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SciML / OrdinaryDiffEq.jl

High performance ordinary differential equation (ODE) and differential-algebraic equation (DAE) solvers, including neural ordinary differential equations (neural ODEs) and scientific machine learning (SciML)
https://diffeq.sciml.ai/latest/
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Interpolation with `DynamicalODEProblem` is broken #2182

Closed ranocha closed 1 month ago

ranocha commented 2 months ago

Describe the bug 🐞

using Pkg; Pkg.activate(temp = true); Pkg.add("OrdinaryDiffEq")

julia> using OrdinaryDiffEq

julia> f1(v, q, params, t) = -sin(q)
f1 (generic function with 1 method)

julia> f2(v, q, params, t) = v
f2 (generic function with 1 method)

julia> v0 = 1.0
1.0

julia> q0 = -1.2
-1.2

julia> tspan = (0.0, 55.0)
(0.0, 55.0)

julia> ode = DynamicalODEProblem(f1, f2, v0, q0, tspan)
ODEProblem with uType RecursiveArrayTools.ArrayPartition{Float64, Tuple{Float64, Float64}} and tType Float64. In-place: false
timespan: (0.0, 55.0)
u0: (1.0, -1.2)

julia> sol = solve(ode, Tsit5())

julia> sol(0.5, idxs = [2, 1])
ERROR: MethodError: no method matching vec(::Float64)

Closest candidates are:
  vec(::StrideArraysCore.PtrArray{T, 1}) where T
   @ StrideArraysCore ~/.julia/packages/StrideArraysCore/ulk0L/src/reshape.jl:1
  vec(::StrideArraysCore.AbstractPtrArray{T, N, R, S, Tuple{Vararg{Nothing, N}}, O, T} where O) where {T, N, R, S}
   @ StrideArraysCore ~/.julia/packages/StrideArraysCore/ulk0L/src/reshape.jl:2
  vec(::LinearAlgebra.Adjoint{<:Real, <:AbstractVector})
   @ LinearAlgebra ~/.julia/juliaup/julia-1.10.3+0.aarch64.apple.darwin14/share/julia/stdlib/v1.10/LinearAlgebra/src/adjtrans.jl:369
  ...

Stacktrace:
  [1] copyto!(dest::Vector{Float64}, A::RecursiveArrayTools.ArrayPartition{Float64, Tuple{Float64, Float64}})
    @ RecursiveArrayTools ~/.julia/packages/RecursiveArrayTools/3hnnF/src/array_partition.jl:184
  [2] copyto_axcheck!(dest::Vector{Float64}, src::RecursiveArrayTools.ArrayPartition{Float64, Tuple{Float64, Float64}})
    @ Base ./abstractarray.jl:1177
  [3] Vector{Float64}(x::RecursiveArrayTools.ArrayPartition{Float64, Tuple{Float64, Float64}})
    @ Base ./array.jl:673
  [4] (Vector)(x::RecursiveArrayTools.ArrayPartition{Float64, Tuple{Float64, Float64}})
    @ Core ./boot.jl:498
  [5] _maybe_reshape(::IndexCartesian, A::RecursiveArrayTools.ArrayPartition{Float64, Tuple{…}}, I::Vector{Int64})
    @ RecursiveArrayTools ~/.julia/packages/RecursiveArrayTools/3hnnF/src/array_partition.jl:265
  [6] _getindex
    @ ./multidimensional.jl:889 [inlined]
  [7] getindex
    @ ./abstractarray.jl:1291 [inlined]
  [8] _ode_interpolant(Θ::Float64, dt::Float64, y₀::RecursiveArrayTools.ArrayPartition{…}, y₁::RecursiveArrayTools.ArrayPartition{…}, k::Vector{…}, cache::OrdinaryDiffEq.Tsit5ConstantCache, idxs::Vector{…}, T::Type{…}, differential_vars::Nothing)
    @ OrdinaryDiffEq ~/.julia/packages/OrdinaryDiffEq/0tf1M/src/dense/interpolants.jl:454
  [9] ode_interpolant(Θ::Float64, dt::Float64, y₀::RecursiveArrayTools.ArrayPartition{…}, y₁::RecursiveArrayTools.ArrayPartition{…}, k::Vector{…}, cache::OrdinaryDiffEq.Tsit5ConstantCache, idxs::Vector{…}, T::Type{…}, differential_vars::Nothing)
    @ OrdinaryDiffEq ~/.julia/packages/OrdinaryDiffEq/0tf1M/src/dense/generic_dense.jl:587
 [10] ode_interpolation(tval::Float64, id::OrdinaryDiffEq.InterpolationData{…}, idxs::Vector{…}, deriv::Type{…}, p::SciMLBase.NullParameters, continuity::Symbol)
    @ OrdinaryDiffEq ~/.julia/packages/OrdinaryDiffEq/0tf1M/src/dense/generic_dense.jl:505
 [11] InterpolationData
    @ ~/.julia/packages/OrdinaryDiffEq/0tf1M/src/interp_func.jl:169 [inlined]
 [12] AbstractODESolution
    @ ~/.julia/packages/SciMLBase/hSv8d/src/solutions/ode_solutions.jl:178 [inlined]
 [13] #_#471
    @ ~/.julia/packages/SciMLBase/hSv8d/src/solutions/ode_solutions.jl:151 [inlined]
 [14] AbstractODESolution
    @ ~/.julia/packages/SciMLBase/hSv8d/src/solutions/ode_solutions.jl:149 [inlined]
 [15] top-level scope
    @ REPL[11]:1
Some type information was truncated. Use `show(err)` to see complete types.

Expected behavior

The interpolation works.

Minimal Reproducible Example 👇

See above

Error & Stacktrace ⚠️

See above

Environment (please complete the following information):

julia> Pkg.status()
Status ...
  [1dea7af3] OrdinaryDiffEq v6.75.0
julia> Pkg.status(; mode = PKGMODE_MANIFEST)
Status ...
⌅ [47edcb42] ADTypes v0.2.7
  [7d9f7c33] Accessors v0.1.36
  [79e6a3ab] Adapt v4.0.4
  [ec485272] ArnoldiMethod v0.4.0
  [4fba245c] ArrayInterface v7.10.0
  [4c555306] ArrayLayouts v1.9.2
  [62783981] BitTwiddlingConvenienceFunctions v0.1.5
  [2a0fbf3d] CPUSummary v0.2.4
  [d360d2e6] ChainRulesCore v1.23.0
  [fb6a15b2] CloseOpenIntervals v0.1.12
  [38540f10] CommonSolve v0.2.4
  [bbf7d656] CommonSubexpressions v0.3.0
  [34da2185] Compat v4.15.0
  [a33af91c] CompositionsBase v0.1.2
  [2569d6c7] ConcreteStructs v0.2.3
  [187b0558] ConstructionBase v1.5.5
  [adafc99b] CpuId v0.3.1
  [9a962f9c] DataAPI v1.16.0
  [864edb3b] DataStructures v0.18.20
  [e2d170a0] DataValueInterfaces v1.0.0
  [2b5f629d] DiffEqBase v6.149.1
  [163ba53b] DiffResults v1.1.0
  [b552c78f] DiffRules v1.15.1
  [ffbed154] DocStringExtensions v0.9.3
  [4e289a0a] EnumX v1.0.4
⌃ [f151be2c] EnzymeCore v0.6.6
  [d4d017d3] ExponentialUtilities v1.26.1
  [e2ba6199] ExprTools v0.1.10
  [7034ab61] FastBroadcast v0.2.8
  [9aa1b823] FastClosures v0.3.2
  [29a986be] FastLapackInterface v2.0.3
  [1a297f60] FillArrays v1.11.0
  [6a86dc24] FiniteDiff v2.23.1
  [f6369f11] ForwardDiff v0.10.36
  [069b7b12] FunctionWrappers v1.1.3
  [77dc65aa] FunctionWrappersWrappers v0.1.3
  [46192b85] GPUArraysCore v0.1.6
  [c145ed77] GenericSchur v0.5.4
  [86223c79] Graphs v1.11.0
  [3e5b6fbb] HostCPUFeatures v0.1.16
  [615f187c] IfElse v0.1.1
  [d25df0c9] Inflate v0.1.4
  [3587e190] InverseFunctions v0.1.14
  [92d709cd] IrrationalConstants v0.2.2
  [82899510] IteratorInterfaceExtensions v1.0.0
  [692b3bcd] JLLWrappers v1.5.0
  [ef3ab10e] KLU v0.6.0
  [ba0b0d4f] Krylov v0.9.6
  [10f19ff3] LayoutPointers v0.1.15
  [5078a376] LazyArrays v1.10.0
  [d3d80556] LineSearches v7.2.0
  [7ed4a6bd] LinearSolve v2.29.1
  [2ab3a3ac] LogExpFunctions v0.3.27
  [bdcacae8] LoopVectorization v0.12.170
  [1914dd2f] MacroTools v0.5.13
  [d125e4d3] ManualMemory v0.1.8
  [a3b82374] MatrixFactorizations v2.2.0
  [bb5d69b7] MaybeInplace v0.1.2
  [46d2c3a1] MuladdMacro v0.2.4
  [d41bc354] NLSolversBase v7.8.3
  [77ba4419] NaNMath v1.0.2
  [8913a72c] NonlinearSolve v3.10.0
  [6fe1bfb0] OffsetArrays v1.14.0
  [bac558e1] OrderedCollections v1.6.3
  [1dea7af3] OrdinaryDiffEq v6.75.0
  [65ce6f38] PackageExtensionCompat v1.0.2
  [d96e819e] Parameters v0.12.3
  [f517fe37] Polyester v0.7.13
  [1d0040c9] PolyesterWeave v0.2.1
  [d236fae5] PreallocationTools v0.4.21
  [aea7be01] PrecompileTools v1.2.1
  [21216c6a] Preferences v1.4.3
  [3cdcf5f2] RecipesBase v1.3.4
  [731186ca] RecursiveArrayTools v3.15.0
  [f2c3362d] RecursiveFactorization v0.2.23
  [189a3867] Reexport v1.2.2
  [ae029012] Requires v1.3.0
  [7e49a35a] RuntimeGeneratedFunctions v0.5.13
  [94e857df] SIMDTypes v0.1.0
  [476501e8] SLEEFPirates v0.6.42
  [0bca4576] SciMLBase v2.36.1
  [c0aeaf25] SciMLOperators v0.3.8
  [53ae85a6] SciMLStructures v1.1.0
  [efcf1570] Setfield v1.1.1
  [727e6d20] SimpleNonlinearSolve v1.8.0
  [699a6c99] SimpleTraits v0.9.4
  [ce78b400] SimpleUnPack v1.1.0
⌃ [47a9eef4] SparseDiffTools v2.18.0
  [e56a9233] Sparspak v0.3.9
  [276daf66] SpecialFunctions v2.3.1
  [aedffcd0] Static v0.8.10
  [0d7ed370] StaticArrayInterface v1.5.0
  [90137ffa] StaticArrays v1.9.3
  [1e83bf80] StaticArraysCore v1.4.2
  [7792a7ef] StrideArraysCore v0.5.6
  [2efcf032] SymbolicIndexingInterface v0.3.21
  [3783bdb8] TableTraits v1.0.1
  [bd369af6] Tables v1.11.1
  [8290d209] ThreadingUtilities v0.5.2
  [a759f4b9] TimerOutputs v0.5.23
  [d5829a12] TriangularSolve v0.2.0
  [410a4b4d] Tricks v0.1.8
  [781d530d] TruncatedStacktraces v1.4.0
  [3a884ed6] UnPack v1.0.2
  [3d5dd08c] VectorizationBase v0.21.67
  [19fa3120] VertexSafeGraphs v0.2.0
  [1d5cc7b8] IntelOpenMP_jll v2024.1.0+0
  [856f044c] MKL_jll v2024.1.0+0
  [efe28fd5] OpenSpecFun_jll v0.5.5+0
  [1317d2d5] oneTBB_jll v2021.12.0+0
  [0dad84c5] ArgTools v1.1.1
  [56f22d72] Artifacts
  [2a0f44e3] Base64
  [ade2ca70] Dates
  [8ba89e20] Distributed
  [f43a241f] Downloads v1.6.0
  [7b1f6079] FileWatching
  [9fa8497b] Future
  [b77e0a4c] InteractiveUtils
  [4af54fe1] LazyArtifacts
  [b27032c2] LibCURL v0.6.4
  [76f85450] LibGit2
  [8f399da3] Libdl
  [37e2e46d] LinearAlgebra
  [56ddb016] Logging
  [d6f4376e] Markdown
  [a63ad114] Mmap
  [ca575930] NetworkOptions v1.2.0
  [44cfe95a] Pkg v1.10.0
  [de0858da] Printf
  [3fa0cd96] REPL
  [9a3f8284] Random
  [ea8e919c] SHA v0.7.0
  [9e88b42a] Serialization
  [1a1011a3] SharedArrays
  [6462fe0b] Sockets
  [2f01184e] SparseArrays v1.10.0
  [10745b16] Statistics v1.10.0
  [4607b0f0] SuiteSparse
  [fa267f1f] TOML v1.0.3
  [a4e569a6] Tar v1.10.0
  [8dfed614] Test
  [cf7118a7] UUIDs
  [4ec0a83e] Unicode
  [e66e0078] CompilerSupportLibraries_jll v1.1.1+0
  [deac9b47] LibCURL_jll v8.4.0+0
  [e37daf67] LibGit2_jll v1.6.4+0
  [29816b5a] LibSSH2_jll v1.11.0+1
  [c8ffd9c3] MbedTLS_jll v2.28.2+1
  [14a3606d] MozillaCACerts_jll v2023.1.10
  [4536629a] OpenBLAS_jll v0.3.23+4
  [05823500] OpenLibm_jll v0.8.1+2
  [bea87d4a] SuiteSparse_jll v7.2.1+1
  [83775a58] Zlib_jll v1.2.13+1
  [8e850b90] libblastrampoline_jll v5.8.0+1
  [8e850ede] nghttp2_jll v1.52.0+1
  [3f19e933] p7zip_jll v17.4.0+2
Info Packages marked with ⌃ and ⌅ have new versions available. Those with ⌃ may be upgradable, but those with ⌅ are restricted by compatibility constraints from upgrading. To see why use `status --outdated -m`

Additional context

Found in https://github.com/ranocha/BSeries.jl/actions/runs/8965125375/job/24618039980#step:9:44

ChrisRackauckas commented 1 month ago

Note that vector version always worked fine:

using OrdinaryDiffEq
f1(v, q, params, t) = -sin.(q)
f2(v, q, params, t) = v
v0 = [1.0]
q0 = [-1.2]
tspan = (0.0, 55.0)
ode = DynamicalODEProblem(f1, f2, v0, q0, tspan)
sol = solve(ode, Tsit5())
sol(0.5, idxs = [2, 1])

it's just arraypartition of scalars. This has a fix coming in today.