
           @testset "TC: $(nameof(typeof(termination_condition)))" for termination_condition in 
        
                                                                       TERMINATION_CONDITIONS

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/lib/NonlinearSolveSpectralMethods/src/NonlinearSolveSpectralMethods.jl

Line 37 in 8fdee10

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/lib/NonlinearSolveSpectralMethods/src/dfsane.jl

Line 25 in 8fdee10

fn_1, n, x_n, f_n) -> fn_1 / n^2

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/lib/NonlinearSolveSpectralMethods/test/core_tests.jl

Line 11 in 8fdee10

u0s=([1.0, 1.0], @SVector[1.0, 1.0], 1.0)

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/lib/NonlinearSolveSpectralMethods/test/core_tests.jl

Line 35 in 8fdee10

p=range(0.01, 2, length = 200)

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/lib/NonlinearSolveSpectralMethods/test/core_tests.jl

Lines 41 to 43 in 8fdee10

    
           u0=[-10.0, -1.0, 1.0, 2.0, 3.0, 4.0, 10.0] 
        
           p=[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0] 
        
           sol=solve_oop(newton_fails, u0, p; solver = DFSane())

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/lib/NonlinearSolveSpectralMethods/test/core_tests.jl

Lines 49 to 59 in 8fdee10

    
           σ_min=[1e-10, 1e-5, 1e-4] 
        
           σ_max=[1e10, 1e5, 1e4] 
        
           σ_1=[1.0, 0.5, 2.0] 
        
           M=[10, 1, 100] 
        
           γ=[1e-4, 1e-3, 1e-5] 
        
           τ_min=[0.1, 0.2, 0.3] 
        
           τ_max=[0.5, 0.8, 0.9] 
        
           nexp=[2, 1, 2] 
        
           η_strategy=[ 
        
               (f_1, k, x, F)->f_1/k^2, (f_1, k, x, F)->f_1/k^3, 
        
               (f_1, k, x, F)->f_1/k^4

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/lib/NonlinearSolveSpectralMethods/test/core_tests.jl

Line 62 in 8fdee10

    
           list_of_options=zip(σ_min, σ_max, σ_1, M, γ, τ_min, τ_max, nexp, η_strategy)

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/lib/NonlinearSolveSpectralMethods/test/core_tests.jl

Line 65 in 8fdee10

alg=DFSane(;

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/lib/NonlinearSolveSpectralMethods/test/core_tests.jl

Lines 71 to 72 in 8fdee10

    
           probN=NonlinearProblem{false}(quadratic_f, [1.0, 1.0], 2.0) 
        
           sol=solve(probN, alg, abstol = 1e-11)

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/lib/NonlinearSolveSpectralMethods/test/core_tests.jl

Lines 80 to 82 in 8fdee10

    
           @testset "TC: $(nameof(typeof(termination_condition)))" for termination_condition in 
        
                                                                       TERMINATION_CONDITIONS

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/lib/SCCNonlinearSolve/test/core_tests.jl

Lines 10 to 17 in 8fdee10

    
           du[1]=cos(u[2])-u[1] 
        
           du[2]=sin(u[1]+u[2])+u[2] 
        
           du[3]=2u[4]+u[3]+1.0 
        
           du[4]=u[5]^2+u[4] 
        
           du[5]=u[3]^2+u[5] 
        
           du[6]=u[1]+u[2]+u[3]+u[4]+u[5]+2.0u[6]+2.5u[7]+1.5u[8] 
        
           du[7]=u[1]+u[2]+u[3]+2.0u[4]+u[5]+4.0u[6]-1.5u[7]+1.5u[8] 
        
           du[8]=u[1]+2.0u[2]+3.0u[3]+5.0u[4]+6.0u[5]+u[6]-u[7]-u[8]

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/lib/SCCNonlinearSolve/test/core_tests.jl

Lines 19 to 20 in 8fdee10

    
           prob=NonlinearProblem(f, zeros(8)) 
        
           sol=solve(prob, NewtonRaphson())

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/lib/SCCNonlinearSolve/test/core_tests.jl

Lines 22 to 23 in 8fdee10

    
           u0=zeros(2) 
        
           p=zeros(3)

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/lib/SCCNonlinearSolve/test/core_tests.jl

Lines 26 to 27 in 8fdee10

    
           du[1]=cos(u[2])-u[1] 
        
           du[2]=sin(u[1]+u[2])+u[2]

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/lib/SCCNonlinearSolve/test/core_tests.jl

Lines 29 to 30 in 8fdee10

    
           explicitfun1(p, sols)=nothing 
        
           prob1=NonlinearProblem(

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/lib/SCCNonlinearSolve/test/core_tests.jl

Line 32 in 8fdee10

sol1=solve(prob1, NewtonRaphson())

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/lib/SCCNonlinearSolve/test/core_tests.jl

Lines 35 to 37 in 8fdee10

    
           du[1]=2u[2]+u[1]+1.0 
        
           du[2]=u[3]^2+u[2] 
        
           du[3]=u[1]^2+u[3]

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/lib/SCCNonlinearSolve/test/core_tests.jl

Lines 39 to 40 in 8fdee10

    
           explicitfun2(p, sols)=nothing 
        
           prob2=NonlinearProblem(

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/lib/SCCNonlinearSolve/test/core_tests.jl

Line 42 in 8fdee10

sol2=solve(prob2, NewtonRaphson())

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/lib/SCCNonlinearSolve/test/core_tests.jl

Lines 45 to 47 in 8fdee10

    
           du[1]=p[1]+2.0u[1]+2.5u[2]+1.5u[3] 
        
           du[2]=p[2]+4.0u[1]-1.5u[2]+1.5u[3] 
        
           du[3]=p[3]++u[1]-u[2]-u[3]

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/lib/SCCNonlinearSolve/test/core_tests.jl

Line 49 in 8fdee10

prob3=NonlinearProblem(

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/lib/SCCNonlinearSolve/test/core_tests.jl

Lines 52 to 55 in 8fdee10

    
           p[1]=sols[1][1]+sols[1][2]+sols[2][1]+sols[2][2]+sols[2][3] 
        
           p[2]=sols[1][1]+sols[1][2]+sols[2][1]+2.0sols[2][2]+sols[2][3] 
        
           p[3]=sols[1][1]+2.0sols[1][2]+3.0sols[2][1]+5.0sols[2][2]+ 
        
                6.0sols[2][3]

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/lib/SCCNonlinearSolve/test/core_tests.jl

Lines 58 to 59 in 8fdee10

    
           sol3=solve(prob3, NewtonRaphson()) 
        
           manualscc=[sol1; sol2; sol3]

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/lib/SCCNonlinearSolve/test/core_tests.jl

Line 61 in 8fdee10

sccprob=SciMLBase.SCCNonlinearProblem([prob1, prob2, prob3],

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/lib/SCCNonlinearSolve/test/core_tests.jl

Line 63 in 8fdee10

scc_sol=solve(sccprob, NewtonRaphson())

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/lib/SCCNonlinearSolve/test/core_tests.jl

Line 68 in 8fdee10

scc_sol=solve(sccprob)

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/lib/SciMLJacobianOperators/src/SciMLJacobianOperators.jl

Line 294 in 8fdee10

vJ, v, u, p) -> begin

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/lib/SciMLJacobianOperators/src/SciMLJacobianOperators.jl

Lines 313 to 315 in 8fdee10

    
           v, 
        
           u, 
        
           p) -> begin

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/lib/SciMLJacobianOperators/src/SciMLJacobianOperators.jl

Lines 323 to 324 in 8fdee10

    
           u, 
        
           p) -> begin

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/lib/SciMLJacobianOperators/src/SciMLJacobianOperators.jl

Line 346 in 8fdee10

Jv, v, u, p) -> begin

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/lib/SciMLJacobianOperators/src/SciMLJacobianOperators.jl

Lines 364 to 366 in 8fdee10

    
           v, 
        
           u, 
        
           p) -> begin

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/lib/SciMLJacobianOperators/src/SciMLJacobianOperators.jl

Lines 374 to 375 in 8fdee10

    
           u, 
        
           p) -> begin

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/lib/SciMLJacobianOperators/test/core_tests.jl

Line 30 in 8fdee10

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/lib/SciMLJacobianOperators/test/core_tests.jl

Line 34 in 8fdee10

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/lib/SciMLJacobianOperators/test/core_tests.jl

Line 56 in 8fdee10

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/lib/SciMLJacobianOperators/test/core_tests.jl

Line 76 in 8fdee10

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/lib/SciMLJacobianOperators/test/core_tests.jl

Line 122 in 8fdee10

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/lib/SciMLJacobianOperators/test/core_tests.jl

Line 126 in 8fdee10

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/lib/SciMLJacobianOperators/test/core_tests.jl

Line 148 in 8fdee10

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/lib/SciMLJacobianOperators/test/core_tests.jl

Line 169 in 8fdee10

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/lib/SciMLJacobianOperators/test/core_tests.jl

Line 213 in 8fdee10

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/lib/SciMLJacobianOperators/test/core_tests.jl

Line 217 in 8fdee10

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/lib/SciMLJacobianOperators/test/core_tests.jl

Line 239 in 8fdee10

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/lib/SciMLJacobianOperators/test/core_tests.jl

Line 260 in 8fdee10

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/lib/SimpleNonlinearSolve/src/SimpleNonlinearSolve.jl

Line 156 in 8fdee10

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/lib/SimpleNonlinearSolve/src/utils.jl

Line 168 in 8fdee10

p) -> begin

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/lib/SimpleNonlinearSolve/test/core/forward_diff_tests.jl

Line 36 in 8fdee10

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/lib/SimpleNonlinearSolve/test/core/rootfind_tests.jl

Lines 73 to 74 in 8fdee10

    
           @testset "Termination Condition: $(nameof(typeof(termination_condition))) u0: $(nameof(typeof(u0)))" for termination_condition in 
        
                                                                                                                    TERMINATION_CONDITIONS,

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/lib/SimpleNonlinearSolve/test/core/rootfind_tests.jl

Lines 107 to 108 in 8fdee10

    
           @testset "Termination Condition: $(nameof(typeof(termination_condition))) u0: $(nameof(typeof(u0)))" for termination_condition in 
        
                                                                                                                    TERMINATION_CONDITIONS,

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/lib/SimpleNonlinearSolve/test/core/rootfind_tests.jl

Lines 140 to 141 in 8fdee10

    
           @testset "Termination Condition: $(nameof(typeof(termination_condition))) u0: $(nameof(typeof(u0)))" for termination_condition in 
        
                                                                                                                    TERMINATION_CONDITIONS,

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/lib/SimpleNonlinearSolve/test/core/rootfind_tests.jl

Lines 151 to 152 in 8fdee10

    
           u0=[-10.0, -1.0, 1.0, 2.0, 3.0, 4.0, 10.0] 
        
           p=[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/lib/SimpleNonlinearSolve/test/core/rootfind_tests.jl

Lines 167 to 168 in 8fdee10

    
           prob=NonlinearProblem(quadratic_f, ones(4), 2.0; maxiters = 2) 
        
           sol=solve(prob, SimpleNewtonRaphson())

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/src/NonlinearSolve.jl

Line 71 in 8fdee10

u, p) -> vcat(u .* u .- p, u .* u .- p)),

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/test/23_test_problems_tests.jl

Lines 13 to 14 in 8fdee10

    
           @testset "$idx: $(dict["title"]) | alg #$(alg_id)" for (alg_id, alg) in 
        
                                                                  enumerate(alg_ops)

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/test/23_test_problems_tests.jl

Line 43 in 8fdee10

alg_ops=(RobustMultiNewton(), FastShortcutNonlinearPolyalg())

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/test/23_test_problems_tests.jl

Lines 45 to 47 in 8fdee10

    
           broken_tests=Dict(alg=>Int[] for alg in alg_ops) 
        
           broken_tests[alg_ops[1]]=[] 
        
           broken_tests[alg_ops[2]]=[]

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/test/23_test_problems_tests.jl

Line 53 in 8fdee10

alg_ops=(

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/test/23_test_problems_tests.jl

Lines 58 to 59 in 8fdee10

    
           broken_tests=Dict(alg=>Int[] for alg in alg_ops) 
        
           broken_tests[alg_ops[1]]=[1]

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/test/23_test_problems_tests.jl

Line 65 in 8fdee10

alg_ops=(SimpleHalley(; autodiff = AutoForwardDiff()),)

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/test/23_test_problems_tests.jl

Lines 67 to 68 in 8fdee10

    
           broken_tests=Dict(alg=>Int[] for alg in alg_ops) 
        
           broken_tests[alg_ops[1]]=[1, 5, 15, 16, 18]

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/test/23_test_problems_tests.jl

Line 74 in 8fdee10

alg_ops=(

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/test/23_test_problems_tests.jl

Lines 85 to 93 in 8fdee10

    
           broken_tests=Dict(alg=>Int[] for alg in alg_ops) 
        
           broken_tests[alg_ops[1]]=[11, 21] 
        
           broken_tests[alg_ops[2]]=[11, 21] 
        
           broken_tests[alg_ops[3]]=[11, 21] 
        
           broken_tests[alg_ops[4]]=[8, 11, 21] 
        
           broken_tests[alg_ops[5]]=[21] 
        
           broken_tests[alg_ops[6]]=[11, 21] 
        
           broken_tests[alg_ops[7]]=[3, 15, 16, 21] 
        
           broken_tests[alg_ops[8]]=[15, 16]

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/test/23_test_problems_tests.jl

Line 101 in 8fdee10

alg_ops=(

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/test/23_test_problems_tests.jl

Lines 107 to 110 in 8fdee10

    
           broken_tests=Dict(alg=>Int[] for alg in alg_ops) 
        
           broken_tests[alg_ops[1]]=[11, 21] 
        
           broken_tests[alg_ops[2]]=[11, 21] 
        
           broken_tests[alg_ops[3]]=[11, 21]

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/test/23_test_problems_tests.jl

Line 116 in 8fdee10

alg_ops=(

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/test/23_test_problems_tests.jl

Lines 121 to 122 in 8fdee10

    
           broken_tests=Dict(alg=>Int[] for alg in alg_ops) 
        
           broken_tests[alg_ops[1]]=[1, 2, 3, 5, 21]

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/test/23_test_problems_tests.jl

Lines 124 to 125 in 8fdee10

    
           if VERSION≥v"1.11-" 
        
               broken_tests[alg_ops[2]]=[1, 2, 3, 5, 6, 11, 21]

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/test/23_test_problems_tests.jl

Line 127 in 8fdee10

broken_tests[alg_ops[2]]=[1, 2, 3, 5, 6, 21]

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/test/23_test_problems_tests.jl

Line 130 in 8fdee10

broken_tests[alg_ops[2]]=[1, 2, 3, 5, 6, 11, 21]

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/test/23_test_problems_tests.jl

Line 137 in 8fdee10

alg_ops=(

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/test/23_test_problems_tests.jl

Lines 145 to 147 in 8fdee10

    
           broken_tests=Dict(alg=>Int[] for alg in alg_ops) 
        
           broken_tests[alg_ops[2]]=[1, 5, 8, 11, 18] 
        
           broken_tests[alg_ops[4]]=[5, 6, 8, 11]

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/test/23_test_problems_tests.jl

Lines 149 to 152 in 8fdee10

    
           broken_tests[alg_ops[1]]=[1, 5, 11] 
        
           broken_tests[alg_ops[3]]=[1, 5, 6, 9, 11] 
        
           if VERSION≥v"1.11-" 
        
               broken_tests[alg_ops[5]]=[1, 4, 5, 11]

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/test/23_test_problems_tests.jl

Line 154 in 8fdee10

broken_tests[alg_ops[5]]=[1, 5, 11]

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/test/23_test_problems_tests.jl

Lines 157 to 159 in 8fdee10

    
           broken_tests[alg_ops[1]]=[1, 5, 11, 15] 
        
           broken_tests[alg_ops[3]]=[1, 5, 6, 9, 11, 16] 
        
           broken_tests[alg_ops[5]]=[1, 5, 11]

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/test/23_test_problems_tests.jl

Line 166 in 8fdee10

alg_ops=(

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/test/23_test_problems_tests.jl

Lines 172 to 175 in 8fdee10

    
           broken_tests=Dict(alg=>Int[] for alg in alg_ops) 
        
           broken_tests[alg_ops[1]]=[1, 2, 4, 5, 11, 18, 22] 
        
           broken_tests[alg_ops[2]]=[2, 4, 5, 7, 18, 22] 
        
           broken_tests[alg_ops[3]]=[1, 2, 4, 5, 11, 22]

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/test/23_test_problems_tests.jl

Line 183 in 8fdee10

alg_ops=(PseudoTransient(),)

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/test/23_test_problems_tests.jl

Lines 185 to 186 in 8fdee10

    
           broken_tests=Dict(alg=>Int[] for alg in alg_ops) 
        
           broken_tests[alg_ops[1]]=[1, 2, 3, 11, 15, 16]

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/test/cuda_tests.jl

Lines 70 to 71 in 8fdee10

    
           for nfn in 
        
               (Base.Fix1(maximum, abs), Base.Fix2(norm, 2), Base.Fix2(norm, Inf))

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/test/forward_ad_tests.jl

Line 107 in 8fdee10

compatible(u0, p) || continue

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/test/wrappers/least_squares_tests.jl

Line 10 in 8fdee10

nlls_problems=[prob_oop, prob_iip]

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/test/wrappers/least_squares_tests.jl

Line 12 in 8fdee10

solvers=[]

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/test/wrappers/least_squares_tests.jl

Lines 20 to 21 in 8fdee10


	sol=solve(prob, solver; maxiters = 10000, abstol = 1e-8)

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/test/wrappers/least_squares_tests.jl

Lines 32 to 33 in 8fdee10

    
           resid=zeros(length(p)) 
        
           ForwardDiff.jacobian!(J, (resid, θ)->loss_function(resid, θ, p), resid, θ)

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/test/wrappers/least_squares_tests.jl

Line 37 in 8fdee10

jac(θ, p)=ForwardDiff.jacobian(θ->loss_function(θ, p), θ)

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/test/wrappers/least_squares_tests.jl

Line 39 in 8fdee10

probs=[

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/test/wrappers/least_squares_tests.jl

Lines 57 to 58 in 8fdee10

    
           solvers=Any[FastLevenbergMarquardtJL(linsolve) for linsolve in (:cholesky, :qr)] 
        
           Sys.isapple()||push!(solvers, CMINPACK())

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/test/wrappers/least_squares_tests.jl

Lines 61 to 62 in 8fdee10


	sol=solve(prob, solver; maxiters = 10000, abstol = 1e-8)

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/test/wrappers/least_squares_tests.jl

Line 70 in 8fdee10

probs=[

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/test/wrappers/least_squares_tests.jl

Line 82 in 8fdee10

solvers=[]

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/test/wrappers/least_squares_tests.jl

Lines 95 to 96 in 8fdee10


	sol=solve(prob, solver; maxiters = 10000, abstol = 1e-8)

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/test/wrappers/least_squares_tests.jl

Line 104 in 8fdee10

x_sa=SA[-1.0, -0.5, 0.0, 0.5, 1.0]

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/test/wrappers/least_squares_tests.jl

Line 106 in 8fdee10

const y_target_sa=true_function(x_sa, θ_true)

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/test/wrappers/least_squares_tests.jl

Line 109 in 8fdee10

ŷ=true_function(p, θ)

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/test/wrappers/least_squares_tests.jl

Lines 113 to 114 in 8fdee10

    
           θ_init_sa=SVector{4}(θ_init) 
        
           prob_sa=NonlinearLeastSquaresProblem{false}(loss_function_sa, θ_init_sa, x)

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/test/wrappers/least_squares_tests.jl

Line 116 in 8fdee10

sol=solve(prob_sa, FastLevenbergMarquardtJL())

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/test/wrappers/rootfind_tests.jl

Lines 5 to 6 in 8fdee10

    
           du[1]=2-2u[1] 
        
           du[2]=u[1]-4u[2]

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/test/wrappers/rootfind_tests.jl

Lines 8 to 9 in 8fdee10

    
           u0=zeros(2) 
        
           prob_iip=SteadyStateProblem(f_iip, u0)

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/test/wrappers/rootfind_tests.jl

Lines 26 to 28 in 8fdee10

    
           f_oop(u, p, t)=[2-2u[1], u[1]-4u[2]] 
        
           u0=zeros(2) 
        
           prob_oop=SteadyStateProblem(f_oop, u0)

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/test/wrappers/rootfind_tests.jl

Lines 51 to 52 in 8fdee10

    
           du[1]=2-2u[1] 
        
           du[2]=u[1]-4u[2]

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/test/wrappers/rootfind_tests.jl

Lines 54 to 55 in 8fdee10

    
           u0=zeros(2) 
        
           prob_iip=NonlinearProblem{true}(f_iip, u0)

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/test/wrappers/rootfind_tests.jl

Lines 73 to 75 in 8fdee10

    
           f_oop(u, p)=[2-2u[1], u[1]-4u[2]] 
        
           u0=zeros(2) 
        
           prob_oop=NonlinearProblem{false}(f_oop, u0)

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/test/wrappers/rootfind_tests.jl

Lines 92 to 93 in 8fdee10

    
           f_tol(u, p)=u^2-2 
        
           prob_tol=NonlinearProblem(f_tol, 1.0)

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/test/wrappers/rootfind_tests.jl

Lines 106 to 108 in 8fdee10

    
           alg isa CMINPACK&&Sys.isapple()&&continue 
        
           alg isa PETScSNES&&Sys.iswindows()&&continue 
        
           sol=solve(prob_tol, alg, abstol = tol)

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/test/wrappers/rootfind_tests.jl

Lines 112 to 113 in 8fdee10

    
           f_jfnk(u, p)=u^2-2 
        
           prob_jfnk=NonlinearProblem(f_jfnk, 1.0)

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/test/wrappers/rootfind_tests.jl

Line 115 in 8fdee10

sol=solve(prob_jfnk, SIAMFANLEquationsJL(linsolve = :gmres), abstol = tol)

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/test/wrappers/rootfind_tests.jl

Lines 121 to 122 in 8fdee10

    
           fvec[1]=(x[1]+3)*(x[2]^3-7)+18 
        
           fvec[2]=sin(x[2]*exp(x[1])-1)

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/test/wrappers/rootfind_tests.jl

Lines 125 to 126 in 8fdee10

    
           prob=NonlinearProblem{true}(f!, [0.1; 1.2]) 
        
           sol=solve(prob, NLsolveJL(autodiff = :central))

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/test/wrappers/rootfind_tests.jl

Line 128 in 8fdee10

sol=solve(prob, SIAMFANLEquationsJL())

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/test/wrappers/rootfind_tests.jl

Line 132 in 8fdee10

sol=solve(prob, NLsolveJL(autodiff = :forward))

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/test/wrappers/rootfind_tests.jl

Lines 136 to 137 in 8fdee10

    
           f_custom_jac!(F, u, p)=(F[1:152]=u .^ 2 .- p) 
        
           j_custom_jac!(J, u, p)=(J[1:152, 1:152]=diagm(2 .* u))

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/test/wrappers/rootfind_tests.jl

Lines 139 to 141 in 8fdee10

    
           init=ones(152) 
        
           A=ones(152) 
        
           A[6]=0.8

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/test/wrappers/rootfind_tests.jl

Lines 143 to 144 in 8fdee10

    
           f=NonlinearFunction(f_custom_jac!; jac = j_custom_jac!) 
        
           p=A

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/test/wrappers/rootfind_tests.jl

Line 146 in 8fdee10

ProbN=NonlinearProblem(f, init, p)

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/test/wrappers/rootfind_tests.jl

Line 148 in 8fdee10

sol=solve(ProbN, NLsolveJL(); abstol = 1e-8)

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/test/wrappers/rootfind_tests.jl

Line 150 in 8fdee10

sol=solve(

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/test/wrappers/rootfind_tests.jl

Line 156 in 8fdee10

sol=solve(ProbN, SIAMFANLEquationsJL(; method = :newton); abstol = 1e-8)

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/test/wrappers/rootfind_tests.jl

Line 158 in 8fdee10

    
           sol=solve(ProbN, SIAMFANLEquationsJL(; method = :pseudotransient); abstol = 1e-8)

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/test/wrappers/rootfind_tests.jl

Line 161 in 8fdee10

sol=solve(ProbN, PETScSNES(); abstol = 1e-8)

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/test/wrappers/rootfind_tests.jl

Line 169 in 8fdee10

f(u, p)=u .* u .- 2

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/test/wrappers/rootfind_tests.jl

Lines 171 to 172 in 8fdee10

    
           u0=[1.0, 1.0] 
        
           probN=NonlinearProblem{false}(f, u0)

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/test/wrappers/rootfind_tests.jl

Line 174 in 8fdee10

sol=solve(probN, PETScSNES(); abstol = 1e-8)

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/test/wrappers/rootfind_tests.jl

Lines 177 to 178 in 8fdee10

    
           u0=[1.0f0, 1.0f0] 
        
           probN=NonlinearProblem{false}(f, u0)

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/test/wrappers/rootfind_tests.jl

Line 180 in 8fdee10

sol=solve(probN, PETScSNES(); abstol = 1e-5)

[JuliaFormatter] _{reported by reviewdog 🐶}

NonlinearSolve.jl/test/wrappers/rootfind_tests.jl

Lines 183 to 184 in 8fdee10

    
           u0=Float16[1.0, 1.0] 
        
           probN=NonlinearProblem{false}(f, u0)

github-actions · 2025-05-13T02:43:49Z

docs/src/tutorials/large_systems.md

+            j,
+            1] = alpha * (u[im1, j, 1] + u[ip1, j, 1] + u[i, jp1, 1] + u[i, jm1, 1] -
+                  4u[i, j, 1]) +
+                 B +
+                 u[i, j, 1]^2 * u[i, j, 2] - (A + 1) * u[i, j, 1] + brusselator_f(x, y)


[JuliaFormatter] _{reported by reviewdog 🐶}

Suggested change

j,

1] = alpha * (u[im1, j, 1] + u[ip1, j, 1] + u[i, jp1, 1] + u[i, jm1, 1] -

4u[i, j, 1]) +

B +

u[i, j, 1]^2 * u[i, j, 2] - (A + 1) * u[i, j, 1] + brusselator_f(x, y)

j,

1] = alpha * (u[im1, j, 1] + u[ip1, j, 1] + u[i, jp1, 1] + u[i, jm1, 1] -

4u[i, j, 1]) +

B +

u[i, j, 1]^2 * u[i, j, 2] - (A + 1) * u[i, j, 1] + brusselator_f(x, y)

github-actions · 2025-05-13T02:43:49Z

docs/src/tutorials/large_systems.md

+            j,
+            2] = alpha * (u[im1, j, 2] + u[ip1, j, 2] + u[i, jp1, 2] + u[i, jm1, 2] -
+                  4u[i, j, 2]) + A * u[i, j, 1] - u[i, j, 1]^2 * u[i, j, 2]


[JuliaFormatter] _{reported by reviewdog 🐶}

Suggested change

j,

2] = alpha * (u[im1, j, 2] + u[ip1, j, 2] + u[i, jp1, 2] + u[i, jm1, 2] -

4u[i, j, 2]) + A * u[i, j, 1] - u[i, j, 1]^2 * u[i, j, 2]

j,

2] = alpha * (u[im1, j, 2] + u[ip1, j, 2] + u[i, jp1, 2] + u[i, jm1, 2] -

4u[i, j, 2]) + A * u[i, j, 1] - u[i, j, 1]^2 * u[i, j, 2]

github-actions · 2025-05-13T02:43:49Z

ext/NonlinearSolveNLSolversExt.jl

@@ -33,7 +33,8 @@ function SciMLBase.__solve(
            prob.f, autodiff, prob.u0, Constant(prob.p)
        )

-        fj_scalar = @closure (Jx, x) -> begin
+        fj_scalar = @closure (Jx,
+            x) -> begin


[JuliaFormatter] _{reported by reviewdog 🐶}

Suggested change

x) -> begin

x) -> begin

github-actions · 2025-05-13T02:43:49Z

ext/NonlinearSolvePETScExt.jl

+        cx,
+        user_ctx) -> begin


[JuliaFormatter] _{reported by reviewdog 🐶}

Suggested change

cx,

user_ctx) -> begin

cx,

user_ctx) -> begin

github-actions · 2025-05-13T02:43:50Z

ext/NonlinearSolvePETScExt.jl

+                J,
+                _,
+                user_ctx) -> begin


[JuliaFormatter] _{reported by reviewdog 🐶}

Suggested change

J,

_,

user_ctx) -> begin

J,

_,

user_ctx) -> begin

github-actions · 2025-05-13T02:43:52Z

lib/NonlinearSolveFirstOrder/test/rootfind_tests.jl

+                            Diagonal(randn!(similar(A, size(A, 1)))), LinearAlgebra.I
+                        )


[JuliaFormatter] _{reported by reviewdog 🐶}

Suggested change

Diagonal(randn!(similar(A, size(A, 1)))), LinearAlgebra.I

)

Diagonal(randn!(similar(A, size(A, 1)))), LinearAlgebra.I

)

github-actions · 2025-05-13T02:43:53Z

lib/NonlinearSolveFirstOrder/test/rootfind_tests.jl

@@ -71,15 +72,17 @@
 end

 @testitem "NewtonRaphson: Iterator Interface" setup=[CoreRootfindTesting] tags=[:core] begin
-    p = range(0.01, 2, length = 200)
+    p=range(0.01, 2, length = 200)


[JuliaFormatter] _{reported by reviewdog 🐶}

Suggested change

p=range(0.01, 2, length = 200)

p = range(0.01, 2, length = 200)

github-actions · 2025-05-13T02:43:53Z

lib/NonlinearSolveFirstOrder/test/rootfind_tests.jl

+    @testset "TC: $(nameof(typeof(termination_condition)))" for termination_condition in
+                                                                TERMINATION_CONDITIONS
+


[JuliaFormatter] _{reported by reviewdog 🐶}

Suggested change

@testset "TC: $(nameof(typeof(termination_condition)))" for termination_condition in

TERMINATION_CONDITIONS

@testset "TC: $(nameof(typeof(termination_condition)))" for termination_condition in TERMINATION_CONDITIONS

github-actions · 2025-05-13T02:43:53Z

lib/NonlinearSolveFirstOrder/test/rootfind_tests.jl

+    preconditioners=[
+        (u0)->nothing,
+        u0->((args...)->(Diagonal(rand!(similar(u0))), nothing))


[JuliaFormatter] _{reported by reviewdog 🐶}

Suggested change

preconditioners=[

(u0)->nothing,

u0->((args...)->(Diagonal(rand!(similar(u0))), nothing))

preconditioners = [

(u0) -> nothing,

u0 -> ((args...) -> (Diagonal(rand!(similar(u0))), nothing))

github-actions · 2025-05-13T02:43:53Z

lib/NonlinearSolveFirstOrder/test/rootfind_tests.jl

+                        Diagonal(randn!(similar(A, size(A, 1)))), LinearAlgebra.I
+                    )


[JuliaFormatter] _{reported by reviewdog 🐶}

Suggested change

Diagonal(randn!(similar(A, size(A, 1)))), LinearAlgebra.I

)

Diagonal(randn!(similar(A, size(A, 1)))), LinearAlgebra.I

)

Format for JuliaFormatter v2

8fdee10

github-actions bot reviewed May 13, 2025

View reviewed changes

ChrisRackauckas closed this May 13, 2025

ChrisRackauckas deleted the format branch May 13, 2025 02:50

Provide feedback

Saved searches

Use saved searches to filter your results more quickly

Uh oh!

Uh oh!

Format for JuliaFormatter v2 #613

Format for JuliaFormatter v2 #613

Uh oh!

ChrisRackauckas commented May 13, 2025

Uh oh!

github-actions bot left a comment

Uh oh!

github-actions bot May 13, 2025

Uh oh!

github-actions bot May 13, 2025

Uh oh!

github-actions bot May 13, 2025

Uh oh!

github-actions bot May 13, 2025

Uh oh!

github-actions bot May 13, 2025

Uh oh!

github-actions bot May 13, 2025

Uh oh!

github-actions bot May 13, 2025

Uh oh!

github-actions bot May 13, 2025

Uh oh!

github-actions bot May 13, 2025

Uh oh!

github-actions bot May 13, 2025

Uh oh!

Uh oh!

	@testset "TC: $(nameof(typeof(termination_condition)))" for termination_condition in
	TERMINATION_CONDITIONS

	u0=[-10.0, -1.0, 1.0, 2.0, 3.0, 4.0, 10.0]
	p=[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]
	sol=solve_oop(newton_fails, u0, p; solver = TrustRegion())

	max_trust_radius=[10.0, 100.0, 1000.0]
	initial_trust_radius=[10.0, 1.0, 0.1]
	step_threshold=[0.0, 0.01, 0.25]
	shrink_threshold=[0.25, 0.3, 0.5]
	expand_threshold=[0.5, 0.8, 0.9]
	shrink_factor=[0.1, 0.3, 0.5]
	expand_factor=[1.5, 2.0, 3.0]
	max_shrink_times=[10, 20, 30]

	list_of_options=zip(

	damping_initial=[0.5, 2.0, 5.0]
	damping_increase_factor=[1.5, 3.0, 10.0]
	damping_decrease_factor=Float64[2, 5, 10.0]
	finite_diff_step_geodesic=[0.02, 0.2, 0.3]
	α_geodesic=[0.6, 0.8, 0.9]
	b_uphill=Float64[0, 1, 2]
	min_damping_D=[1e-12, 1e-9, 1e-4]

	list_of_options=zip(

	Δ=Tridiagonal(-ones(99), 2*ones(100), -ones(99))
	return u+0.1u . Δ*u-p

	Δ=Tridiagonal(-ones(99), 2*ones(100), -ones(99))
	du.=u+0.1u . Δ*u-p

	Δ=Tridiagonal(-ones(99), 2*ones(100), -ones(99))
	return v+0.1(u . Δv+v . Δ*u)

	Δ=Tridiagonal(-ones(99), 2*ones(100), -ones(99))
	du.=v+0.1(u . Δv+v . Δ*u)

	prob=NonlinearProblem(NonlinearFunction{false}(F; jvp = JVP), u0, u0)
	sol=solve(prob, NewtonRaphson(; linsolve = KrylovJL_GMRES()); abstol = 1e-13)
	err=maximum(abs, sol.resid)

	j,
	1] = alpha *
	(u[im1, j, 1] + u[ip1, j, 1] + u[i, jp1, 1] + u[i, jm1, 1] -
	4u[i, j, 1]) +
	B +
	u[i, j, 1]^2 * u[i, j, 2] - (A + 1) * u[i, j, 1] +
	brusselator_f(x, y)

	j,
	2] = alpha *
	(u[im1, j, 2] + u[ip1, j, 2] + u[i, jp1, 2] + u[i, jm1, 2] -
	4u[i, j, 2]) + A * u[i, j, 1] - u[i, j, 1]^2 * u[i, j, 2]

	σ_min=[1e-10, 1e-5, 1e-4]
	σ_max=[1e10, 1e5, 1e4]
	σ_1=[1.0, 0.5, 2.0]
	M=[10, 1, 100]
	γ=[1e-4, 1e-3, 1e-5]
	τ_min=[0.1, 0.2, 0.3]
	τ_max=[0.5, 0.8, 0.9]
	nexp=[2, 1, 2]
	η_strategy=[
	(f_1, k, x, F)->f_1/k^2, (f_1, k, x, F)->f_1/k^3,
	(f_1, k, x, F)->f_1/k^4

	probN=NonlinearProblem{false}(quadratic_f, [1.0, 1.0], 2.0)
	sol=solve(probN, alg, abstol = 1e-11)

	du[1]=cos(u[2])-u[1]
	du[2]=sin(u[1]+u[2])+u[2]
	du[3]=2u[4]+u[3]+1.0
	du[4]=u[5]^2+u[4]
	du[5]=u[3]^2+u[5]
	du[6]=u[1]+u[2]+u[3]+u[4]+u[5]+2.0u[6]+2.5u[7]+1.5u[8]
	du[7]=u[1]+u[2]+u[3]+2.0u[4]+u[5]+4.0u[6]-1.5u[7]+1.5u[8]
	du[8]=u[1]+2.0u[2]+3.0u[3]+5.0u[4]+6.0u[5]+u[6]-u[7]-u[8]

	prob=NonlinearProblem(f, zeros(8))
	sol=solve(prob, NewtonRaphson())

	du[1]=p[1]+2.0u[1]+2.5u[2]+1.5u[3]
	du[2]=p[2]+4.0u[1]-1.5u[2]+1.5u[3]
	du[3]=p[3]++u[1]-u[2]-u[3]

	p[1]=sols[1][1]+sols[1][2]+sols[2][1]+sols[2][2]+sols[2][3]
	p[2]=sols[1][1]+sols[1][2]+sols[2][1]+2.0sols[2][2]+sols[2][3]
	p[3]=sols[1][1]+2.0sols[1][2]+3.0sols[2][1]+5.0sols[2][2]+
	6.0sols[2][3]

	sol3=solve(prob3, NewtonRaphson())
	manualscc=[sol1; sol2; sol3]

	@testset "Termination Condition: $(nameof(typeof(termination_condition))) u0: $(nameof(typeof(u0)))" for termination_condition in
	TERMINATION_CONDITIONS,

	prob=NonlinearProblem(quadratic_f, ones(4), 2.0; maxiters = 2)
	sol=solve(prob, SimpleNewtonRaphson())

Uh oh!

Format for JuliaFormatter v2 #613

Format for JuliaFormatter v2 #613

Uh oh!

Conversation

ChrisRackauckas commented May 13, 2025

Uh oh!

github-actions bot left a comment

Choose a reason for hiding this comment

Uh oh!

github-actions bot May 13, 2025

Choose a reason for hiding this comment

Uh oh!

github-actions bot May 13, 2025

Choose a reason for hiding this comment

Uh oh!

github-actions bot May 13, 2025

Choose a reason for hiding this comment

Uh oh!

github-actions bot May 13, 2025

Choose a reason for hiding this comment

Uh oh!

github-actions bot May 13, 2025

Choose a reason for hiding this comment

Uh oh!

github-actions bot May 13, 2025

Choose a reason for hiding this comment

Uh oh!

github-actions bot May 13, 2025

Choose a reason for hiding this comment

Uh oh!

github-actions bot May 13, 2025

Choose a reason for hiding this comment

Uh oh!

github-actions bot May 13, 2025

Choose a reason for hiding this comment

Uh oh!

github-actions bot May 13, 2025

Choose a reason for hiding this comment

Uh oh!

Uh oh!

	@testset "$idx: $(dict["title"]) \| alg #$(alg_id)" for (alg_id, alg) in
	enumerate(alg_ops)

	broken_tests=Dict(alg=>Int[] for alg in alg_ops)
	broken_tests[alg_ops[1]]=[]
	broken_tests[alg_ops[2]]=[]

	broken_tests=Dict(alg=>Int[] for alg in alg_ops)
	broken_tests[alg_ops[1]]=[1]

	broken_tests=Dict(alg=>Int[] for alg in alg_ops)
	broken_tests[alg_ops[1]]=[1, 5, 15, 16, 18]

	broken_tests=Dict(alg=>Int[] for alg in alg_ops)
	broken_tests[alg_ops[1]]=[11, 21]
	broken_tests[alg_ops[2]]=[11, 21]
	broken_tests[alg_ops[3]]=[11, 21]
	broken_tests[alg_ops[4]]=[8, 11, 21]
	broken_tests[alg_ops[5]]=[21]
	broken_tests[alg_ops[6]]=[11, 21]
	broken_tests[alg_ops[7]]=[3, 15, 16, 21]
	broken_tests[alg_ops[8]]=[15, 16]

	broken_tests=Dict(alg=>Int[] for alg in alg_ops)
	broken_tests[alg_ops[1]]=[1, 2, 3, 5, 21]

	if VERSION≥v"1.11-"
	broken_tests[alg_ops[2]]=[1, 2, 3, 5, 6, 11, 21]

	broken_tests=Dict(alg=>Int[] for alg in alg_ops)
	broken_tests[alg_ops[2]]=[1, 5, 8, 11, 18]
	broken_tests[alg_ops[4]]=[5, 6, 8, 11]

	broken_tests[alg_ops[1]]=[1, 5, 11]
	broken_tests[alg_ops[3]]=[1, 5, 6, 9, 11]
	if VERSION≥v"1.11-"
	broken_tests[alg_ops[5]]=[1, 4, 5, 11]

	broken_tests[alg_ops[1]]=[1, 5, 11, 15]
	broken_tests[alg_ops[3]]=[1, 5, 6, 9, 11, 16]
	broken_tests[alg_ops[5]]=[1, 5, 11]