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SciML · Sep 15, 2024 · 09aa469 · 09aa469
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diff --git a/docs/src/massmatrixdae/Rosenbrock.md b/docs/src/massmatrixdae/Rosenbrock.md
@@ -11,7 +11,7 @@ the former is more efficient, but the latter is more reliable.
 For larger systems look at multistep methods.
 
 !!! warn
-
+    
     In order to use OrdinaryDiffEqRosenbrock with DAEs that require a non-trivial
     consistent initialization, a nonlinear solver is required and thus
     `using OrdinaryDiffEqNonlinearSolve` is required or you must pass an `initializealg`

diff --git a/lib/OrdinaryDiffEqBDF/src/bdf_perform_step.jl b/lib/OrdinaryDiffEqBDF/src/bdf_perform_step.jl
@@ -1113,7 +1113,8 @@ function perform_step!(integrator, cache::FBDFConstantCache{max_order},
         end
         tmp = -uprev * bdf_coeffs[k, 2]
         for i in 1:(k - 1)
-            tmp = @.. tmp - $(_reshape(view(u_corrector, :, i), axes(u))) * bdf_coeffs[k, i + 2]
+            tmp = @.. tmp -
+                      $(_reshape(view(u_corrector, :, i), axes(u))) * bdf_coeffs[k, i + 2]
         end
     end
 
@@ -1170,7 +1171,9 @@ function perform_step!(integrator, cache::FBDFConstantCache{max_order},
             terk *= abs(dt^(k))
         else
             for i in 2:(k + 1)
-                terk = @.. terk + fd_weights[i, k + 1] * $(_reshape(view(u_history, :, i - 1), axes(u)))
+                terk = @.. terk +
+                           fd_weights[i, k + 1] *
+                           $(_reshape(view(u_history, :, i - 1), axes(u)))
             end
             terk *= abs(dt^(k))
         end

diff --git a/lib/OrdinaryDiffEqBDF/src/controllers.jl b/lib/OrdinaryDiffEqBDF/src/controllers.jl
@@ -217,7 +217,8 @@ function choose_order!(alg::FBDF, integrator,
                 terk_tmp = similar(u)
                 @.. terk_tmp = fd_weights[k - 2, 1] * _vec(u)
                 for i in 2:(k - 2)
-                    @.. terk_tmp += fd_weights[i, k - 2] * $(_reshape(view(u_history, :, i - 1), axes(u)))
+                    @.. terk_tmp += fd_weights[i, k - 2] *
+                                    $(_reshape(view(u_history, :, i - 1), axes(u)))
                 end
                 @.. terk_tmp *= abs(dt^(k - 2))
             end

diff --git a/lib/OrdinaryDiffEqCore/src/caches/basic_caches.jl b/lib/OrdinaryDiffEqCore/src/caches/basic_caches.jl
@@ -51,7 +51,8 @@ function get_fsalfirstlast(cache::DefaultCache, u)
     (cache.u, cache.u) # will be overwritten by the cache choice
 end
 
-function ismutablecache(cache::DefaultCache{T1, T2, T3, T4, T5, T6, A, F, uType}) where {T1, T2, T3, T4, T5, T6, A, F, uType}
+function ismutablecache(cache::DefaultCache{
+        T1, T2, T3, T4, T5, T6, A, F, uType}) where {T1, T2, T3, T4, T5, T6, A, F, uType}
     T1 <: OrdinaryDiffEqMutableCache
 end
 

diff --git a/lib/OrdinaryDiffEqCore/src/initialize_dae.jl b/lib/OrdinaryDiffEqCore/src/initialize_dae.jl
@@ -121,20 +121,23 @@ function default_nlsolve(
 end
 
 function default_nlsolve(
-    ::Nothing, isinplace::Val{false}, u::Nothing, ::NonlinearProblem, autodiff = false)
-nothing
+        ::Nothing, isinplace::Val{false}, u::Nothing, ::NonlinearProblem, autodiff = false)
+    nothing
 end
 
 function default_nlsolve(
-    ::Nothing, isinplace::Val{false}, u::Nothing, ::NonlinearLeastSquaresProblem, autodiff = false)
-nothing
+        ::Nothing, isinplace::Val{false}, u::Nothing,
+        ::NonlinearLeastSquaresProblem, autodiff = false)
+    nothing
 end
 
-function OrdinaryDiffEqCore.default_nlsolve(::Nothing, isinplace, u, ::NonlinearProblem, autodiff = false)
+function OrdinaryDiffEqCore.default_nlsolve(
+        ::Nothing, isinplace, u, ::NonlinearProblem, autodiff = false)
     error("This ODE requires a DAE initialization and thus a nonlinear solve but no nonlinear solve has been loaded. To solve this problem, do `using OrdinaryDiffEqNonlinearSolve` or pass a custom `nlsolve` choice into the `initializealg`.")
 end
 
-function OrdinaryDiffEqCore.default_nlsolve(::Nothing, isinplace, u, ::NonlinearLeastSquaresProblem, autodiff = false)
+function OrdinaryDiffEqCore.default_nlsolve(
+        ::Nothing, isinplace, u, ::NonlinearLeastSquaresProblem, autodiff = false)
     error("This ODE requires a DAE initialization and thus a nonlinear solve but no nonlinear solve has been loaded. To solve this problem, do `using OrdinaryDiffEqNonlinearSolve` or pass a custom `nlsolve` choice into the `initializealg`.")
 end
 
@@ -179,12 +182,13 @@ end
 
 ## CheckInit
 struct CheckInitFailureError <: Exception
-    normresid
-    abstol
+    normresid::Any
+    abstol::Any
 end
 
 function Base.showerror(io::IO, e::CheckInitFailureError)
-    print(io, "CheckInit specified but initialization not satisifed. normresid = $(e.normresid) > abstol = $(e.abstol)")
+    print(io,
+        "CheckInit specified but initialization not satisifed. normresid = $(e.normresid) > abstol = $(e.abstol)")
 end
 
 function _initialize_dae!(integrator, prob::ODEProblem, alg::CheckInit,
@@ -202,7 +206,7 @@ function _initialize_dae!(integrator, prob::ODEProblem, alg::CheckInit,
     tmp .= ArrayInterface.restructure(tmp, algebraic_eqs .* _vec(tmp))
 
     normresid = integrator.opts.internalnorm(tmp, t)
-    if normresid > integrator.opts.abstol 
+    if normresid > integrator.opts.abstol
         throw(CheckInitFailureError(normresid, integrator.opts.abstol))
     end
 end
@@ -221,7 +225,7 @@ function _initialize_dae!(integrator, prob::ODEProblem, alg::CheckInit,
     resid = _vec(du)[algebraic_eqs]
 
     normresid = integrator.opts.internalnorm(resid, t)
-    if normresid > integrator.opts.abstol 
+    if normresid > integrator.opts.abstol
         throw(CheckInitFailureError(normresid, integrator.opts.abstol))
     end
 end
@@ -234,7 +238,7 @@ function _initialize_dae!(integrator, prob::DAEProblem,
 
     f(resid, integrator.du, u0, p, t)
     normresid = integrator.opts.internalnorm(resid, t)
-    if normresid > integrator.opts.abstol 
+    if normresid > integrator.opts.abstol
         throw(CheckInitFailureError(normresid, integrator.opts.abstol))
     end
 end
@@ -252,7 +256,7 @@ function _initialize_dae!(integrator, prob::DAEProblem,
 
     resid = f(integrator.du, u0, p, t)
     normresid = integrator.opts.internalnorm(resid, t)
-    if normresid > integrator.opts.abstol 
+    if normresid > integrator.opts.abstol
         throw(CheckInitFailureError(normresid, integrator.opts.abstol))
     end
-end
+end
diff --git a/lib/OrdinaryDiffEqCore/src/integrators/integrator_interface.jl b/lib/OrdinaryDiffEqCore/src/integrators/integrator_interface.jl
@@ -38,9 +38,10 @@ end
 function DiffEqBase.reeval_internals_due_to_modification!(
         integrator::ODEIntegrator, continuous_modification = true;
         callback_initializealg = nothing)
-
     if integrator.isdae
-        DiffEqBase.initialize_dae!(integrator, isnothing(callback_initializealg) ? integrator.initializealg : callback_initializealg)
+        DiffEqBase.initialize_dae!(integrator,
+            isnothing(callback_initializealg) ? integrator.initializealg :
+            callback_initializealg)
         update_uprev!(integrator)
     end
 

diff --git a/lib/OrdinaryDiffEqCore/src/interp_func.jl b/lib/OrdinaryDiffEqCore/src/interp_func.jl
@@ -76,7 +76,8 @@ end
 
 function strip_cache(cache)
     if hasfield(typeof(cache), :jac_config) || hasfield(typeof(cache), :grad_config) ||
-       hasfield(typeof(cache), :nlsolver) || hasfield(typeof(cache), :tf) || hasfield(typeof(cache), :uf)
+       hasfield(typeof(cache), :nlsolver) || hasfield(typeof(cache), :tf) ||
+       hasfield(typeof(cache), :uf)
         fieldnums = length(fieldnames(typeof(cache)))
         noth_list = fill(nothing, fieldnums)
         cache_type_name = Base.typename(typeof(cache)).wrapper

diff --git a/lib/OrdinaryDiffEqDefault/test/default_solver_tests.jl b/lib/OrdinaryDiffEqDefault/test/default_solver_tests.jl
@@ -1,4 +1,5 @@
-using OrdinaryDiffEqDefault, OrdinaryDiffEqTsit5, OrdinaryDiffEqVerner, OrdinaryDiffEqRosenbrock, OrdinaryDiffEqBDF
+using OrdinaryDiffEqDefault, OrdinaryDiffEqTsit5, OrdinaryDiffEqVerner,
+      OrdinaryDiffEqRosenbrock, OrdinaryDiffEqBDF
 using Test, LinearSolve, LinearAlgebra, SparseArrays, StaticArrays
 
 f_2dlinear = (du, u, p, t) -> (@. du = p * u)

diff --git a/lib/OrdinaryDiffEqDifferentiation/src/alg_utils.jl b/lib/OrdinaryDiffEqDifferentiation/src/alg_utils.jl
@@ -76,4 +76,4 @@ end
 @generated function pick_static_chunksize(::Val{chunksize}) where {chunksize}
     x = ForwardDiff.pickchunksize(chunksize)
     :(Val{$x}())
-end
+end
diff --git a/lib/OrdinaryDiffEqDifferentiation/src/derivative_utils.jl b/lib/OrdinaryDiffEqDifferentiation/src/derivative_utils.jl
@@ -12,7 +12,7 @@ struct StaticWOperator{isinv, T, F} <: AbstractSciMLOperator{T}
             # doing to how StaticArrays and StaticArraysCore are split up
             StaticArrays.LU(LowerTriangular(W), UpperTriangular(W), SVector{n}(1:n))
         else
-            lu(W, check=false)
+            lu(W, check = false)
         end
         # when constructing W for the first time for the type
         # inv(W) can be singular
@@ -938,28 +938,28 @@ function LinearSolve.init_cacheval(
 end
 
 for alg in [LinearSolve.AppleAccelerateLUFactorization,
-             LinearSolve.BunchKaufmanFactorization,
-             LinearSolve.CHOLMODFactorization,
-             LinearSolve.CholeskyFactorization,
-             LinearSolve.CudaOffloadFactorization,
-             LinearSolve.DiagonalFactorization,
-             LinearSolve.FastLUFactorization,
-             LinearSolve.FastQRFactorization,
-             LinearSolve.GenericFactorization,
-             LinearSolve.GenericLUFactorization,
-             LinearSolve.KLUFactorization,
-             LinearSolve.LDLtFactorization,
-             LinearSolve.LUFactorization,
-             LinearSolve.MKLLUFactorization,
-             LinearSolve.MetalLUFactorization,
-             LinearSolve.NormalBunchKaufmanFactorization,
-             LinearSolve.NormalCholeskyFactorization,
-             LinearSolve.QRFactorization,
-             LinearSolve.RFLUFactorization,
-             LinearSolve.SVDFactorization,
-             LinearSolve.SimpleLUFactorization,
-             LinearSolve.SparspakFactorization,
-             LinearSolve.UMFPACKFactorization]
+    LinearSolve.BunchKaufmanFactorization,
+    LinearSolve.CHOLMODFactorization,
+    LinearSolve.CholeskyFactorization,
+    LinearSolve.CudaOffloadFactorization,
+    LinearSolve.DiagonalFactorization,
+    LinearSolve.FastLUFactorization,
+    LinearSolve.FastQRFactorization,
+    LinearSolve.GenericFactorization,
+    LinearSolve.GenericLUFactorization,
+    LinearSolve.KLUFactorization,
+    LinearSolve.LDLtFactorization,
+    LinearSolve.LUFactorization,
+    LinearSolve.MKLLUFactorization,
+    LinearSolve.MetalLUFactorization,
+    LinearSolve.NormalBunchKaufmanFactorization,
+    LinearSolve.NormalCholeskyFactorization,
+    LinearSolve.QRFactorization,
+    LinearSolve.RFLUFactorization,
+    LinearSolve.SVDFactorization,
+    LinearSolve.SimpleLUFactorization,
+    LinearSolve.SparspakFactorization,
+    LinearSolve.UMFPACKFactorization]
     @eval function LinearSolve.init_cacheval(alg::$alg, A::WOperator, b, u, Pl, Pr,
             maxiters::Int, abstol, reltol, verbose::Bool,
             assumptions::OperatorAssumptions)
@@ -1003,4 +1003,4 @@ function resize_J_W!(cache, integrator, i)
     end
 
     nothing
-end
+end
diff --git a/lib/OrdinaryDiffEqExtrapolation/src/extrapolation_perform_step.jl b/lib/OrdinaryDiffEqExtrapolation/src/extrapolation_perform_step.jl
@@ -1193,7 +1193,7 @@ function perform_step!(integrator, cache::ImplicitDeuflhardExtrapolationCache,
             for j in 2:j_int
                 f(k, cache.u_temp1, p, t + (j - 1) * dt_int)
                 OrdinaryDiffEqCore.increment_nf!(integrator.stats, 1)
-                @.. broadcast=false linsolve_tmps[1]=k - (u_temp1 - u_temp2)/dt_int
+                @.. broadcast=false linsolve_tmps[1]=k - (u_temp1 - u_temp2) / dt_int
 
                 linsolve = cache.linsolve[1]
 
@@ -1270,7 +1270,8 @@ function perform_step!(integrator, cache::ImplicitDeuflhardExtrapolationCache,
                                 p, t + (j - 1) * dt_int_temp)
                             @.. broadcast=false linsolve_tmps[Threads.threadid()]=k_tmps[Threads.threadid()] -
                                                                                   (u_temp3[Threads.threadid()] -
-                                                                                   u_temp4[Threads.threadid()])/dt_int_temp
+                                                                                   u_temp4[Threads.threadid()]) /
+                                                                                  dt_int_temp
 
                             linsolve = cache.linsolve[Threads.threadid()]
 
@@ -1354,7 +1355,8 @@ function perform_step!(integrator, cache::ImplicitDeuflhardExtrapolationCache,
                                 p, t + (j - 1) * dt_int_temp)
                             @.. broadcast=false linsolve_tmps[Threads.threadid()]=k_tmps[Threads.threadid()] -
                                                                                   (u_temp3[Threads.threadid()] -
-                                                                                   u_temp4[Threads.threadid()])/dt_int_temp
+                                                                                   u_temp4[Threads.threadid()]) /
+                                                                                  dt_int_temp
 
                             linsolve = cache.linsolve[Threads.threadid()]
 
@@ -2555,7 +2557,7 @@ function perform_step!(integrator, cache::ImplicitHairerWannerExtrapolationCache
             for j in 2:(j_int + 1)
                 f(k, cache.u_temp1, p, t + (j - 1) * dt_int)
                 OrdinaryDiffEqCore.increment_nf!(integrator.stats, 1)
-                @.. broadcast=false linsolve_tmps[1]=k - (u_temp1 - u_temp2)/dt_int
+                @.. broadcast=false linsolve_tmps[1]=k - (u_temp1 - u_temp2) / dt_int
 
                 linsolve = cache.linsolve[1]
 
@@ -2634,9 +2636,10 @@ function perform_step!(integrator, cache::ImplicitHairerWannerExtrapolationCache
                             f(k_tmps[Threads.threadid()],
                                 cache.u_temp3[Threads.threadid()],
                                 p, t + (j - 1) * dt_int_temp)
-                            @.. broadcast=false linsolve_tmps[Threads.threadid()]= k_tmps[Threads.threadid()] -
+                            @.. broadcast=false linsolve_tmps[Threads.threadid()]=k_tmps[Threads.threadid()] -
                                                                                   (u_temp3[Threads.threadid()] -
-                                                                                   u_temp4[Threads.threadid()]) / dt_int_temp
+                                                                                   u_temp4[Threads.threadid()]) /
+                                                                                  dt_int_temp
 
                             linsolve = cache.linsolve[Threads.threadid()]
                             if !repeat_step && j == 1
@@ -2717,7 +2720,8 @@ function perform_step!(integrator, cache::ImplicitHairerWannerExtrapolationCache
                         for j in 2:(j_int_temp + 1)
                             f(ktmp, cache.u_temp3[tid], p, t + (j - 1) * dt_int_temp)
                             @.. broadcast=false linsolvetmp=ktmp -
-                                                            (u_temp3[tid] - u_temp4[tid])/dt_int_temp
+                                                            (u_temp3[tid] - u_temp4[tid]) /
+                                                            dt_int_temp
 
                             linsolve = cache.linsolve[tid]
 
@@ -2832,7 +2836,7 @@ function perform_step!(integrator, cache::ImplicitHairerWannerExtrapolationCache
                 for j in 2:(j_int + 1)
                     f(k, cache.u_temp1, p, t + (j - 1) * dt_int)
                     OrdinaryDiffEqCore.increment_nf!(integrator.stats, 1)
-                    @.. broadcast=false linsolve_tmps[1]=k - (u_temp1 - u_temp2)/dt_int
+                    @.. broadcast=false linsolve_tmps[1]=k - (u_temp1 - u_temp2) / dt_int
 
                     linsolve = cache.linsolve[1]
 

diff --git a/lib/OrdinaryDiffEqFIRK/src/firk_perform_step.jl b/lib/OrdinaryDiffEqFIRK/src/firk_perform_step.jl
@@ -902,7 +902,7 @@ end
         rhs3 = @.. broadcast=false fw3 - β1dt * Mw2-α1dt * Mw3
         rhs4 = @.. broadcast=false fw4 - α2dt * Mw4+β2dt * Mw5
         rhs5 = @.. broadcast=false fw5 - β2dt * Mw4-α2dt * Mw5
-        dw1  = _reshape(LU1 \ _vec(rhs1), axes(u))
+        dw1 = _reshape(LU1 \ _vec(rhs1), axes(u))
         dw23 = _reshape(LU2 \ _vec(@.. broadcast=false rhs2+rhs3 * im), axes(u))
         dw45 = _reshape(LU3 \ _vec(@.. broadcast=false rhs4+rhs5 * im), axes(u))
         integrator.stats.nsolve += 3

diff --git a/lib/OrdinaryDiffEqNonlinearSolve/src/initialize_dae.jl b/lib/OrdinaryDiffEqNonlinearSolve/src/initialize_dae.jl
@@ -1,21 +1,23 @@
-function default_nlsolve(::Nothing, isinplace::Val{true}, u, ::NonlinearProblem, autodiff = false)
+function default_nlsolve(
+        ::Nothing, isinplace::Val{true}, u, ::NonlinearProblem, autodiff = false)
     FastShortcutNonlinearPolyalg(;
         autodiff = autodiff ? AutoForwardDiff() : AutoFiniteDiff())
 end
 function default_nlsolve(
-    ::Nothing, isinplace::Val{true}, u, ::NonlinearLeastSquaresProblem, autodiff = false)
+        ::Nothing, isinplace::Val{true}, u, ::NonlinearLeastSquaresProblem, autodiff = false)
     FastShortcutNLLSPolyalg(; autodiff = autodiff ? AutoForwardDiff() : AutoFiniteDiff())
 end
-function default_nlsolve(::Nothing, isinplace::Val{false}, u, ::NonlinearProblem, autodiff = false)
+function default_nlsolve(
+        ::Nothing, isinplace::Val{false}, u, ::NonlinearProblem, autodiff = false)
     FastShortcutNonlinearPolyalg(;
         autodiff = autodiff ? AutoForwardDiff() : AutoFiniteDiff())
 end
 function default_nlsolve(
-    ::Nothing, isinplace::Val{false}, u, ::NonlinearLeastSquaresProblem, autodiff = false)
+        ::Nothing, isinplace::Val{false}, u, ::NonlinearLeastSquaresProblem, autodiff = false)
     FastShortcutNLLSPolyalg(; autodiff = autodiff ? AutoForwardDiff() : AutoFiniteDiff())
 end
 function default_nlsolve(::Nothing, isinplace::Val{false}, u::StaticArray,
-    ::NonlinearProblem, autodiff = false)
+        ::NonlinearProblem, autodiff = false)
     SimpleTrustRegion(autodiff = autodiff ? AutoForwardDiff() : AutoFiniteDiff())
 end
 function default_nlsolve(::Nothing, isinplace::Val{false}, u::StaticArray,