Open
Description
Describe the bug 🐞
When using Rodas5()
on a SplitODEProblem{isinplace}
ForwardDiff is not working.
(I think because du
is not a Dual Number when it should be.)
Expected behavior
ForwardDiff is working.
Minimal Reproducible Example 👇
# Here everything works as expected
function f(du, u , p, t)
du .= -u.^2 .+ 2u
return nothing
end
prob = ODEProblem(f, ones(2), (0.0, 1.0))
sol = solve(prob, Rodas5())
# The SplitODEProblem is not working
function f1(du, u , p, t)
du .= -u.^2
return nothing
end
function f2(du, u , p, t)
du .= 2u
return nothing
end
prob_split = SplitODEProblem(f1, f2, ones(2), (0.0, 1.0))
sol_split = solve(prob_split, Rodas5())
interestingly, doing
function f1(du, u , p, t)
@show du, u
du .= -u.^2
return nothing
end
gives me
(du, u) = ([-1.0, -1.0], [1.0, 1.0])
(du, u) = ([-1.0, -1.0], [1.01, 1.01])
(du, u) = ([-1.0201, -1.0201], [1.0, 1.0])
(du, u) = ([-1.0, -1.0], ForwardDiff.Dual{ForwardDiff.Tag{DiffEqBase.OrdinaryDiffEqTag, Float64}, Float64, 2}[Dual{ForwardDiff.Tag{DiffEqBase.OrdinaryDiffEqTag, Float64}}(1.0,1.0,0.0), Dual{ForwardDiff.Tag{DiffEqBase.OrdinaryDiffEqTag, Float64}}(1.0,0.0,1.0)])
ERROR: First call to automatic differentiation for the Jacobian
failed. This means that the user `f` function is not compatible
with automatic differentiation. Methods to fix this include:
...
So du
is not a dual number, even when it should be.
Error & Stacktrace
Looks like the normal "First call to automatic differentiation" Error message, but I think the problem is not the User in this case.
ERROR: First call to automatic differentiation for the Jacobian
failed. This means that the user `f` function is not compatible
with automatic differentiation. Methods to fix this include:
1. Turn off automatic differentiation (e.g. Rosenbrock23() becomes
Rosenbrock23(autodiff = AutoFiniteDiff())). More details can befound at
https://docs.sciml.ai/DiffEqDocs/stable/features/performance_overloads/
2. Improving the compatibility of `f` with ForwardDiff.jl automatic
differentiation (using tools like PreallocationTools.jl). More details
can be found at https://docs.sciml.ai/DiffEqDocs/stable/basics/faq/#Autodifferentiation-and-Dual-Numbers
3. Defining analytical Jacobians. More details can be
found at https://docs.sciml.ai/DiffEqDocs/stable/types/ode_types/#SciMLBase.ODEFunction
Note: turning off automatic differentiation tends to have a very minimal
performance impact (for this use case, because it's forward mode for a
square Jacobian. This is different from optimization gradient scenarios).
However, one should be careful as some methods are more sensitive to
accurate gradients than others. Specifically, Rodas methods like `Rodas4`
and `Rodas5P` require accurate Jacobians in order to have good convergence,
while many other methods like BDF (`QNDF`, `FBDF`), SDIRK (`KenCarp4`),
and Rosenbrock-W (`Rosenbrock23`) do not. Thus if using an algorithm which
is sensitive to autodiff and solving at a low tolerance, please change the
algorithm as well.
MethodError: no method matching Float64(::ForwardDiff.Dual{ForwardDiff.Tag{DiffEqBase.OrdinaryDiffEqTag, Float64}, Float64, 2})
The type `Float64` exists, but no method is defined for this combination of argument types when trying to construct it.
Closest candidates are:
(::Type{T})(::Real, ::RoundingMode) where T<:AbstractFloat
@ Base rounding.jl:265
(::Type{T})(::T) where T<:Number
@ Core boot.jl:900
Float64(::IrrationalConstants.Sqrthalfπ)
@ IrrationalConstants C:\Users\colli\.julia\packages\IrrationalConstants\lWTip\src\macro.jl:131
...
Stacktrace:
[1] jacobian!(J::Matrix{…}, f::Function, x::Vector{…}, fx::Vector{…}, integrator::OrdinaryDiffEqCore.ODEIntegrator{…}, jac_config::Tuple{…})
@ OrdinaryDiffEqDifferentiation C:\Users\colli\.julia\packages\OrdinaryDiffEqDifferentiation\Akmzh\src\derivative_wrappers.jl:223
[2] calc_J!
@ C:\Users\colli\.julia\packages\OrdinaryDiffEqDifferentiation\Akmzh\src\derivative_utils.jl:222 [inlined]
[3] calc_W!
@ C:\Users\colli\.julia\packages\OrdinaryDiffEqDifferentiation\Akmzh\src\derivative_utils.jl:627 [inlined]
[4] calc_W!
@ C:\Users\colli\.julia\packages\OrdinaryDiffEqDifferentiation\Akmzh\src\derivative_utils.jl:565 [inlined]
[5] calc_rosenbrock_differentiation!
@ C:\Users\colli\.julia\packages\OrdinaryDiffEqDifferentiation\Akmzh\src\derivative_utils.jl:702 [inlined]
[6] perform_step!(integrator::OrdinaryDiffEqCore.ODEIntegrator{…}, cache::OrdinaryDiffEqRosenbrock.RosenbrockCache{…}, repeat_step::Bool)
@ OrdinaryDiffEqRosenbrock C:\Users\colli\.julia\packages\OrdinaryDiffEqRosenbrock\gYeUg\src\rosenbrock_perform_step.jl:1337
[7] perform_step!
@ C:\Users\colli\.julia\packages\OrdinaryDiffEqRosenbrock\gYeUg\src\rosenbrock_perform_step.jl:1320 [inlined]
[8] solve!(integrator::OrdinaryDiffEqCore.ODEIntegrator{…})
@ OrdinaryDiffEqCore C:\Users\colli\.julia\packages\OrdinaryDiffEqCore\UVwdM\src\solve.jl:620
[9] __solve(::ODEProblem{…}, ::Rodas5{…}; kwargs::@Kwargs{})
@ OrdinaryDiffEqCore C:\Users\colli\.julia\packages\OrdinaryDiffEqCore\UVwdM\src\solve.jl:7
[10] __solve
@ C:\Users\colli\.julia\packages\OrdinaryDiffEqCore\UVwdM\src\solve.jl:1 [inlined]
[11] #solve_call#36
@ C:\Users\colli\.julia\packages\DiffEqBase\yhgdI\src\solve.jl:667 [inlined]
[12] solve_call
@ C:\Users\colli\.julia\packages\DiffEqBase\yhgdI\src\solve.jl:624 [inlined]
[13] #solve_up#45
@ C:\Users\colli\.julia\packages\DiffEqBase\yhgdI\src\solve.jl:1199 [inlined]
[14] solve_up
@ C:\Users\colli\.julia\packages\DiffEqBase\yhgdI\src\solve.jl:1177 [inlined]
[15] #solve#43
@ C:\Users\colli\.julia\packages\DiffEqBase\yhgdI\src\solve.jl:1089 [inlined]
[16] solve(prob::ODEProblem{…}, args::Rodas5{…})
@ DiffEqBase C:\Users\colli\.julia\packages\DiffEqBase\yhgdI\src\solve.jl:1079
[17] top-level scope
@ c:\Users\colli\OneDrive - JGU\12. Semester\HiWi\issue\mwe.jl:27
caused by: MethodError: no method matching Float64(::ForwardDiff.Dual{ForwardDiff.Tag{DiffEqBase.OrdinaryDiffEqTag, Float64}, Float64, 2})
The type `Float64` exists, but no method is defined for this combination of argument types when trying to construct it.
Closest candidates are:
(::Type{T})(::Real, ::RoundingMode) where T<:AbstractFloat
@ Base rounding.jl:265
(::Type{T})(::T) where T<:Number
@ Core boot.jl:900
Float64(::IrrationalConstants.Sqrthalfπ)
@ IrrationalConstants C:\Users\colli\.julia\packages\IrrationalConstants\lWTip\src\macro.jl:131
...
Stacktrace:
[1] convert(::Type{Float64}, x::ForwardDiff.Dual{ForwardDiff.Tag{DiffEqBase.OrdinaryDiffEqTag, Float64}, Float64, 2})
@ Base .\number.jl:7
[2] setindex!(A::Memory{Float64}, x::ForwardDiff.Dual{ForwardDiff.Tag{…}, Float64, 2}, i1::Int64)
@ Base .\genericmemory.jl:243
[3] unsafe_copyto!(dest::Memory{Float64}, doffs::Int64, src::Memory{ForwardDiff.Dual{…}}, soffs::Int64, n::Int64)
@ Base .\genericmemory.jl:153
[4] unsafe_copyto!
@ .\genericmemory.jl:133 [inlined]
[5] _copyto_impl!
@ .\array.jl:308 [inlined]
[6] copyto!
@ .\array.jl:294 [inlined]
[7] copyto!
@ .\array.jl:319 [inlined]
[8] copyto!
@ .\broadcast.jl:966 [inlined]
[9] copyto!
@ .\broadcast.jl:925 [inlined]
[10] materialize!
@ .\broadcast.jl:883 [inlined]
[11] materialize!
@ .\broadcast.jl:880 [inlined]
[12] f1(du::Vector{Float64}, u::Vector{ForwardDiff.Dual{…}}, p::SciMLBase.NullParameters, t::Float64)
@ Main c:\Users\colli\OneDrive - JGU\12. Semester\HiWi\issue\mwe.jl:17
[13] ODEFunction
@ C:\Users\colli\.julia\packages\SciMLBase\iHgIu\src\scimlfunctions.jl:2573 [inlined]
[14] (::SplitFunction{…})(du::Vector{…}, u::Vector{…}, p::SciMLBase.NullParameters, t::Float64)
@ SciMLBase C:\Users\colli\.julia\packages\SciMLBase\iHgIu\src\scimlfunctions.jl:2590
[15] UJacobianWrapper
@ C:\Users\colli\.julia\packages\SciMLBase\iHgIu\src\function_wrappers.jl:32 [inlined]
[16] vector_mode_dual_eval!
@ C:\Users\colli\.julia\packages\ForwardDiff\UBbGT\src\apiutils.jl:31 [inlined]
[17] vector_mode_jacobian!(result::Matrix{…}, f!::SciMLBase.UJacobianWrapper{…}, y::Vector{…}, x::Vector{…}, cfg::ForwardDiff.JacobianConfig{…})
@ ForwardDiff C:\Users\colli\.julia\packages\ForwardDiff\UBbGT\src\jacobian.jl:157
[18] jacobian!
@ C:\Users\colli\.julia\packages\ForwardDiff\UBbGT\src\jacobian.jl:82 [inlined]
[19] jacobian!(::SciMLBase.UJacobianWrapper{…}, ::Vector{…}, ::Matrix{…}, ::DifferentiationInterfaceForwardDiffExt.ForwardDiffTwoArgJacobianPrep{…}, ::ADTypes.AutoForwardDiff{…}, ::Vector{…})
@ DifferentiationInterfaceForwardDiffExt C:\Users\colli\.julia\packages\DifferentiationInterface\zJHX8\ext\DifferentiationInterfaceForwardDiffExt\twoarg.jl:489
[20] jacobian!(J::Matrix{…}, f::Function, x::Vector{…}, fx::Vector{…}, integrator::OrdinaryDiffEqCore.ODEIntegrator{…}, jac_config::Tuple{…})
@ OrdinaryDiffEqDifferentiation C:\Users\colli\.julia\packages\OrdinaryDiffEqDifferentiation\Akmzh\src\derivative_wrappers.jl:221
[21] calc_J!
@ C:\Users\colli\.julia\packages\OrdinaryDiffEqDifferentiation\Akmzh\src\derivative_utils.jl:222 [inlined]
[22] calc_W!
@ C:\Users\colli\.julia\packages\OrdinaryDiffEqDifferentiation\Akmzh\src\derivative_utils.jl:627 [inlined]
[23] calc_W!
@ C:\Users\colli\.julia\packages\OrdinaryDiffEqDifferentiation\Akmzh\src\derivative_utils.jl:565 [inlined]
[24] calc_rosenbrock_differentiation!
@ C:\Users\colli\.julia\packages\OrdinaryDiffEqDifferentiation\Akmzh\src\derivative_utils.jl:702 [inlined]
[25] perform_step!(integrator::OrdinaryDiffEqCore.ODEIntegrator{…}, cache::OrdinaryDiffEqRosenbrock.RosenbrockCache{…}, repeat_step::Bool)
@ OrdinaryDiffEqRosenbrock C:\Users\colli\.julia\packages\OrdinaryDiffEqRosenbrock\gYeUg\src\rosenbrock_perform_step.jl:1337
[26] perform_step!
@ C:\Users\colli\.julia\packages\OrdinaryDiffEqRosenbrock\gYeUg\src\rosenbrock_perform_step.jl:1320 [inlined]
[27] solve!(integrator::OrdinaryDiffEqCore.ODEIntegrator{…})
@ OrdinaryDiffEqCore C:\Users\colli\.julia\packages\OrdinaryDiffEqCore\UVwdM\src\solve.jl:620
[28] __solve(::ODEProblem{…}, ::Rodas5{…}; kwargs::@Kwargs{})
@ OrdinaryDiffEqCore C:\Users\colli\.julia\packages\OrdinaryDiffEqCore\UVwdM\src\solve.jl:7
[29] __solve
@ C:\Users\colli\.julia\packages\OrdinaryDiffEqCore\UVwdM\src\solve.jl:1 [inlined]
[29] __solve
[29] __solve
[29] __solve
@ C:\Users\colli\.julia\packages\OrdinaryDiffEqCore\UVwdM\src\solve.jl:1 [inlined]
[30] #solve_call#36
@ C:\Users\colli\.julia\packages\DiffEqBase\yhgdI\src\solve.jl:667 [inlined]
[31] solve_call
@ C:\Users\colli\.julia\packages\DiffEqBase\yhgdI\src\solve.jl:624 [inlined]
[32] #solve_up#45
@ C:\Users\colli\.julia\packages\DiffEqBase\yhgdI\src\solve.jl:1199 [inlined]
[33] solve_up
[29] __solve
@ C:\Users\colli\.julia\packages\OrdinaryDiffEqCore\UVwdM\src\solve.jl:1 [inlined]
[30] #solve_call#36
@ C:\Users\colli\.julia\packages\DiffEqBase\yhgdI\src\solve.jl:667 [inlined]
[31] solve_call
@ C:\Users\colli\.julia\packages\DiffEqBase\yhgdI\src\solve.jl:624 [inlined]
[32] #solve_up#45
[29] __solve
@ C:\Users\colli\.julia\packages\OrdinaryDiffEqCore\UVwdM\src\solve.jl:1 [inlined]
[30] #solve_call#36
@ C:\Users\colli\.julia\packages\DiffEqBase\yhgdI\src\solve.jl:667 [inlined]
[31] solve_call
[29] __solve
@ C:\Users\colli\.julia\packages\OrdinaryDiffEqCore\UVwdM\src\solve.jl:1 [inlined]
[30] #solve_call#36
@ C:\Users\colli\.julia\packages\DiffEqBase\yhgdI\src\solve.jl:667 [inlined]
[31] solve_call
@ C:\Users\colli\.julia\packages\DiffEqBase\yhgdI\src\solve.jl:624 [inlined]
[29] __solve
@ C:\Users\colli\.julia\packages\OrdinaryDiffEqCore\UVwdM\src\solve.jl:1 [inlined]
[30] #solve_call#36
@ C:\Users\colli\.julia\packages\DiffEqBase\yhgdI\src\solve.jl:667 [inlined]
[31] solve_call
@ C:\Users\colli\.julia\packages\DiffEqBase\yhgdI\src\solve.jl:624 [inlined]
[32] #solve_up#45
@ C:\Users\colli\.julia\packages\DiffEqBase\yhgdI\src\solve.jl:1199 [inlined]
[33] solve_up
@ C:\Users\colli\.julia\packages\DiffEqBase\yhgdI\src\solve.jl:1177 [inlined]
[34] #solve#43
[29] __solve
@ C:\Users\colli\.julia\packages\OrdinaryDiffEqCore\UVwdM\src\solve.jl:1 [inlined]
[30] #solve_call#36
@ C:\Users\colli\.julia\packages\DiffEqBase\yhgdI\src\solve.jl:667 [inlined]
[31] solve_call
@ C:\Users\colli\.julia\packages\DiffEqBase\yhgdI\src\solve.jl:624 [inlined]
[32] #solve_up#45
@ C:\Users\colli\.julia\packages\DiffEqBase\yhgdI\src\solve.jl:1199 [inlined]
[33] solve_up
@ C:\Users\colli\.julia\packages\DiffEqBase\yhgdI\src\solve.jl:1177 [inlined]
[34] #solve#43
[29] __solve
@ C:\Users\colli\.julia\packages\OrdinaryDiffEqCore\UVwdM\src\solve.jl:1 [inlined]
[30] #solve_call#36
@ C:\Users\colli\.julia\packages\DiffEqBase\yhgdI\src\solve.jl:667 [inlined]
[31] solve_call
@ C:\Users\colli\.julia\packages\DiffEqBase\yhgdI\src\solve.jl:624 [inlined]
[32] #solve_up#45
@ C:\Users\colli\.julia\packages\DiffEqBase\yhgdI\src\solve.jl:1199 [inlined]
@ C:\Users\colli\.julia\packages\DiffEqBase\yhgdI\src\solve.jl:667 [inlined]
[31] solve_call
@ C:\Users\colli\.julia\packages\DiffEqBase\yhgdI\src\solve.jl:624 [inlined]
[32] #solve_up#45
@ C:\Users\colli\.julia\packages\DiffEqBase\yhgdI\src\solve.jl:1199 [inlined]
[33] solve_up
[32] #solve_up#45
@ C:\Users\colli\.julia\packages\DiffEqBase\yhgdI\src\solve.jl:1199 [inlined]
[33] solve_up
[33] solve_up
@ C:\Users\colli\.julia\packages\DiffEqBase\yhgdI\src\solve.jl:1177 [inlined]
[34] #solve#43
@ C:\Users\colli\.julia\packages\DiffEqBase\yhgdI\src\solve.jl:1177 [inlined]
[34] #solve#43
@ C:\Users\colli\.julia\packages\DiffEqBase\yhgdI\src\solve.jl:1089 [inlined]
[34] #solve#43
@ C:\Users\colli\.julia\packages\DiffEqBase\yhgdI\src\solve.jl:1089 [inlined]
@ C:\Users\colli\.julia\packages\DiffEqBase\yhgdI\src\solve.jl:1089 [inlined]
[35] solve(prob::ODEProblem{…}, args::Rodas5{…})
@ DiffEqBase C:\Users\colli\.julia\packages\DiffEqBase\yhgdI\src\solve.jl:1079
[35] solve(prob::ODEProblem{…}, args::Rodas5{…})
@ DiffEqBase C:\Users\colli\.julia\packages\DiffEqBase\yhgdI\src\solve.jl:1079
@ DiffEqBase C:\Users\colli\.julia\packages\DiffEqBase\yhgdI\src\solve.jl:1079
[36] top-level scope
@ c:\Users\colli\OneDrive - JGU\12. Semester\HiWi\issue\mwe.jl:27
Some type information was truncated. Use `show(err)` to see complete types.
Environment (please complete the following information):
- Output of
using Pkg; Pkg.status()
[1dea7af3] OrdinaryDiffEq v6.97.0
- Output of
using Pkg; Pkg.status(; mode = PKGMODE_MANIFEST)
[47edcb42] ADTypes v1.14.0
[7d9f7c33] Accessors v0.1.42
[79e6a3ab] Adapt v4.3.0
[4fba245c] ArrayInterface v7.19.0
[4c555306] ArrayLayouts v1.11.1
[62783981] BitTwiddlingConvenienceFunctions v0.1.6
[70df07ce] BracketingNonlinearSolve v1.2.0
[2a0fbf3d] CPUSummary v0.2.6
[d360d2e6] ChainRulesCore v1.25.1
[fb6a15b2] CloseOpenIntervals v0.1.13
[38540f10] CommonSolve v0.2.4
[bbf7d656] CommonSubexpressions v0.3.1
[f70d9fcc] CommonWorldInvalidations v1.0.0
[34da2185] Compat v4.16.0
[a33af91c] CompositionsBase v0.1.2
[2569d6c7] ConcreteStructs v0.2.3
[187b0558] ConstructionBase v1.5.8
[adafc99b] CpuId v0.3.1
[a8cc5b0e] Crayons v4.1.1
[9a962f9c] DataAPI v1.16.0
[864edb3b] DataStructures v0.18.22
[e2d170a0] DataValueInterfaces v1.0.0
[2b5f629d] DiffEqBase v6.174.0
[163ba53b] DiffResults v1.1.0
[b552c78f] DiffRules v1.15.1
⌅ [a0c0ee7d] DifferentiationInterface v0.6.54
[ffbed154] DocStringExtensions v0.9.4
[4e289a0a] EnumX v1.0.5
[f151be2c] EnzymeCore v0.8.9
[d4d017d3] ExponentialUtilities v1.27.0
[e2ba6199] ExprTools v0.1.10
[55351af7] ExproniconLite v0.10.14
[7034ab61] FastBroadcast v0.3.5
[9aa1b823] FastClosures v0.3.2
[442a2c76] FastGaussQuadrature v1.0.2
[a4df4552] FastPower v1.1.2
[1a297f60] FillArrays v1.13.0
[6a86dc24] FiniteDiff v2.27.0
⌅ [f6369f11] ForwardDiff v0.10.38
[069b7b12] FunctionWrappers v1.1.3
[77dc65aa] FunctionWrappersWrappers v0.1.3
[46192b85] GPUArraysCore v0.2.0
[c145ed77] GenericSchur v0.5.5
[615f187c] IfElse v0.1.1
[3587e190] InverseFunctions v0.1.17
[92d709cd] IrrationalConstants v0.2.4
[82899510] IteratorInterfaceExtensions v1.0.0
[692b3bcd] JLLWrappers v1.7.0
[ae98c720] Jieko v0.2.1
[ba0b0d4f] Krylov v0.10.1
[b964fa9f] LaTeXStrings v1.4.0
[10f19ff3] LayoutPointers v0.1.17
[5078a376] LazyArrays v2.6.1
[87fe0de2] LineSearch v0.1.4
[d3d80556] LineSearches v7.3.0
[7ed4a6bd] LinearSolve v3.14.1
[2ab3a3ac] LogExpFunctions v0.3.29
[1914dd2f] MacroTools v0.5.16
[d125e4d3] ManualMemory v0.1.8
[bb5d69b7] MaybeInplace v0.1.4
[2e0e35c7] Moshi v0.3.5
[46d2c3a1] MuladdMacro v0.2.4
[d41bc354] NLSolversBase v7.9.1
[77ba4419] NaNMath v1.1.3
[8913a72c] NonlinearSolve v4.9.0
[be0214bd] NonlinearSolveBase v1.10.0
[5959db7a] NonlinearSolveFirstOrder v1.5.0
[9a2c21bd] NonlinearSolveQuasiNewton v1.5.0
[26075421] NonlinearSolveSpectralMethods v1.2.0
[bac558e1] OrderedCollections v1.8.1
[1dea7af3] OrdinaryDiffEq v6.97.0
[89bda076] OrdinaryDiffEqAdamsBashforthMoulton v1.2.0
[6ad6398a] OrdinaryDiffEqBDF v1.5.0
[bbf590c4] OrdinaryDiffEqCore v1.26.0
[50262376] OrdinaryDiffEqDefault v1.4.0
[4302a76b] OrdinaryDiffEqDifferentiation v1.9.0
[9286f039] OrdinaryDiffEqExplicitRK v1.1.0
[e0540318] OrdinaryDiffEqExponentialRK v1.4.0
[becaefa8] OrdinaryDiffEqExtrapolation v1.5.0
[5960d6e9] OrdinaryDiffEqFIRK v1.12.0
[101fe9f7] OrdinaryDiffEqFeagin v1.1.0
[d3585ca7] OrdinaryDiffEqFunctionMap v1.1.1
[d28bc4f8] OrdinaryDiffEqHighOrderRK v1.1.0
[9f002381] OrdinaryDiffEqIMEXMultistep v1.3.0
[521117fe] OrdinaryDiffEqLinear v1.3.0
[1344f307] OrdinaryDiffEqLowOrderRK v1.2.0
[b0944070] OrdinaryDiffEqLowStorageRK v1.3.0
[127b3ac7] OrdinaryDiffEqNonlinearSolve v1.9.0
[c9986a66] OrdinaryDiffEqNordsieck v1.1.0
[5dd0a6cf] OrdinaryDiffEqPDIRK v1.3.0
[5b33eab2] OrdinaryDiffEqPRK v1.1.0
[04162be5] OrdinaryDiffEqQPRK v1.1.0
[af6ede74] OrdinaryDiffEqRKN v1.1.0
[43230ef6] OrdinaryDiffEqRosenbrock v1.10.0
[2d112036] OrdinaryDiffEqSDIRK v1.3.0
[669c94d9] OrdinaryDiffEqSSPRK v1.3.0
[e3e12d00] OrdinaryDiffEqStabilizedIRK v1.3.0
[358294b1] OrdinaryDiffEqStabilizedRK v1.1.0
[fa646aed] OrdinaryDiffEqSymplecticRK v1.3.0
[b1df2697] OrdinaryDiffEqTsit5 v1.1.0
[79d7bb75] OrdinaryDiffEqVerner v1.2.0
[d96e819e] Parameters v0.12.3
[f517fe37] Polyester v0.7.17
[1d0040c9] PolyesterWeave v0.2.2
[d236fae5] PreallocationTools v0.4.27
⌅ [aea7be01] PrecompileTools v1.2.1
[21216c6a] Preferences v1.4.3
[08abe8d2] PrettyTables v2.4.0
[3cdcf5f2] RecipesBase v1.3.4
[731186ca] RecursiveArrayTools v3.33.0
[189a3867] Reexport v1.2.2
[ae029012] Requires v1.3.1
[7e49a35a] RuntimeGeneratedFunctions v0.5.14
[94e857df] SIMDTypes v0.1.0
[0bca4576] SciMLBase v2.93.0
[19f34311] SciMLJacobianOperators v0.1.5
⌅ [c0aeaf25] SciMLOperators v0.4.0
[53ae85a6] SciMLStructures v1.7.0
[efcf1570] Setfield v1.1.2
[727e6d20] SimpleNonlinearSolve v2.5.0
[ce78b400] SimpleUnPack v1.1.0
[0a514795] SparseMatrixColorings v0.4.19
[276daf66] SpecialFunctions v2.5.1
[aedffcd0] Static v1.2.0
[0d7ed370] StaticArrayInterface v1.8.0
[90137ffa] StaticArrays v1.9.13
[1e83bf80] StaticArraysCore v1.4.3
[10745b16] Statistics v1.11.1
[7792a7ef] StrideArraysCore v0.5.7
[892a3eda] StringManipulation v0.4.1
[2efcf032] SymbolicIndexingInterface v0.3.40
[3783bdb8] TableTraits v1.0.1
[bd369af6] Tables v1.12.0
[8290d209] ThreadingUtilities v0.5.3
[a759f4b9] TimerOutputs v0.5.29
[781d530d] TruncatedStacktraces v1.4.0
[3a884ed6] UnPack v1.0.2
[1d5cc7b8] IntelOpenMP_jll v2025.0.4+0
[856f044c] MKL_jll v2025.0.1+1
[efe28fd5] OpenSpecFun_jll v0.5.6+0
[1317d2d5] oneTBB_jll v2022.0.0+0
[0dad84c5] ArgTools v1.1.2
[56f22d72] Artifacts v1.11.0
[2a0f44e3] Base64 v1.11.0
[ade2ca70] Dates v1.11.0
[8ba89e20] Distributed v1.11.0
[f43a241f] Downloads v1.6.0
[7b1f6079] FileWatching v1.11.0
[9fa8497b] Future v1.11.0
[b77e0a4c] InteractiveUtils v1.11.0
[4af54fe1] LazyArtifacts v1.11.0
[b27032c2] LibCURL v0.6.4
[76f85450] LibGit2 v1.11.0
[8f399da3] Libdl v1.11.0
[37e2e46d] LinearAlgebra v1.11.0
[56ddb016] Logging v1.11.0
[d6f4376e] Markdown v1.11.0
[ca575930] NetworkOptions v1.2.0
[44cfe95a] Pkg v1.11.0
[de0858da] Printf v1.11.0
[9a3f8284] Random v1.11.0
[ea8e919c] SHA v0.7.0
[9e88b42a] Serialization v1.11.0
[6462fe0b] Sockets v1.11.0
[2f01184e] SparseArrays v1.11.0
[fa267f1f] TOML v1.0.3
[a4e569a6] Tar v1.10.0
[cf7118a7] UUIDs v1.11.0
[4ec0a83e] Unicode v1.11.0
[e66e0078] CompilerSupportLibraries_jll v1.1.1+0
[deac9b47] LibCURL_jll v8.6.0+0
[e37daf67] LibGit2_jll v1.7.2+0
[29816b5a] LibSSH2_jll v1.11.0+1
[c8ffd9c3] MbedTLS_jll v2.28.6+0
[14a3606d] MozillaCACerts_jll v2023.12.12
[4536629a] OpenBLAS_jll v0.3.27+1
[05823500] OpenLibm_jll v0.8.5+0
[bea87d4a] SuiteSparse_jll v7.7.0+0
[83775a58] Zlib_jll v1.2.13+1
[8e850b90] libblastrampoline_jll v5.11.0+0
[8e850ede] nghttp2_jll v1.59.0+0
[3f19e933] p7zip_jll v17.4.0+2
Info Packages marked with ⌅ have new versions available but compatibility constraints restrict them from upgrading. To see why use `status --outdated -m`
- Output of
versioninfo()
julia> versioninfo()
Julia Version 1.11.5
Commit 760b2e5b73 (2025-04-14 06:53 UTC)
Build Info:
Official https://julialang.org/ release
Platform Info:
OS: Windows (x86_64-w64-mingw32)
CPU: 8 × 11th Gen Intel(R) Core(TM) i7-1185G7 @ 3.00GHz
WORD_SIZE: 64
LLVM: libLLVM-16.0.6 (ORCJIT, tigerlake)
Threads: 8 default, 0 interactive, 4 GC (on 8 virtual cores)
Environment:
JULIA_NUM_THREADS = 8
JULIA_EDITOR = code
JULIA_VSCODE_REPL = 1
Additional context
Add any other context about the problem here.