Package evaluation of StochasticDiffEq on Julia 1.13.0-DEV.1114 (7de5585024*) started at 2025-09-14T09:45:24.356 ################################################################################ # Set-up # Installing PkgEval dependencies (TestEnv)... Set-up completed after 9.63s ################################################################################ # Installation # Installing StochasticDiffEq... Resolving package versions... Updating `~/.julia/environments/v1.13/Project.toml` [789caeaf] + StochasticDiffEq v6.82.0 Updating `~/.julia/environments/v1.13/Manifest.toml` [47edcb42] + ADTypes v1.18.0 [7d9f7c33] + Accessors v0.1.42 [79e6a3ab] + Adapt v4.3.0 [66dad0bd] + AliasTables v1.1.3 [ec485272] + ArnoldiMethod v0.4.0 [4fba245c] + ArrayInterface v7.20.0 [4c555306] + ArrayLayouts v1.11.2 [62783981] + BitTwiddlingConvenienceFunctions v0.1.6 [70df07ce] + BracketingNonlinearSolve v1.4.0 [2a0fbf3d] + CPUSummary v0.2.7 [d360d2e6] + ChainRulesCore v1.26.0 [fb6a15b2] + CloseOpenIntervals v0.1.13 [38540f10] + CommonSolve v0.2.4 [bbf7d656] + CommonSubexpressions v0.3.1 [f70d9fcc] + CommonWorldInvalidations v1.0.0 [34da2185] + Compat v4.18.0 [a33af91c] + CompositionsBase v0.1.2 [2569d6c7] + ConcreteStructs v0.2.3 [187b0558] + ConstructionBase v1.6.0 [adafc99b] + CpuId v0.3.1 [9a962f9c] + DataAPI v1.16.0 [864edb3b] + DataStructures v0.19.1 [2b5f629d] + DiffEqBase v6.189.1 [459566f4] + DiffEqCallbacks v4.9.0 [77a26b50] + DiffEqNoiseProcess v5.24.1 [163ba53b] + DiffResults v1.1.0 [b552c78f] + DiffRules v1.15.1 [a0c0ee7d] + DifferentiationInterface v0.7.7 [b4f34e82] + Distances v0.10.12 [31c24e10] + Distributions v0.25.120 [ffbed154] + DocStringExtensions v0.9.5 [4e289a0a] + EnumX v1.0.5 [f151be2c] + EnzymeCore v0.8.13 [e2ba6199] + ExprTools v0.1.10 [55351af7] + ExproniconLite v0.10.14 [7034ab61] + FastBroadcast v0.3.5 [9aa1b823] + FastClosures v0.3.2 [a4df4552] + FastPower v1.1.3 [1a297f60] + FillArrays v1.14.0 [6a86dc24] + FiniteDiff v2.28.1 [f6369f11] + ForwardDiff v1.2.1 [069b7b12] + FunctionWrappers v1.1.3 [77dc65aa] + FunctionWrappersWrappers v0.1.3 [d9f16b24] + Functors v0.5.2 [46192b85] + GPUArraysCore v0.2.0 [86223c79] + Graphs v1.13.1 [34004b35] + HypergeometricFunctions v0.3.28 [615f187c] + IfElse v0.1.1 [d25df0c9] + Inflate v0.1.5 [3587e190] + InverseFunctions v0.1.17 [92d709cd] + IrrationalConstants v0.2.4 [82899510] + IteratorInterfaceExtensions v1.0.0 [692b3bcd] + JLLWrappers v1.7.1 [ae98c720] + Jieko v0.2.1 [ccbc3e58] + JumpProcesses v9.19.1 [ba0b0d4f] + Krylov v0.10.1 [10f19ff3] + LayoutPointers v0.1.17 [5078a376] + LazyArrays v2.6.2 [2d8b4e74] + LevyArea v1.0.0 [87fe0de2] + LineSearch v0.1.4 [d3d80556] + LineSearches v7.4.0 [7ed4a6bd] + LinearSolve v3.40.0 [2ab3a3ac] + LogExpFunctions v0.3.29 [1914dd2f] + MacroTools v0.5.16 [d125e4d3] + ManualMemory v0.1.8 [bb5d69b7] + MaybeInplace v0.1.4 [e1d29d7a] + Missings v1.2.0 [2e0e35c7] + Moshi v0.3.7 [46d2c3a1] + MuladdMacro v0.2.4 [d41bc354] + NLSolversBase v7.10.0 [2774e3e8] + NLsolve v4.5.1 [77ba4419] + NaNMath v1.1.3 [8913a72c] + NonlinearSolve v4.10.0 [be0214bd] + NonlinearSolveBase v1.15.0 [5959db7a] + NonlinearSolveFirstOrder v1.8.0 [9a2c21bd] + NonlinearSolveQuasiNewton v1.9.0 [26075421] + NonlinearSolveSpectralMethods v1.4.0 [429524aa] + Optim v1.13.2 [bac558e1] + OrderedCollections v1.8.1 [bbf590c4] + OrdinaryDiffEqCore v1.34.0 [4302a76b] + OrdinaryDiffEqDifferentiation v1.16.0 [127b3ac7] + OrdinaryDiffEqNonlinearSolve v1.14.1 [90014a1f] + PDMats v0.11.35 [d96e819e] + Parameters v0.12.3 [e409e4f3] + PoissonRandom v0.4.6 [f517fe37] + Polyester v0.7.18 [1d0040c9] + PolyesterWeave v0.2.2 [85a6dd25] + PositiveFactorizations v0.2.4 [d236fae5] + PreallocationTools v0.4.34 [aea7be01] + PrecompileTools v1.3.3 [21216c6a] + Preferences v1.5.0 [43287f4e] + PtrArrays v1.3.0 [1fd47b50] + QuadGK v2.11.2 [74087812] + Random123 v1.7.1 [e6cf234a] + RandomNumbers v1.6.0 [3cdcf5f2] + RecipesBase v1.3.4 [731186ca] + RecursiveArrayTools v3.37.1 [189a3867] + Reexport v1.2.2 [ae029012] + Requires v1.3.1 [ae5879a3] + ResettableStacks v1.1.1 [79098fc4] + Rmath v0.8.0 [7e49a35a] + RuntimeGeneratedFunctions v0.5.15 [94e857df] + SIMDTypes v0.1.0 [0bca4576] + SciMLBase v2.118.0 [19f34311] + SciMLJacobianOperators v0.1.11 [c0aeaf25] + SciMLOperators v1.7.1 [53ae85a6] + SciMLStructures v1.7.0 [efcf1570] + Setfield v1.1.2 [727e6d20] + SimpleNonlinearSolve v2.8.0 [699a6c99] + SimpleTraits v0.9.5 [ce78b400] + SimpleUnPack v1.1.0 [a2af1166] + SortingAlgorithms v1.2.2 [0a514795] + SparseMatrixColorings v0.4.21 [276daf66] + SpecialFunctions v2.5.1 [aedffcd0] + Static v1.2.0 [0d7ed370] + StaticArrayInterface v1.8.0 [90137ffa] + StaticArrays v1.9.15 [1e83bf80] + StaticArraysCore v1.4.3 [10745b16] + Statistics v1.11.1 [82ae8749] + StatsAPI v1.7.1 [2913bbd2] + StatsBase v0.34.6 [4c63d2b9] + StatsFuns v1.5.0 [789caeaf] + StochasticDiffEq v6.82.0 [7792a7ef] + StrideArraysCore v0.5.8 [2efcf032] + SymbolicIndexingInterface v0.3.43 [8290d209] + ThreadingUtilities v0.5.5 [a759f4b9] + TimerOutputs v0.5.29 [781d530d] + TruncatedStacktraces v1.4.0 [3a884ed6] + UnPack v1.0.2 [1d5cc7b8] + IntelOpenMP_jll v2025.2.0+0 [856f044c] + MKL_jll v2025.2.0+0 [efe28fd5] + OpenSpecFun_jll v0.5.6+0 [f50d1b31] + Rmath_jll v0.5.1+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 v1.7.0 [7b1f6079] + FileWatching v1.11.0 [9fa8497b] + Future v1.11.0 [b77e0a4c] + InteractiveUtils v1.11.0 [ac6e5ff7] + JuliaSyntaxHighlighting v1.12.0 [4af54fe1] + LazyArtifacts v1.11.0 [b27032c2] + LibCURL v0.6.4 [76f85450] + LibGit2 v1.11.0 [8f399da3] + Libdl v1.11.0 [37e2e46d] + LinearAlgebra v1.13.0 [56ddb016] + Logging v1.11.0 [d6f4376e] + Markdown v1.11.0 [a63ad114] + Mmap v1.11.0 [ca575930] + NetworkOptions v1.3.0 [44cfe95a] + Pkg v1.13.0 [de0858da] + Printf v1.11.0 [9a3f8284] + Random v1.11.0 [ea8e919c] + SHA v0.7.0 [9e88b42a] + Serialization v1.11.0 [1a1011a3] + SharedArrays v1.11.0 [6462fe0b] + Sockets v1.11.0 [2f01184e] + SparseArrays v1.13.0 [f489334b] + StyledStrings v1.11.0 [4607b0f0] + SuiteSparse [fa267f1f] + TOML v1.0.3 [a4e569a6] + Tar v1.10.0 [cf7118a7] + UUIDs v1.11.0 [4ec0a83e] + Unicode v1.11.0 [e66e0078] + CompilerSupportLibraries_jll v1.3.0+1 [deac9b47] + LibCURL_jll v8.16.0+0 [e37daf67] + LibGit2_jll v1.9.1+0 [29816b5a] + LibSSH2_jll v1.11.3+1 [14a3606d] + MozillaCACerts_jll v2025.9.9 [4536629a] + OpenBLAS_jll v0.3.29+0 [05823500] + OpenLibm_jll v0.8.7+0 [458c3c95] + OpenSSL_jll v3.5.2+0 [efcefdf7] + PCRE2_jll v10.46.0+0 [bea87d4a] + SuiteSparse_jll v7.10.1+0 [83775a58] + Zlib_jll v1.3.1+2 [3161d3a3] + Zstd_jll v1.5.7+1 [8e850b90] + libblastrampoline_jll v5.13.1+0 [8e850ede] + nghttp2_jll v1.67.0+0 [3f19e933] + p7zip_jll v17.6.0+0 Installation completed after 5.86s ################################################################################ # Precompilation # Precompiling PkgEval dependencies... ┌ Warning: Could not use exact versions of packages in manifest, re-resolving └ @ TestEnv ~/.julia/packages/TestEnv/nGMfF/src/julia-1.11/activate_set.jl:76 Precompiling package dependencies... Precompilation completed after 48.66s ################################################################################ # Testing # Testing StochasticDiffEq Test Could not use exact versions of packages in manifest, re-resolving. Note: if you do not check your manifest file into source control, then you can probably ignore this message. However, if you do check your manifest file into source control, then you probably want to pass the `allow_reresolve = false` kwarg when calling the `Pkg.test` function. Updating `/tmp/jl_gwQnEP/Project.toml` ⌅ [864edb3b] ↓ DataStructures v0.19.1 ⇒ v0.18.22 [f3b72e0c] + DiffEqDevTools v2.48.0 [961ee093] + ModelingToolkit v10.22.0 [1dea7af3] + OrdinaryDiffEq v6.102.1 [c72e72a9] + SDEProblemLibrary v1.0.0 [1bc83da4] + SafeTestsets v0.1.0 [789caeaf] + StochasticDiffEq v6.82.0 [8dfed614] ~ Test ⇒ v1.11.0 Updating `/tmp/jl_gwQnEP/Manifest.toml` [1520ce14] + AbstractTrees v0.4.5 [e2ed5e7c] + Bijections v0.2.2 [8e7c35d0] + BlockArrays v1.7.2 ⌅ [861a8166] + Combinatorics v1.0.2 [a80b9123] + CommonMark v0.9.1 [b152e2b5] + CompositeTypes v0.1.4 ⌅ [864edb3b] ↓ DataStructures v0.19.1 ⇒ v0.18.22 [e2d170a0] + DataValueInterfaces v1.0.0 [f3b72e0c] + DiffEqDevTools v2.48.0 [8d63f2c5] + DispatchDoctor v0.4.26 [5b8099bc] + DomainSets v0.7.16 [7c1d4256] + DynamicPolynomials v0.6.3 [06fc5a27] + DynamicQuantities v1.9.0 [d4d017d3] + ExponentialUtilities v1.27.0 [442a2c76] + FastGaussQuadrature v1.0.2 [64ca27bc] + FindFirstFunctions v1.4.2 [1fa38f19] + Format v1.3.7 [c145ed77] + GenericSchur v0.5.5 [c27321d9] + Glob v1.3.1 [3263718b] + ImplicitDiscreteSolve v1.2.0 [18e54dd8] + IntegerMathUtils v0.1.3 [8197267c] + IntervalSets v0.7.11 [98e50ef6] + JuliaFormatter v2.1.6 ⌅ [70703baa] + JuliaSyntax v0.4.10 [b964fa9f] + LaTeXStrings v1.4.0 [23fbe1c1] + Latexify v0.16.10 [d8e11817] + MLStyle v0.4.17 [961ee093] + ModelingToolkit v10.22.0 ⌃ [102ac46a] + MultivariatePolynomials v0.5.9 [d8a4904e] + MutableArithmetics v1.6.4 [6fe1bfb0] + OffsetArrays v1.17.0 [1dea7af3] + OrdinaryDiffEq v6.102.1 [89bda076] + OrdinaryDiffEqAdamsBashforthMoulton v1.5.0 [6ad6398a] + OrdinaryDiffEqBDF v1.10.1 [50262376] + OrdinaryDiffEqDefault v1.8.0 [9286f039] + OrdinaryDiffEqExplicitRK v1.4.0 [e0540318] + OrdinaryDiffEqExponentialRK v1.8.0 [becaefa8] + OrdinaryDiffEqExtrapolation v1.9.0 [5960d6e9] + OrdinaryDiffEqFIRK v1.16.0 [101fe9f7] + OrdinaryDiffEqFeagin v1.4.0 [d3585ca7] + OrdinaryDiffEqFunctionMap v1.5.0 [d28bc4f8] + OrdinaryDiffEqHighOrderRK v1.5.0 [9f002381] + OrdinaryDiffEqIMEXMultistep v1.7.0 [521117fe] + OrdinaryDiffEqLinear v1.6.0 [1344f307] + OrdinaryDiffEqLowOrderRK v1.6.0 [b0944070] + OrdinaryDiffEqLowStorageRK v1.7.0 [c9986a66] + OrdinaryDiffEqNordsieck v1.4.0 [5dd0a6cf] + OrdinaryDiffEqPDIRK v1.6.0 [5b33eab2] + OrdinaryDiffEqPRK v1.4.0 [04162be5] + OrdinaryDiffEqQPRK v1.4.0 [af6ede74] + OrdinaryDiffEqRKN v1.5.0 [43230ef6] + OrdinaryDiffEqRosenbrock v1.17.0 [2d112036] + OrdinaryDiffEqSDIRK v1.7.0 [669c94d9] + OrdinaryDiffEqSSPRK v1.7.0 [e3e12d00] + OrdinaryDiffEqStabilizedIRK v1.6.0 [358294b1] + OrdinaryDiffEqStabilizedRK v1.4.0 [fa646aed] + OrdinaryDiffEqSymplecticRK v1.7.0 [b1df2697] + OrdinaryDiffEqTsit5 v1.5.0 [79d7bb75] + OrdinaryDiffEqVerner v1.6.0 [27ebfcd6] + Primes v0.5.7 [47965b36] + RootedTrees v2.23.1 [9dfe8606] + SCCNonlinearSolve v1.5.0 [c72e72a9] + SDEProblemLibrary v1.0.0 [1bc83da4] + SafeTestsets v0.1.0 [431bcebd] + SciMLPublic v1.0.0 [789caeaf] + StochasticDiffEq v6.82.0 [09ab397b] + StructArrays v0.7.1 [19f23fe9] + SymbolicLimits v0.2.3 [d1185830] + SymbolicUtils v3.32.0 [0c5d862f] + Symbolics v6.54.0 [3783bdb8] + TableTraits v1.0.1 [bd369af6] + Tables v1.12.1 [ed4db957] + TaskLocalValues v0.1.3 [8ea1fca8] + TermInterface v2.0.0 [1c621080] + TestItems v1.0.0 [410a4b4d] + Tricks v0.1.12 [5c2747f8] + URIs v1.6.1 [1986cc42] + Unitful v1.24.0 [a7c27f48] + Unityper v0.1.6 [61579ee1] + Ghostscript_jll v9.55.1+0 [aacddb02] + JpegTurbo_jll v3.1.3+0 [8dfed614] ~ Test ⇒ v1.11.0 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` Test Successfully re-resolved Status `/tmp/jl_gwQnEP/Project.toml` [47edcb42] ADTypes v1.18.0 [79e6a3ab] Adapt v4.3.0 [4fba245c] ArrayInterface v7.20.0 ⌅ [864edb3b] DataStructures v0.18.22 [2b5f629d] DiffEqBase v6.189.1 [459566f4] DiffEqCallbacks v4.9.0 [f3b72e0c] DiffEqDevTools v2.48.0 [77a26b50] DiffEqNoiseProcess v5.24.1 [ffbed154] DocStringExtensions v0.9.5 [a4df4552] FastPower v1.1.3 [6a86dc24] FiniteDiff v2.28.1 [f6369f11] ForwardDiff v1.2.1 [ccbc3e58] JumpProcesses v9.19.1 [2d8b4e74] LevyArea v1.0.0 [7ed4a6bd] LinearSolve v3.40.0 [961ee093] ModelingToolkit v10.22.0 [46d2c3a1] MuladdMacro v0.2.4 [2774e3e8] NLsolve v4.5.1 [1dea7af3] OrdinaryDiffEq v6.102.1 [bbf590c4] OrdinaryDiffEqCore v1.34.0 [4302a76b] OrdinaryDiffEqDifferentiation v1.16.0 [127b3ac7] OrdinaryDiffEqNonlinearSolve v1.14.1 [e6cf234a] RandomNumbers v1.6.0 [731186ca] RecursiveArrayTools v3.37.1 [189a3867] Reexport v1.2.2 [c72e72a9] SDEProblemLibrary v1.0.0 [1bc83da4] SafeTestsets v0.1.0 [0bca4576] SciMLBase v2.118.0 [c0aeaf25] SciMLOperators v1.7.1 [90137ffa] StaticArrays v1.9.15 [10745b16] Statistics v1.11.1 [789caeaf] StochasticDiffEq v6.82.0 [3a884ed6] UnPack v1.0.2 [37e2e46d] LinearAlgebra v1.13.0 [56ddb016] Logging v1.11.0 [44cfe95a] Pkg v1.13.0 [9a3f8284] Random v1.11.0 [2f01184e] SparseArrays v1.13.0 [8dfed614] Test v1.11.0 Status `/tmp/jl_gwQnEP/Manifest.toml` [47edcb42] ADTypes v1.18.0 [1520ce14] AbstractTrees v0.4.5 [7d9f7c33] Accessors v0.1.42 [79e6a3ab] Adapt v4.3.0 [66dad0bd] AliasTables v1.1.3 [ec485272] ArnoldiMethod v0.4.0 [4fba245c] ArrayInterface v7.20.0 [4c555306] ArrayLayouts v1.11.2 [e2ed5e7c] Bijections v0.2.2 [62783981] BitTwiddlingConvenienceFunctions v0.1.6 [8e7c35d0] BlockArrays v1.7.2 [70df07ce] BracketingNonlinearSolve v1.4.0 [2a0fbf3d] CPUSummary v0.2.7 [d360d2e6] ChainRulesCore v1.26.0 [fb6a15b2] CloseOpenIntervals v0.1.13 ⌅ [861a8166] Combinatorics v1.0.2 [a80b9123] CommonMark v0.9.1 [38540f10] CommonSolve v0.2.4 [bbf7d656] CommonSubexpressions v0.3.1 [f70d9fcc] CommonWorldInvalidations v1.0.0 [34da2185] Compat v4.18.0 [b152e2b5] CompositeTypes v0.1.4 [a33af91c] CompositionsBase v0.1.2 [2569d6c7] ConcreteStructs v0.2.3 [187b0558] ConstructionBase v1.6.0 [adafc99b] CpuId v0.3.1 [9a962f9c] DataAPI v1.16.0 ⌅ [864edb3b] DataStructures v0.18.22 [e2d170a0] DataValueInterfaces v1.0.0 [2b5f629d] DiffEqBase v6.189.1 [459566f4] DiffEqCallbacks v4.9.0 [f3b72e0c] DiffEqDevTools v2.48.0 [77a26b50] DiffEqNoiseProcess v5.24.1 [163ba53b] DiffResults v1.1.0 [b552c78f] DiffRules v1.15.1 [a0c0ee7d] DifferentiationInterface v0.7.7 [8d63f2c5] DispatchDoctor v0.4.26 [b4f34e82] Distances v0.10.12 [31c24e10] Distributions v0.25.120 [ffbed154] DocStringExtensions v0.9.5 [5b8099bc] DomainSets v0.7.16 [7c1d4256] DynamicPolynomials v0.6.3 [06fc5a27] DynamicQuantities v1.9.0 [4e289a0a] EnumX v1.0.5 [f151be2c] EnzymeCore v0.8.13 [d4d017d3] ExponentialUtilities v1.27.0 [e2ba6199] ExprTools v0.1.10 [55351af7] ExproniconLite v0.10.14 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Zstd_jll v1.5.7+1 [8e850b90] libblastrampoline_jll v5.13.1+0 [8e850ede] nghttp2_jll v1.67.0+0 [3f19e933] p7zip_jll v17.6.0+0 Info Packages marked with ⌃ and ⌅ have new versions available. Those with ⌃ may be upgradable, but those with ⌅ are restricted by compatibility constraints from upgrading. Testing Running tests... ┌ Warning: `Base.getindex(VA::AbstractDiffEqArray{T, N, A}, i::Int) where {T, N, A <: Union{AbstractArray, AbstractVectorOfArray}}` is deprecated, use `VA.u[i]` instead. │ caller = top-level scope at first_rand_test.jl:539 └ @ Core ~/.julia/packages/StochasticDiffEq/sNZzr/test/first_rand_test.jl:539 ┌ Warning: `Base.getindex(VA::AbstractDiffEqArray{T, N, A}, i::Int) where {T, N, A <: Union{AbstractArray, AbstractVectorOfArray}}` is deprecated, use `VA.u[i]` instead. │ caller = top-level scope at first_rand_test.jl:539 └ @ Core ~/.julia/packages/StochasticDiffEq/sNZzr/test/first_rand_test.jl:539 ┌ Warning: `Base.getindex(VA::AbstractDiffEqArray{T, N, A}, i::Int) where {T, N, A <: Union{AbstractArray, AbstractVectorOfArray}}` is deprecated, use `VA.u[i]` instead. │ caller = top-level scope at first_rand_test.jl:539 └ @ Core ~/.julia/packages/StochasticDiffEq/sNZzr/test/first_rand_test.jl:539 Test Summary: | Pass Total Time First Rand Tests | 4 4 49.8s 50.943623 seconds (30.70 M allocations: 1.937 GiB, 3.18% gc time, 61.98% compilation time: 7% of which was recompilation) WARNING: Method definition f(Any, Any, Any) in module ##Inference Tests#141 at /home/pkgeval/.julia/packages/StochasticDiffEq/sNZzr/test/inference_test.jl:5 overwritten at /home/pkgeval/.julia/packages/StochasticDiffEq/sNZzr/test/inference_test.jl:17. WARNING: Method definition g(Any, Any, Any) in module ##Inference Tests#141 at /home/pkgeval/.julia/packages/StochasticDiffEq/sNZzr/test/inference_test.jl:6 overwritten at /home/pkgeval/.julia/packages/StochasticDiffEq/sNZzr/test/inference_test.jl:18. Test Summary: | Pass Total Time Inference Tests | 2 2 15.4s 15.371883 seconds (10.00 M allocations: 569.171 MiB, 1.43% gc time, 99.63% compilation time: <1% of which was recompilation) ┌ Warning: `Base.getindex(VA::AbstractDiffEqArray{T, N, A}, i::Int) where {T, N, A <: Union{AbstractArray, AbstractVectorOfArray}}` is deprecated, use `VA.u[i]` instead. │ caller = top-level scope at rode_linear_tests.jl:539 └ @ Core ~/.julia/packages/StochasticDiffEq/sNZzr/test/rode_linear_tests.jl:539 ┌ Warning: `Base.getindex(VA::AbstractDiffEqArray{T, N, A}, i::Int) where {T, N, A <: Union{AbstractArray, AbstractVectorOfArray}}` is deprecated, use `VA.u[i]` instead. │ caller = top-level scope at rode_linear_tests.jl:539 └ @ Core ~/.julia/packages/StochasticDiffEq/sNZzr/test/rode_linear_tests.jl:539 ┌ Warning: Linear indexing of `AbstractVectorOfArray` is deprecated. Change `A[i]` to `A.u[i]` │ caller = top-level scope at rode_linear_tests.jl:539 └ @ Core ~/.julia/packages/StochasticDiffEq/sNZzr/test/rode_linear_tests.jl:539 ┌ Warning: `Base.getindex(VA::AbstractDiffEqArray{T, N, A}, i::Int) where {T, N, A <: Union{AbstractArray, AbstractVectorOfArray}}` is deprecated, use `VA.u[i]` instead. │ caller = top-level scope at rode_linear_tests.jl:539 └ @ Core ~/.julia/packages/StochasticDiffEq/sNZzr/test/rode_linear_tests.jl:539 ┌ Warning: Linear indexing of `AbstractVectorOfArray` is deprecated. Change `A[i]` to `A.u[i]` │ caller = top-level scope at rode_linear_tests.jl:539 └ @ Core ~/.julia/packages/StochasticDiffEq/sNZzr/test/rode_linear_tests.jl:539 ┌ Warning: `Base.getindex(VA::AbstractDiffEqArray{T, N, A}, i::Int) where {T, N, A <: Union{AbstractArray, AbstractVectorOfArray}}` is deprecated, use `VA.u[i]` instead. │ caller = top-level scope at rode_linear_tests.jl:539 └ @ Core ~/.julia/packages/StochasticDiffEq/sNZzr/test/rode_linear_tests.jl:539 WARNING: Method definition f(Any, Any, Any, Any) in module ##Linear RODE Tests#142 at /home/pkgeval/.julia/packages/StochasticDiffEq/sNZzr/test/rode_linear_tests.jl:4 overwritten at /home/pkgeval/.julia/packages/StochasticDiffEq/sNZzr/test/rode_linear_tests.jl:25. ┌ Warning: `Base.getindex(VA::AbstractDiffEqArray{T, N, A}, i::Int) where {T, N, A <: Union{AbstractArray, AbstractVectorOfArray}}` is deprecated, use `VA.u[i]` instead. │ caller = top-level scope at rode_linear_tests.jl:539 └ @ Core ~/.julia/packages/StochasticDiffEq/sNZzr/test/rode_linear_tests.jl:539 ┌ Warning: `Base.getindex(VA::AbstractDiffEqArray{T, N, A}, i::Int) where {T, N, A <: Union{AbstractArray, AbstractVectorOfArray}}` is deprecated, use `VA.u[i]` instead. │ caller = top-level scope at rode_linear_tests.jl:539 └ @ Core ~/.julia/packages/StochasticDiffEq/sNZzr/test/rode_linear_tests.jl:539 WARNING: Method definition f(Any, Any, Any, Any, Any) in module ##Linear RODE Tests#142 at /home/pkgeval/.julia/packages/StochasticDiffEq/sNZzr/test/rode_linear_tests.jl:15 overwritten at /home/pkgeval/.julia/packages/StochasticDiffEq/sNZzr/test/rode_linear_tests.jl:36. ┌ Warning: Linear indexing of `AbstractVectorOfArray` is deprecated. Change `A[i]` to `A.u[i]` │ caller = top-level scope at rode_linear_tests.jl:539 └ @ Core ~/.julia/packages/StochasticDiffEq/sNZzr/test/rode_linear_tests.jl:539 ┌ Warning: `Base.getindex(VA::AbstractDiffEqArray{T, N, A}, i::Int) where {T, N, A <: Union{AbstractArray, AbstractVectorOfArray}}` is deprecated, use `VA.u[i]` instead. │ caller = top-level scope at rode_linear_tests.jl:539 └ @ Core ~/.julia/packages/StochasticDiffEq/sNZzr/test/rode_linear_tests.jl:539 ┌ Warning: Linear indexing of `AbstractVectorOfArray` is deprecated. Change `A[i]` to `A.u[i]` │ caller = top-level scope at rode_linear_tests.jl:539 └ @ Core ~/.julia/packages/StochasticDiffEq/sNZzr/test/rode_linear_tests.jl:539 ┌ Warning: `Base.getindex(VA::AbstractDiffEqArray{T, N, A}, i::Int) where {T, N, A <: Union{AbstractArray, AbstractVectorOfArray}}` is deprecated, use `VA.u[i]` instead. │ caller = top-level scope at rode_linear_tests.jl:539 └ @ Core ~/.julia/packages/StochasticDiffEq/sNZzr/test/rode_linear_tests.jl:539 WARNING: Method definition f(Any, Any, Any, Any, Any) in module ##Linear RODE Tests#142 at /home/pkgeval/.julia/packages/StochasticDiffEq/sNZzr/test/rode_linear_tests.jl:36 overwritten at /home/pkgeval/.julia/packages/StochasticDiffEq/sNZzr/test/rode_linear_tests.jl:50. ┌ Warning: Linear indexing of `AbstractVectorOfArray` is deprecated. Change `A[i]` to `A.u[i]` │ caller = top-level scope at rode_linear_tests.jl:539 └ @ Core ~/.julia/packages/StochasticDiffEq/sNZzr/test/rode_linear_tests.jl:539 ┌ Warning: `Base.getindex(VA::AbstractDiffEqArray{T, N, A}, i::Int) where {T, N, A <: Union{AbstractArray, AbstractVectorOfArray}}` is deprecated, use `VA.u[i]` instead. │ caller = top-level scope at rode_linear_tests.jl:539 └ @ Core ~/.julia/packages/StochasticDiffEq/sNZzr/test/rode_linear_tests.jl:539 ┌ Warning: Linear indexing of `AbstractVectorOfArray` is deprecated. Change `A[i]` to `A.u[i]` │ caller = top-level scope at rode_linear_tests.jl:539 └ @ Core ~/.julia/packages/StochasticDiffEq/sNZzr/test/rode_linear_tests.jl:539 ┌ Warning: `Base.getindex(VA::AbstractDiffEqArray{T, N, A}, i::Int) where {T, N, A <: Union{AbstractArray, AbstractVectorOfArray}}` is deprecated, use `VA.u[i]` instead. │ caller = top-level scope at rode_linear_tests.jl:539 └ @ Core ~/.julia/packages/StochasticDiffEq/sNZzr/test/rode_linear_tests.jl:539 ┌ Warning: Linear indexing of `AbstractVectorOfArray` is deprecated. Change `A[i]` to `A.u[i]` │ caller = top-level scope at rode_linear_tests.jl:539 └ @ Core ~/.julia/packages/StochasticDiffEq/sNZzr/test/rode_linear_tests.jl:539 ┌ Warning: `Base.getindex(VA::AbstractDiffEqArray{T, N, A}, i::Int) where {T, N, A <: Union{AbstractArray, AbstractVectorOfArray}}` is deprecated, use `VA.u[i]` instead. │ caller = top-level scope at rode_linear_tests.jl:539 └ @ Core ~/.julia/packages/StochasticDiffEq/sNZzr/test/rode_linear_tests.jl:539 Test Summary: | Pass Total Time Linear RODE Tests | 10 10 42.4s 42.449336 seconds (18.32 M allocations: 1.040 GiB, 2.39% gc time, 99.71% compilation time: 25% of which was recompilation) Test Summary: | Pass Total Time Complex Number Tests | 24 24 4m05.3s 245.309838 seconds (95.67 M allocations: 5.305 GiB, 1.51% gc time, 99.96% compilation time) Test Summary: | Broken Total Time Static Array Tests | 4 4 17.5s 17.529546 seconds (13.21 M allocations: 737.966 MiB, 1.39% gc time, 99.81% compilation time: <1% of which was recompilation) WARNING: Method definition f(Any, Any, Any, Any) in module ##Noise Type Tests#145 at /home/pkgeval/.julia/packages/StochasticDiffEq/sNZzr/test/noise_type_test.jl:3 overwritten at /home/pkgeval/.julia/packages/StochasticDiffEq/sNZzr/test/noise_type_test.jl:18. WARNING: Method definition g(Any, Any, Any, Any) in module ##Noise Type Tests#145 at /home/pkgeval/.julia/packages/StochasticDiffEq/sNZzr/test/noise_type_test.jl:4 overwritten at /home/pkgeval/.julia/packages/StochasticDiffEq/sNZzr/test/noise_type_test.jl:19. ┌ Warning: `Base.getindex(VA::AbstractDiffEqArray{T, N, A}, i::Int) where {T, N, A <: Union{AbstractArray, AbstractVectorOfArray}}` is deprecated, use `VA.u[i]` instead. │ caller = top-level scope at noise_type_test.jl:539 └ @ Core ~/.julia/packages/StochasticDiffEq/sNZzr/test/noise_type_test.jl:539 WARNING: Method definition f(Any, Any, Any, Any) in module ##Noise Type Tests#145 at /home/pkgeval/.julia/packages/StochasticDiffEq/sNZzr/test/noise_type_test.jl:18 overwritten at /home/pkgeval/.julia/packages/StochasticDiffEq/sNZzr/test/noise_type_test.jl:40. WARNING: Method definition g(Any, Any, Any, Any) in module ##Noise Type Tests#145 at /home/pkgeval/.julia/packages/StochasticDiffEq/sNZzr/test/noise_type_test.jl:19 overwritten at /home/pkgeval/.julia/packages/StochasticDiffEq/sNZzr/test/noise_type_test.jl:41. ┌ Warning: `alias_noise` keyword argument is deprecated, to set `alias_noise`, │ please use an SDEAliasSpecifier, e.g. `solve(prob, alias = SDEAliasSpecifier(alias_noise = true))` │ caller = ip:0x0 └ @ Core :-1 ┌ Warning: `alias_noise` keyword argument is deprecated, to set `alias_noise`, │ please use an SDEAliasSpecifier, e.g. `solve(prob, alias = SDEAliasSpecifier(alias_noise = true))` │ caller = top-level scope at noise_type_test.jl:52 └ @ Core ~/.julia/packages/StochasticDiffEq/sNZzr/test/noise_type_test.jl:52 ┌ Warning: `alias_noise` keyword argument is deprecated, to set `alias_noise`, │ please use an SDEAliasSpecifier, e.g. `solve(prob, alias = SDEAliasSpecifier(alias_noise = true))` │ caller = top-level scope at noise_type_test.jl:59 └ @ Core ~/.julia/packages/StochasticDiffEq/sNZzr/test/noise_type_test.jl:59 WARNING: Method definition g(Any, Any, Any, Any) in module ##Noise Type Tests#145 at /home/pkgeval/.julia/packages/StochasticDiffEq/sNZzr/test/noise_type_test.jl:41 overwritten at /home/pkgeval/.julia/packages/StochasticDiffEq/sNZzr/test/noise_type_test.jl:66. ┌ Warning: `Base.getindex(VA::AbstractDiffEqArray{T, N, A}, i::Int) where {T, N, A <: Union{AbstractArray, AbstractVectorOfArray}}` is deprecated, use `VA.u[i]` instead. │ caller = top-level scope at noise_type_test.jl:539 └ @ Core ~/.julia/packages/StochasticDiffEq/sNZzr/test/noise_type_test.jl:539 ┌ Warning: `alias_noise` keyword argument is deprecated, to set `alias_noise`, │ please use an SDEAliasSpecifier, e.g. `solve(prob, alias = SDEAliasSpecifier(alias_noise = true))` │ caller = top-level scope at noise_type_test.jl:105 └ @ Core ~/.julia/packages/StochasticDiffEq/sNZzr/test/noise_type_test.jl:105 ┌ Warning: `alias_noise` keyword argument is deprecated, to set `alias_noise`, │ please use an SDEAliasSpecifier, e.g. `solve(prob, alias = SDEAliasSpecifier(alias_noise = true))` │ caller = top-level scope at noise_type_test.jl:108 └ @ Core ~/.julia/packages/StochasticDiffEq/sNZzr/test/noise_type_test.jl:108 ┌ Warning: `alias_noise` keyword argument is deprecated, to set `alias_noise`, │ please use an SDEAliasSpecifier, e.g. `solve(prob, alias = SDEAliasSpecifier(alias_noise = true))` │ caller = top-level scope at noise_type_test.jl:114 └ @ Core ~/.julia/packages/StochasticDiffEq/sNZzr/test/noise_type_test.jl:114 Test Summary: | Pass Total Time Noise Type Tests | 2024 2024 2m20.9s 140.896218 seconds (41.79 M allocations: 2.331 GiB, 0.88% gc time, 99.85% compilation time) Test Summary: | Pass Total Time Mass matrix tests | 5 5 1m42.2s 102.159898 seconds (50.19 M allocations: 2.761 GiB, 1.80% gc time, 99.91% compilation time) Scalar g Vector g Implicit EM SKenCarp Test Summary: | Broken Total Time Outofplace Arrays Tests | 3 3 1m55.1s 115.146048 seconds (43.12 M allocations: 2.423 GiB, 0.92% gc time, 99.94% compilation time) WARNING: Imported binding SDEProblemLibrary.prob_sde_linear was undeclared at import time during import to ##tdir Tests#148. WARNING: Imported binding SDEProblemLibrary.prob_sde_2Dlinear was undeclared at import time during import to ##tdir Tests#148. Test Summary: | Pass Total Time tdir Tests | 5 5 1m22.7s 82.688315 seconds (33.94 M allocations: 1.985 GiB, 1.31% gc time, 97.65% compilation time: <1% of which was recompilation) (u, t) = (0.549863280969428, 0.0625) (u, t) = (0.6202962041978632, 0.125) (u, t) = (0.7152273105977963, 0.1875) (u, t) = (0.7000313545432915, 0.25) (u, t) = (0.34534364076926255, 0.3125) (u, t) = (0.36875325671990966, 0.33) (u, t) = (0.48097249983873785, 0.3925) (u, t) = (0.5684659566071866, 0.455) (u, t) = (0.6977112387438974, 0.5175000000000001) (u, t) = (0.7079156024944517, 0.5800000000000001) (u, t) = (0.6937134547051718, 0.6425000000000001) (u, t) = (0.7979147112274164, 0.7050000000000001) (u, t) = (0.8066087043671065, 0.7675000000000001) (u, t) = (0.9622092786672275, 0.8300000000000001) (u, t) = (0.777278659031075, 0.8925000000000001) (u, t) = (1.0561872988940517, 0.9550000000000001) (u, t) = (1.3428482829693857, 1.0) ┌ Warning: Assignment to `integrator` in soft scope is ambiguous because a global variable by the same name exists: `integrator` will be treated as a new local. Disambiguate by using `local integrator` to suppress this warning or `global integrator` to assign to the existing global variable. └ @ ~/.julia/packages/StochasticDiffEq/sNZzr/test/tstops_tests.jl:28 [ Info: 1 [ Info: 2 Test Summary: | Pass Total Time tstops Tests | 11 11 12.4s 12.440279 seconds (3.19 M allocations: 186.982 MiB, 1.28% gc time, 99.65% compilation time: 2% of which was recompilation) [ Info: Warning Expected ┌ Warning: Interrupted. Larger maxiters is needed. If you are using an integrator for non-stiff ODEs or an automatic switching algorithm (the default), you may want to consider using a method for stiff equations. See the solver pages for more details (e.g. https://docs.sciml.ai/DiffEqDocs/stable/solvers/ode_solve/#Stiff-Problems). └ @ SciMLBase ~/.julia/packages/SciMLBase/oZ3WD/src/integrator_interface.jl:623 Test Summary: | Pass Total Time saveat Tests | 10 10 1m00.2s 60.229201 seconds (23.31 M allocations: 1.311 GiB, 2.25% gc time, 99.85% compilation time) Test Summary: | Total Time Oval2 | 0 0.8s 0.775895 seconds (574.81 k allocations: 33.065 MiB, 98.20% compilation time) solver: StochasticDiffEq.SRA{StochasticDiffEq.RosslerSRA{Float64, Float64}}(StochasticDiffEq.RosslerSRA{Float64, Float64}([0.0, 0.75], [1.0, 0.0], [0.0 0.0; 0.75 0.0], [0.0 0.0; 1.5 0.0], [0.3333333333333333, 0.6666666666666666], [1.0, 0.0], [-1.0, 1.0], 2//1)) solver: StochasticDiffEq.SRA1() solver: StochasticDiffEq.SRA2() solver: StochasticDiffEq.SRA3() solver: StochasticDiffEq.SOSRA() solver: StochasticDiffEq.SOSRA2() solver: StochasticDiffEq.SKenCarp{0, true, Nothing, typeof(OrdinaryDiffEqCore.DEFAULT_PRECS), Val{:central}, true, nothing, OrdinaryDiffEqNonlinearSolve.NLNewton{Rational{Int64}, Rational{Int64}, Rational{Int64}, Nothing}, Float64, :Predictive}(nothing, OrdinaryDiffEqNonlinearSolve.NLNewton{Rational{Int64}, Rational{Int64}, Rational{Int64}, Nothing}(1//100, 10, 1//5, 1//5, false, true, nothing), OrdinaryDiffEqCore.DEFAULT_PRECS, true, :min_correct, 0.001, true) solver: StochasticDiffEq.SRA{StochasticDiffEq.RosslerSRA{Float64, Float64}}(StochasticDiffEq.RosslerSRA{Float64, Float64}([0.0, 0.75], [1.0, 0.0], [0.0 0.0; 0.75 0.0], [0.0 0.0; 1.5 0.0], [0.3333333333333333, 0.6666666666666666], [1.0, 0.0], [-1.0, 1.0], 2//1)) solver: StochasticDiffEq.SRA1() solver: StochasticDiffEq.SRA2() solver: StochasticDiffEq.SRA3() solver: StochasticDiffEq.SOSRA() solver: StochasticDiffEq.SOSRA2() solver: StochasticDiffEq.SKenCarp{0, true, Nothing, typeof(OrdinaryDiffEqCore.DEFAULT_PRECS), Val{:central}, true, nothing, OrdinaryDiffEqNonlinearSolve.NLNewton{Rational{Int64}, Rational{Int64}, Rational{Int64}, Nothing}, Float64, :Predictive}(nothing, OrdinaryDiffEqNonlinearSolve.NLNewton{Rational{Int64}, Rational{Int64}, Rational{Int64}, Nothing}(1//100, 10, 1//5, 1//5, false, true, nothing), OrdinaryDiffEqCore.DEFAULT_PRECS, true, :min_correct, 0.001, true) solver: StochasticDiffEq.EulerHeun() solver: StochasticDiffEq.LambaEulerHeun() solver: StochasticDiffEq.RKMil{SciMLBase.AlgorithmInterpretation.Stratonovich}() solver: StochasticDiffEq.RKMilCommute{StochasticDiffEq.IICommutative}(SciMLBase.AlgorithmInterpretation.Stratonovich, StochasticDiffEq.IICommutative()) solver: StochasticDiffEq.RKMilGeneral{StochasticDiffEq.IILevyArea, Nothing}(SciMLBase.AlgorithmInterpretation.Stratonovich, StochasticDiffEq.IILevyArea(), 1, nothing) solver: StochasticDiffEq.SROCK1{SciMLBase.AlgorithmInterpretation.Stratonovich, Nothing}(nothing) solver: StochasticDiffEq.ImplicitEulerHeun{0, true, Nothing, typeof(OrdinaryDiffEqCore.DEFAULT_PRECS), Val{:central}, true, nothing, OrdinaryDiffEqNonlinearSolve.NLNewton{Rational{Int64}, Rational{Int64}, Rational{Int64}, Nothing}, Float64, :Predictive}(nothing, OrdinaryDiffEqNonlinearSolve.NLNewton{Rational{Int64}, Rational{Int64}, Rational{Int64}, Nothing}(1//100, 10, 1//5, 1//5, false, true, nothing), OrdinaryDiffEqCore.DEFAULT_PRECS, 1.0, :constant, 0.001, false) solver: StochasticDiffEq.ImplicitRKMil{0, true, Nothing, typeof(OrdinaryDiffEqCore.DEFAULT_PRECS), Val{:central}, true, nothing, OrdinaryDiffEqNonlinearSolve.NLNewton{Rational{Int64}, Rational{Int64}, Rational{Int64}, Nothing}, Float64, :Predictive, SciMLBase.AlgorithmInterpretation.Stratonovich}(nothing, OrdinaryDiffEqNonlinearSolve.NLNewton{Rational{Int64}, Rational{Int64}, Rational{Int64}, Nothing}(1//100, 10, 1//5, 1//5, false, true, nothing), OrdinaryDiffEqCore.DEFAULT_PRECS, 1.0, :constant, 0.001, false) solver: StochasticDiffEq.ISSEulerHeun{0, true, Nothing, typeof(OrdinaryDiffEqCore.DEFAULT_PRECS), Val{:central}, true, nothing, OrdinaryDiffEqNonlinearSolve.NLNewton{Rational{Int64}, Rational{Int64}, Rational{Int64}, Nothing}, Float64, :Predictive}(nothing, OrdinaryDiffEqNonlinearSolve.NLNewton{Rational{Int64}, Rational{Int64}, Rational{Int64}, Nothing}(1//100, 10, 1//5, 1//5, false, true, nothing), OrdinaryDiffEqCore.DEFAULT_PRECS, 1.0, :constant, 0.001, false) solver: StochasticDiffEq.EulerHeun() solver: StochasticDiffEq.LambaEulerHeun() solver: StochasticDiffEq.RKMil{SciMLBase.AlgorithmInterpretation.Stratonovich}() solver: StochasticDiffEq.RKMilCommute{StochasticDiffEq.IICommutative}(SciMLBase.AlgorithmInterpretation.Stratonovich, StochasticDiffEq.IICommutative()) solver: StochasticDiffEq.RKMilGeneral{StochasticDiffEq.IILevyArea, Nothing}(SciMLBase.AlgorithmInterpretation.Stratonovich, StochasticDiffEq.IILevyArea(), 1, nothing) solver: StochasticDiffEq.SROCK1{SciMLBase.AlgorithmInterpretation.Stratonovich, Nothing}(nothing) solver: StochasticDiffEq.ImplicitEulerHeun{0, true, Nothing, typeof(OrdinaryDiffEqCore.DEFAULT_PRECS), Val{:central}, true, nothing, OrdinaryDiffEqNonlinearSolve.NLNewton{Rational{Int64}, Rational{Int64}, Rational{Int64}, Nothing}, Float64, :Predictive}(nothing, OrdinaryDiffEqNonlinearSolve.NLNewton{Rational{Int64}, Rational{Int64}, Rational{Int64}, Nothing}(1//100, 10, 1//5, 1//5, false, true, nothing), OrdinaryDiffEqCore.DEFAULT_PRECS, 1.0, :constant, 0.001, false) solver: StochasticDiffEq.ImplicitRKMil{0, true, Nothing, typeof(OrdinaryDiffEqCore.DEFAULT_PRECS), Val{:central}, true, nothing, OrdinaryDiffEqNonlinearSolve.NLNewton{Rational{Int64}, Rational{Int64}, Rational{Int64}, Nothing}, Float64, :Predictive, SciMLBase.AlgorithmInterpretation.Stratonovich}(nothing, OrdinaryDiffEqNonlinearSolve.NLNewton{Rational{Int64}, Rational{Int64}, Rational{Int64}, Nothing}(1//100, 10, 1//5, 1//5, false, true, nothing), OrdinaryDiffEqCore.DEFAULT_PRECS, 1.0, :constant, 0.001, false) solver: StochasticDiffEq.ISSEulerHeun{0, true, Nothing, typeof(OrdinaryDiffEqCore.DEFAULT_PRECS), Val{:central}, true, nothing, OrdinaryDiffEqNonlinearSolve.NLNewton{Rational{Int64}, Rational{Int64}, Rational{Int64}, Nothing}, Float64, :Predictive}(nothing, OrdinaryDiffEqNonlinearSolve.NLNewton{Rational{Int64}, Rational{Int64}, Rational{Int64}, Nothing}(1//100, 10, 1//5, 1//5, false, true, nothing), OrdinaryDiffEqCore.DEFAULT_PRECS, 1.0, :constant, 0.001, false) solver: StochasticDiffEq.EM{true}() Ito Solver Reversal Tests (out-of-place): Error During Test at /home/pkgeval/.julia/packages/StochasticDiffEq/sNZzr/test/reversal_tests.jl:118 Got exception outside of a @test An indexing operation was performed on a NullParameters object. This means no parameters were passed into the AbstractSciMLProblem (e.x.: ODEProblem) but the parameters object `p` was used in an indexing expression (e.x. `p[i]`, or `x .+ p`). Two common reasons for this issue are: 1. Forgetting to pass parameters into the problem constructor. For example, `ODEProblem(f,u0,tspan)` should be `ODEProblem(f,u0,tspan,p)` in order to use parameters. 2. Using the wrong function signature. For example, with `ODEProblem`s the function signature is always `f(du,u,p,t)` for the in-place form or `f(u,p,t)` for the out-of-place form. Note that the `p` argument will always be in the function signature regardless of if the problem is defined with parameters! Stacktrace: [1] getindex(::SciMLBase.NullParameters, i::Int64) @ SciMLBase ~/.julia/packages/SciMLBase/oZ3WD/src/problems/problem_utils.jl:177 [2] macro expansion @ ~/.julia/packages/SymbolicUtils/N76BL/src/code.jl:411 [inlined] [3] macro expansion @ ~/.julia/packages/Symbolics/FHhXE/src/build_function.jl:366 [inlined] [4] macro expansion @ ~/.julia/packages/RuntimeGeneratedFunctions/2SjTC/src/RuntimeGeneratedFunctions.jl:161 [inlined] [5] macro expansion @ ./none:0 [inlined] [6] generated_callfunc @ ./none:0 [inlined] [7] (::RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:__mtk_arg_1, :___mtkparameters___, :t), ModelingToolkit.var"#_RGF_ModTag", ModelingToolkit.var"#_RGF_ModTag", (0x04e619b6, 0xbe01ac01, 0x40600b99, 0x859a22c8, 0xb582487f), Nothing})(::Vector{Float64}, ::SciMLBase.NullParameters, ::Float64) @ RuntimeGeneratedFunctions ~/.julia/packages/RuntimeGeneratedFunctions/2SjTC/src/RuntimeGeneratedFunctions.jl:148 [8] (::SciMLBase.SDEFunction{false, SciMLBase.FullSpecialize, RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:__mtk_arg_1, :___mtkparameters___, :t), ModelingToolkit.var"#_RGF_ModTag", ModelingToolkit.var"#_RGF_ModTag", (0x04e619b6, 0xbe01ac01, 0x40600b99, 0x859a22c8, 0xb582487f), Nothing}, typeof(SDEProblemLibrary.σ_linear), LinearAlgebra.UniformScaling{Bool}, typeof(SDEProblemLibrary.linear_analytic), Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing, Nothing})(u::Vector{Float64}, p::SciMLBase.NullParameters, t::Float64) @ SciMLBase ~/.julia/packages/SciMLBase/oZ3WD/src/scimlfunctions.jl:2663 [9] perform_step!(integrator::StochasticDiffEq.SDEIntegrator{StochasticDiffEq.EM{true}, false, Vector{Float64}, Float64, Float64, Float64, SciMLBase.NullParameters, Float64, Float64, Float64, DiffEqNoiseProcess.NoiseGrid{Float64, 0, Float64, Float64, Float64, Vector{Float64}, Base.RefValue{Int64}, false}, Nothing, Vector{Float64}, SciMLBase.RODESolution{Float64, 2, Vector{Vector{Float64}}, Vector{Vector{Float64}}, Dict{Symbol, Float64}, Vector{Float64}, DiffEqNoiseProcess.NoiseGrid{Float64, 0, Float64, Float64, Float64, Vector{Float64}, Base.RefValue{Int64}, false}, Nothing, SciMLBase.SDEProblem{Vector{Float64}, Tuple{Float64, Float64}, false, SciMLBase.NullParameters, DiffEqNoiseProcess.NoiseGrid{Float64, 0, Float64, Float64, Float64, Vector{Float64}, Base.RefValue{Int64}, false}, SciMLBase.SDEFunction{false, SciMLBase.FullSpecialize, RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:__mtk_arg_1, :___mtkparameters___, :t), ModelingToolkit.var"#_RGF_ModTag", ModelingToolkit.var"#_RGF_ModTag", (0x04e619b6, 0xbe01ac01, 0x40600b99, 0x859a22c8, 0xb582487f), Nothing}, typeof(SDEProblemLibrary.σ_linear), LinearAlgebra.UniformScaling{Bool}, typeof(SDEProblemLibrary.linear_analytic), Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing, Nothing}, typeof(SDEProblemLibrary.σ_linear), @Kwargs{}, Nothing}, StochasticDiffEq.EM{true}, StochasticDiffEq.LinearInterpolationData{Vector{Vector{Float64}}, Vector{Float64}}, SciMLBase.DEStats, Nothing, Nothing}, StochasticDiffEq.EMConstantCache, SciMLBase.SDEFunction{false, SciMLBase.FullSpecialize, RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:__mtk_arg_1, :___mtkparameters___, :t), ModelingToolkit.var"#_RGF_ModTag", ModelingToolkit.var"#_RGF_ModTag", (0x04e619b6, 0xbe01ac01, 0x40600b99, 0x859a22c8, 0xb582487f), Nothing}, typeof(SDEProblemLibrary.σ_linear), LinearAlgebra.UniformScaling{Bool}, typeof(SDEProblemLibrary.linear_analytic), Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing, Nothing}, typeof(SDEProblemLibrary.σ_linear), Nothing, StochasticDiffEq.SDEOptions{Float64, Float64, OrdinaryDiffEqCore.PIController{Float64}, typeof(DiffEqBase.ODE_DEFAULT_NORM), Nothing, SciMLBase.CallbackSet{Tuple{}, Tuple{}}, typeof(DiffEqBase.ODE_DEFAULT_ISOUTOFDOMAIN), typeof(DiffEqBase.ODE_DEFAULT_PROG_MESSAGE), typeof(DiffEqBase.ODE_DEFAULT_UNSTABLE_CHECK), DataStructures.BinaryHeap{Float64, DataStructures.FasterForward}, DataStructures.BinaryHeap{Float64, DataStructures.FasterForward}, Nothing, Nothing, Int64, Float64, Float64, Float64, Tuple{}, Tuple{}, Tuple{}}, DiffEqNoiseProcess.NoiseGrid{Float64, 0, Float64, Float64, Float64, Vector{Float64}, Base.RefValue{Int64}, false}, Float64, Nothing, Nothing, OrdinaryDiffEqCore.DefaultInit}, cache::StochasticDiffEq.EMConstantCache) @ StochasticDiffEq ~/.julia/packages/StochasticDiffEq/sNZzr/src/perform_step/low_order.jl:4 [10] solve!(integrator::StochasticDiffEq.SDEIntegrator{StochasticDiffEq.EM{true}, false, Vector{Float64}, Float64, Float64, Float64, SciMLBase.NullParameters, Float64, Float64, Float64, DiffEqNoiseProcess.NoiseGrid{Float64, 0, Float64, Float64, Float64, Vector{Float64}, Base.RefValue{Int64}, false}, Nothing, Vector{Float64}, SciMLBase.RODESolution{Float64, 2, Vector{Vector{Float64}}, Vector{Vector{Float64}}, Dict{Symbol, Float64}, Vector{Float64}, DiffEqNoiseProcess.NoiseGrid{Float64, 0, Float64, Float64, Float64, Vector{Float64}, Base.RefValue{Int64}, false}, Nothing, SciMLBase.SDEProblem{Vector{Float64}, Tuple{Float64, Float64}, false, SciMLBase.NullParameters, DiffEqNoiseProcess.NoiseGrid{Float64, 0, Float64, Float64, Float64, Vector{Float64}, Base.RefValue{Int64}, false}, SciMLBase.SDEFunction{false, SciMLBase.FullSpecialize, RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:__mtk_arg_1, :___mtkparameters___, :t), ModelingToolkit.var"#_RGF_ModTag", ModelingToolkit.var"#_RGF_ModTag", (0x04e619b6, 0xbe01ac01, 0x40600b99, 0x859a22c8, 0xb582487f), Nothing}, typeof(SDEProblemLibrary.σ_linear), LinearAlgebra.UniformScaling{Bool}, typeof(SDEProblemLibrary.linear_analytic), Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing, Nothing}, typeof(SDEProblemLibrary.σ_linear), @Kwargs{}, Nothing}, StochasticDiffEq.EM{true}, StochasticDiffEq.LinearInterpolationData{Vector{Vector{Float64}}, Vector{Float64}}, SciMLBase.DEStats, Nothing, Nothing}, StochasticDiffEq.EMConstantCache, SciMLBase.SDEFunction{false, SciMLBase.FullSpecialize, RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:__mtk_arg_1, :___mtkparameters___, :t), ModelingToolkit.var"#_RGF_ModTag", ModelingToolkit.var"#_RGF_ModTag", (0x04e619b6, 0xbe01ac01, 0x40600b99, 0x859a22c8, 0xb582487f), Nothing}, typeof(SDEProblemLibrary.σ_linear), LinearAlgebra.UniformScaling{Bool}, typeof(SDEProblemLibrary.linear_analytic), Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing, Nothing}, typeof(SDEProblemLibrary.σ_linear), Nothing, StochasticDiffEq.SDEOptions{Float64, Float64, OrdinaryDiffEqCore.PIController{Float64}, typeof(DiffEqBase.ODE_DEFAULT_NORM), Nothing, SciMLBase.CallbackSet{Tuple{}, Tuple{}}, typeof(DiffEqBase.ODE_DEFAULT_ISOUTOFDOMAIN), typeof(DiffEqBase.ODE_DEFAULT_PROG_MESSAGE), typeof(DiffEqBase.ODE_DEFAULT_UNSTABLE_CHECK), DataStructures.BinaryHeap{Float64, DataStructures.FasterForward}, DataStructures.BinaryHeap{Float64, DataStructures.FasterForward}, Nothing, Nothing, Int64, Float64, Float64, Float64, Tuple{}, Tuple{}, Tuple{}}, DiffEqNoiseProcess.NoiseGrid{Float64, 0, Float64, Float64, Float64, Vector{Float64}, Base.RefValue{Int64}, false}, Float64, Nothing, Nothing, OrdinaryDiffEqCore.DefaultInit}) @ StochasticDiffEq ~/.julia/packages/StochasticDiffEq/sNZzr/src/solve.jl:725 [11] __solve(prob::SciMLBase.SDEProblem{Vector{Float64}, Tuple{Float64, Float64}, false, SciMLBase.NullParameters, DiffEqNoiseProcess.NoiseGrid{Float64, 0, Float64, Float64, Float64, Vector{Float64}, Base.RefValue{Int64}, false}, SciMLBase.SDEFunction{false, SciMLBase.FullSpecialize, RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:__mtk_arg_1, :___mtkparameters___, :t), ModelingToolkit.var"#_RGF_ModTag", ModelingToolkit.var"#_RGF_ModTag", (0x04e619b6, 0xbe01ac01, 0x40600b99, 0x859a22c8, 0xb582487f), Nothing}, typeof(SDEProblemLibrary.σ_linear), LinearAlgebra.UniformScaling{Bool}, typeof(SDEProblemLibrary.linear_analytic), Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing, Nothing}, typeof(SDEProblemLibrary.σ_linear), @Kwargs{}, Nothing}, alg::StochasticDiffEq.EM{true}, timeseries::Vector{Any}, ts::Vector{Any}, ks::Nothing, recompile::Type{Val{true}}; kwargs::@Kwargs{dt::Float64, adaptive::Bool}) @ StochasticDiffEq ~/.julia/packages/StochasticDiffEq/sNZzr/src/solve.jl:7 ┌[12] __solve │ @ ~/.julia/packages/StochasticDiffEq/sNZzr/src/solve.jl:1 [inlined] ╰──── repeated 5 times [17] #solve_call#21 @ ~/.julia/packages/DiffEqBase/dqv41/src/solve.jl:127 [inlined] [18] solve_call @ ~/.julia/packages/DiffEqBase/dqv41/src/solve.jl:84 [inlined] [19] #solve_up#31 @ ~/.julia/packages/DiffEqBase/dqv41/src/solve.jl:683 [inlined] [20] solve_up @ ~/.julia/packages/DiffEqBase/dqv41/src/solve.jl:660 [inlined] [21] #solve#29 @ ~/.julia/packages/DiffEqBase/dqv41/src/solve.jl:555 [inlined] [22] kwcall(::@NamedTuple{dt::Float64, adaptive::Bool}, ::typeof(CommonSolve.solve), prob::SciMLBase.SDEProblem{Vector{Float64}, Tuple{Float64, Float64}, false, SciMLBase.NullParameters, DiffEqNoiseProcess.NoiseGrid{Float64, 0, Float64, Float64, Float64, Vector{Float64}, Base.RefValue{Int64}, false}, SciMLBase.SDEFunction{false, SciMLBase.FullSpecialize, RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:__mtk_arg_1, :___mtkparameters___, :t), ModelingToolkit.var"#_RGF_ModTag", ModelingToolkit.var"#_RGF_ModTag", (0x04e619b6, 0xbe01ac01, 0x40600b99, 0x859a22c8, 0xb582487f), Nothing}, typeof(SDEProblemLibrary.σ_linear), LinearAlgebra.UniformScaling{Bool}, typeof(SDEProblemLibrary.linear_analytic), Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing, Nothing}, typeof(SDEProblemLibrary.σ_linear), @Kwargs{}, Nothing}, args::StochasticDiffEq.EM{true}) @ DiffEqBase ~/.julia/packages/DiffEqBase/dqv41/src/solve.jl:545 [23] macro expansion @ ~/.julia/packages/StochasticDiffEq/sNZzr/test/reversal_tests.jl:143 [inlined] [24] macro expansion @ /opt/julia/share/julia/stdlib/v1.13/Test/src/Test.jl:2033 [inlined] [25] top-level scope @ ~/.julia/packages/StochasticDiffEq/sNZzr/test/reversal_tests.jl:2057 [26] include(mapexpr::Function, mod::Module, _path::String) @ Base ./Base.jl:309 [27] top-level scope @ ~/.julia/packages/SafeTestsets/raUNr/src/SafeTestsets.jl:56 [28] macro expansion @ /opt/julia/share/julia/stdlib/v1.13/Test/src/Test.jl:1952 [inlined] [29] macro expansion @ ~/.julia/packages/StochasticDiffEq/sNZzr/test/runtests.jl:56 [inlined] [30] eval(m::Module, e::Any) @ Core ./boot.jl:489 [31] macro expansion @ ~/.julia/packages/SafeTestsets/raUNr/src/SafeTestsets.jl:28 [inlined] [32] macro expansion @ ./timing.jl:645 [inlined] [33] macro expansion @ ~/.julia/packages/StochasticDiffEq/sNZzr/test/runtests.jl:55 [inlined] [34] macro expansion @ ./timing.jl:645 [inlined] [35] top-level scope @ ~/.julia/packages/StochasticDiffEq/sNZzr/test/runtests.jl:353 [36] include(mapexpr::Function, mod::Module, _path::String) @ Base ./Base.jl:309 [37] top-level scope @ none:6 [38] eval(m::Module, e::Any) @ Core ./boot.jl:489 [39] exec_options(opts::Base.JLOptions) @ Base ./client.jl:296 [40] _start() @ Base ./client.jl:563 solver: StochasticDiffEq.EM{true}() Ito Solver Reversal Tests (in-place): Error During Test at /home/pkgeval/.julia/packages/StochasticDiffEq/sNZzr/test/reversal_tests.jl:118 Got exception outside of a @test An indexing operation was performed on a NullParameters object. This means no parameters were passed into the AbstractSciMLProblem (e.x.: ODEProblem) but the parameters object `p` was used in an indexing expression (e.x. `p[i]`, or `x .+ p`). Two common reasons for this issue are: 1. Forgetting to pass parameters into the problem constructor. For example, `ODEProblem(f,u0,tspan)` should be `ODEProblem(f,u0,tspan,p)` in order to use parameters. 2. Using the wrong function signature. For example, with `ODEProblem`s the function signature is always `f(du,u,p,t)` for the in-place form or `f(u,p,t)` for the out-of-place form. Note that the `p` argument will always be in the function signature regardless of if the problem is defined with parameters! Stacktrace: [1] getindex(::SciMLBase.NullParameters, i::Int64) @ SciMLBase ~/.julia/packages/SciMLBase/oZ3WD/src/problems/problem_utils.jl:177 [2] macro expansion @ ~/.julia/packages/SymbolicUtils/N76BL/src/code.jl:411 [inlined] [3] macro expansion @ ~/.julia/packages/Symbolics/FHhXE/src/build_function.jl:368 [inlined] [4] macro expansion @ ~/.julia/packages/RuntimeGeneratedFunctions/2SjTC/src/RuntimeGeneratedFunctions.jl:161 [inlined] [5] macro expansion @ ./none:0 [inlined] [6] generated_callfunc @ ./none:0 [inlined] [7] (::RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:ˍ₋out, :__mtk_arg_1, :___mtkparameters___, :t), ModelingToolkit.var"#_RGF_ModTag", ModelingToolkit.var"#_RGF_ModTag", (0x2345b8cf, 0xdd3bb0ed, 0xb38c633b, 0x2bd7618f, 0x73b4bb8a), Nothing})(::Vector{Float64}, ::Vector{Float64}, ::SciMLBase.NullParameters, ::Float64) @ RuntimeGeneratedFunctions ~/.julia/packages/RuntimeGeneratedFunctions/2SjTC/src/RuntimeGeneratedFunctions.jl:148 [8] (::SciMLBase.SDEFunction{true, SciMLBase.FullSpecialize, RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:ˍ₋out, :__mtk_arg_1, :___mtkparameters___, :t), ModelingToolkit.var"#_RGF_ModTag", ModelingToolkit.var"#_RGF_ModTag", (0x2345b8cf, 0xdd3bb0ed, 0xb38c633b, 0x2bd7618f, 0x73b4bb8a), Nothing}, typeof(SDEProblemLibrary.σ_linear_iip), LinearAlgebra.UniformScaling{Bool}, typeof(SDEProblemLibrary.linear_analytic), Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing, Nothing})(du::Vector{Float64}, u::Vector{Float64}, p::SciMLBase.NullParameters, t::Float64) @ SciMLBase ~/.julia/packages/SciMLBase/oZ3WD/src/scimlfunctions.jl:2655 [9] perform_step!(integrator::StochasticDiffEq.SDEIntegrator{StochasticDiffEq.EM{true}, true, Vector{Float64}, Float64, Float64, Float64, SciMLBase.NullParameters, Float64, Float64, Float64, DiffEqNoiseProcess.NoiseGrid{Float64, 0, Float64, Float64, Float64, Vector{Float64}, Base.RefValue{Int64}, false}, Nothing, Vector{Float64}, SciMLBase.RODESolution{Float64, 2, Vector{Vector{Float64}}, Vector{Vector{Float64}}, Dict{Symbol, Float64}, Vector{Float64}, DiffEqNoiseProcess.NoiseGrid{Float64, 0, Float64, Float64, Float64, Vector{Float64}, Base.RefValue{Int64}, false}, Nothing, SciMLBase.SDEProblem{Vector{Float64}, Tuple{Float64, Float64}, true, SciMLBase.NullParameters, DiffEqNoiseProcess.NoiseGrid{Float64, 0, Float64, Float64, Float64, Vector{Float64}, Base.RefValue{Int64}, false}, SciMLBase.SDEFunction{true, SciMLBase.FullSpecialize, RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:ˍ₋out, :__mtk_arg_1, :___mtkparameters___, :t), ModelingToolkit.var"#_RGF_ModTag", ModelingToolkit.var"#_RGF_ModTag", (0x2345b8cf, 0xdd3bb0ed, 0xb38c633b, 0x2bd7618f, 0x73b4bb8a), Nothing}, typeof(SDEProblemLibrary.σ_linear_iip), LinearAlgebra.UniformScaling{Bool}, typeof(SDEProblemLibrary.linear_analytic), Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing, Nothing}, typeof(SDEProblemLibrary.σ_linear_iip), @Kwargs{}, Nothing}, StochasticDiffEq.EM{true}, StochasticDiffEq.LinearInterpolationData{Vector{Vector{Float64}}, Vector{Float64}}, SciMLBase.DEStats, Nothing, Nothing}, StochasticDiffEq.EMCache{Vector{Float64}, Vector{Float64}, Vector{Float64}}, SciMLBase.SDEFunction{true, SciMLBase.FullSpecialize, RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:ˍ₋out, :__mtk_arg_1, :___mtkparameters___, :t), ModelingToolkit.var"#_RGF_ModTag", ModelingToolkit.var"#_RGF_ModTag", (0x2345b8cf, 0xdd3bb0ed, 0xb38c633b, 0x2bd7618f, 0x73b4bb8a), Nothing}, typeof(SDEProblemLibrary.σ_linear_iip), LinearAlgebra.UniformScaling{Bool}, typeof(SDEProblemLibrary.linear_analytic), Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing, Nothing}, typeof(SDEProblemLibrary.σ_linear_iip), Nothing, StochasticDiffEq.SDEOptions{Float64, Float64, OrdinaryDiffEqCore.PIController{Float64}, typeof(DiffEqBase.ODE_DEFAULT_NORM), Nothing, SciMLBase.CallbackSet{Tuple{}, Tuple{}}, typeof(DiffEqBase.ODE_DEFAULT_ISOUTOFDOMAIN), typeof(DiffEqBase.ODE_DEFAULT_PROG_MESSAGE), typeof(DiffEqBase.ODE_DEFAULT_UNSTABLE_CHECK), DataStructures.BinaryHeap{Float64, DataStructures.FasterForward}, DataStructures.BinaryHeap{Float64, DataStructures.FasterForward}, Nothing, Nothing, Int64, Float64, Float64, Float64, Tuple{}, Tuple{}, Tuple{}}, DiffEqNoiseProcess.NoiseGrid{Float64, 0, Float64, Float64, Float64, Vector{Float64}, Base.RefValue{Int64}, false}, Float64, Nothing, Nothing, OrdinaryDiffEqCore.DefaultInit}, cache::StochasticDiffEq.EMCache{Vector{Float64}, Vector{Float64}, Vector{Float64}}) @ StochasticDiffEq ~/.julia/packages/StochasticDiffEq/sNZzr/src/perform_step/low_order.jl:30 [10] solve!(integrator::StochasticDiffEq.SDEIntegrator{StochasticDiffEq.EM{true}, true, Vector{Float64}, Float64, Float64, Float64, SciMLBase.NullParameters, Float64, Float64, Float64, DiffEqNoiseProcess.NoiseGrid{Float64, 0, Float64, Float64, Float64, Vector{Float64}, Base.RefValue{Int64}, false}, Nothing, Vector{Float64}, SciMLBase.RODESolution{Float64, 2, Vector{Vector{Float64}}, Vector{Vector{Float64}}, Dict{Symbol, Float64}, Vector{Float64}, DiffEqNoiseProcess.NoiseGrid{Float64, 0, Float64, Float64, Float64, Vector{Float64}, Base.RefValue{Int64}, false}, Nothing, SciMLBase.SDEProblem{Vector{Float64}, Tuple{Float64, Float64}, true, SciMLBase.NullParameters, DiffEqNoiseProcess.NoiseGrid{Float64, 0, Float64, Float64, Float64, Vector{Float64}, Base.RefValue{Int64}, false}, SciMLBase.SDEFunction{true, SciMLBase.FullSpecialize, RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:ˍ₋out, :__mtk_arg_1, :___mtkparameters___, :t), ModelingToolkit.var"#_RGF_ModTag", ModelingToolkit.var"#_RGF_ModTag", (0x2345b8cf, 0xdd3bb0ed, 0xb38c633b, 0x2bd7618f, 0x73b4bb8a), Nothing}, typeof(SDEProblemLibrary.σ_linear_iip), LinearAlgebra.UniformScaling{Bool}, typeof(SDEProblemLibrary.linear_analytic), Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing, Nothing}, typeof(SDEProblemLibrary.σ_linear_iip), @Kwargs{}, Nothing}, StochasticDiffEq.EM{true}, StochasticDiffEq.LinearInterpolationData{Vector{Vector{Float64}}, Vector{Float64}}, SciMLBase.DEStats, Nothing, Nothing}, StochasticDiffEq.EMCache{Vector{Float64}, Vector{Float64}, Vector{Float64}}, SciMLBase.SDEFunction{true, SciMLBase.FullSpecialize, RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:ˍ₋out, :__mtk_arg_1, :___mtkparameters___, :t), ModelingToolkit.var"#_RGF_ModTag", ModelingToolkit.var"#_RGF_ModTag", (0x2345b8cf, 0xdd3bb0ed, 0xb38c633b, 0x2bd7618f, 0x73b4bb8a), Nothing}, typeof(SDEProblemLibrary.σ_linear_iip), LinearAlgebra.UniformScaling{Bool}, typeof(SDEProblemLibrary.linear_analytic), Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing, Nothing}, typeof(SDEProblemLibrary.σ_linear_iip), Nothing, StochasticDiffEq.SDEOptions{Float64, Float64, OrdinaryDiffEqCore.PIController{Float64}, typeof(DiffEqBase.ODE_DEFAULT_NORM), Nothing, SciMLBase.CallbackSet{Tuple{}, Tuple{}}, typeof(DiffEqBase.ODE_DEFAULT_ISOUTOFDOMAIN), typeof(DiffEqBase.ODE_DEFAULT_PROG_MESSAGE), typeof(DiffEqBase.ODE_DEFAULT_UNSTABLE_CHECK), DataStructures.BinaryHeap{Float64, DataStructures.FasterForward}, DataStructures.BinaryHeap{Float64, DataStructures.FasterForward}, Nothing, Nothing, Int64, Float64, Float64, Float64, Tuple{}, Tuple{}, Tuple{}}, DiffEqNoiseProcess.NoiseGrid{Float64, 0, Float64, Float64, Float64, Vector{Float64}, Base.RefValue{Int64}, false}, Float64, Nothing, Nothing, OrdinaryDiffEqCore.DefaultInit}) @ StochasticDiffEq ~/.julia/packages/StochasticDiffEq/sNZzr/src/solve.jl:725 [11] __solve(prob::SciMLBase.SDEProblem{Vector{Float64}, Tuple{Float64, Float64}, true, SciMLBase.NullParameters, DiffEqNoiseProcess.NoiseGrid{Float64, 0, Float64, Float64, Float64, Vector{Float64}, Base.RefValue{Int64}, false}, SciMLBase.SDEFunction{true, SciMLBase.FullSpecialize, RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:ˍ₋out, :__mtk_arg_1, :___mtkparameters___, :t), ModelingToolkit.var"#_RGF_ModTag", ModelingToolkit.var"#_RGF_ModTag", (0x2345b8cf, 0xdd3bb0ed, 0xb38c633b, 0x2bd7618f, 0x73b4bb8a), Nothing}, typeof(SDEProblemLibrary.σ_linear_iip), LinearAlgebra.UniformScaling{Bool}, typeof(SDEProblemLibrary.linear_analytic), Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing, Nothing}, typeof(SDEProblemLibrary.σ_linear_iip), @Kwargs{}, Nothing}, alg::StochasticDiffEq.EM{true}, timeseries::Vector{Any}, ts::Vector{Any}, ks::Nothing, recompile::Type{Val{true}}; kwargs::@Kwargs{dt::Float64, adaptive::Bool}) @ StochasticDiffEq ~/.julia/packages/StochasticDiffEq/sNZzr/src/solve.jl:7 ┌[12] __solve │ @ ~/.julia/packages/StochasticDiffEq/sNZzr/src/solve.jl:1 [inlined] ╰──── repeated 5 times [17] #solve_call#21 @ ~/.julia/packages/DiffEqBase/dqv41/src/solve.jl:127 [inlined] [18] solve_call @ ~/.julia/packages/DiffEqBase/dqv41/src/solve.jl:84 [inlined] [19] #solve_up#31 @ ~/.julia/packages/DiffEqBase/dqv41/src/solve.jl:683 [inlined] [20] solve_up @ ~/.julia/packages/DiffEqBase/dqv41/src/solve.jl:660 [inlined] [21] #solve#29 @ ~/.julia/packages/DiffEqBase/dqv41/src/solve.jl:555 [inlined] [22] kwcall(::@NamedTuple{dt::Float64, adaptive::Bool}, ::typeof(CommonSolve.solve), prob::SciMLBase.SDEProblem{Vector{Float64}, Tuple{Float64, Float64}, true, SciMLBase.NullParameters, DiffEqNoiseProcess.NoiseGrid{Float64, 0, Float64, Float64, Float64, Vector{Float64}, Base.RefValue{Int64}, false}, SciMLBase.SDEFunction{true, SciMLBase.FullSpecialize, RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:ˍ₋out, :__mtk_arg_1, :___mtkparameters___, :t), ModelingToolkit.var"#_RGF_ModTag", ModelingToolkit.var"#_RGF_ModTag", (0x2345b8cf, 0xdd3bb0ed, 0xb38c633b, 0x2bd7618f, 0x73b4bb8a), Nothing}, typeof(SDEProblemLibrary.σ_linear_iip), LinearAlgebra.UniformScaling{Bool}, typeof(SDEProblemLibrary.linear_analytic), Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing, Nothing}, typeof(SDEProblemLibrary.σ_linear_iip), @Kwargs{}, Nothing}, args::StochasticDiffEq.EM{true}) @ DiffEqBase ~/.julia/packages/DiffEqBase/dqv41/src/solve.jl:545 [23] macro expansion @ ~/.julia/packages/StochasticDiffEq/sNZzr/test/reversal_tests.jl:143 [inlined] [24] macro expansion @ /opt/julia/share/julia/stdlib/v1.13/Test/src/Test.jl:2033 [inlined] [25] top-level scope @ ~/.julia/packages/StochasticDiffEq/sNZzr/test/reversal_tests.jl:2057 [26] include(mapexpr::Function, mod::Module, _path::String) @ Base ./Base.jl:309 [27] top-level scope @ ~/.julia/packages/SafeTestsets/raUNr/src/SafeTestsets.jl:56 [28] macro expansion @ /opt/julia/share/julia/stdlib/v1.13/Test/src/Test.jl:1952 [inlined] [29] macro expansion @ ~/.julia/packages/StochasticDiffEq/sNZzr/test/runtests.jl:56 [inlined] [30] eval(m::Module, e::Any) @ Core ./boot.jl:489 [31] macro expansion @ ~/.julia/packages/SafeTestsets/raUNr/src/SafeTestsets.jl:28 [inlined] [32] macro expansion @ ./timing.jl:645 [inlined] [33] macro expansion @ ~/.julia/packages/StochasticDiffEq/sNZzr/test/runtests.jl:55 [inlined] [34] macro expansion @ ./timing.jl:645 [inlined] [35] top-level scope @ ~/.julia/packages/StochasticDiffEq/sNZzr/test/runtests.jl:353 [36] include(mapexpr::Function, mod::Module, _path::String) @ Base ./Base.jl:309 [37] top-level scope @ none:6 [38] eval(m::Module, e::Any) @ Core ./boot.jl:489 [39] exec_options(opts::Base.JLOptions) @ Base ./client.jl:296 [40] _start() @ Base ./client.jl:563 Test Summary: | Pass Error Total Time Solver Reversal Tests | 64 2 66 13m07.1s Additive Noise Solver Reversal Tests (out-of-place) | 14 14 1m22.5s Additive Noise Solver Reversal Tests (in-place) | 14 14 2m34.1s Stratonovich Solver Reversal Tests (out-of-place) | 18 18 1m19.2s Stratonovich Solver Reversal Tests (in-place) | 18 18 4m16.4s Ito Solver Reversal Tests (out-of-place) | 1 1 1m53.7s Ito Solver Reversal Tests (in-place) | 1 1 18.5s RNG of the outermost testset: Random.Xoshiro(0x66c915880c0757b6, 0x717087d0256bec1e, 0x0eb904620d31b045, 0x7db0f1c8350ec3d8, 0x748e5f5c31aae851) ERROR: LoadError: Some tests did not pass: 64 passed, 0 failed, 2 errored, 0 broken. in expression starting at /home/pkgeval/.julia/packages/StochasticDiffEq/sNZzr/test/runtests.jl:16 Testing failed after 1719.26s ERROR: LoadError: Package StochasticDiffEq errored during testing Stacktrace: [1] pkgerror(msg::String) @ Pkg.Types /opt/julia/share/julia/stdlib/v1.13/Pkg/src/Types.jl:68 [2] test(ctx::Pkg.Types.Context, pkgs::Vector{PackageSpec}; coverage::Bool, julia_args::Cmd, test_args::Cmd, test_fn::Nothing, force_latest_compatible_version::Bool, allow_earlier_backwards_compatible_versions::Bool, allow_reresolve::Bool) @ Pkg.Operations /opt/julia/share/julia/stdlib/v1.13/Pkg/src/Operations.jl:2673 [3] test @ /opt/julia/share/julia/stdlib/v1.13/Pkg/src/Operations.jl:2522 [inlined] [4] test(ctx::Pkg.Types.Context, pkgs::Vector{PackageSpec}; coverage::Bool, test_fn::Nothing, julia_args::Cmd, test_args::Cmd, force_latest_compatible_version::Bool, allow_earlier_backwards_compatible_versions::Bool, allow_reresolve::Bool, kwargs::@Kwargs{io::IOContext{IO}}) @ Pkg.API /opt/julia/share/julia/stdlib/v1.13/Pkg/src/API.jl:538 [5] kwcall(::@NamedTuple{julia_args::Cmd, io::IOContext{IO}}, ::typeof(Pkg.API.test), ctx::Pkg.Types.Context, pkgs::Vector{PackageSpec}) @ Pkg.API /opt/julia/share/julia/stdlib/v1.13/Pkg/src/API.jl:515 [6] test(pkgs::Vector{PackageSpec}; io::IOContext{IO}, kwargs::@Kwargs{julia_args::Cmd}) @ Pkg.API /opt/julia/share/julia/stdlib/v1.13/Pkg/src/API.jl:168 [7] kwcall(::@NamedTuple{julia_args::Cmd}, ::typeof(Pkg.API.test), pkgs::Vector{PackageSpec}) @ Pkg.API /opt/julia/share/julia/stdlib/v1.13/Pkg/src/API.jl:157 [8] test(pkgs::Vector{String}; kwargs::@Kwargs{julia_args::Cmd}) @ Pkg.API /opt/julia/share/julia/stdlib/v1.13/Pkg/src/API.jl:156 [9] test @ /opt/julia/share/julia/stdlib/v1.13/Pkg/src/API.jl:156 [inlined] [10] kwcall(::@NamedTuple{julia_args::Cmd}, ::typeof(Pkg.API.test), pkg::String) @ Pkg.API /opt/julia/share/julia/stdlib/v1.13/Pkg/src/API.jl:155 [11] top-level scope @ /PkgEval.jl/scripts/evaluate.jl:219 [12] include(mod::Module, _path::String) @ Base ./Base.jl:308 [13] exec_options(opts::Base.JLOptions) @ Base ./client.jl:330 [14] _start() @ Base ./client.jl:563 in expression starting at /PkgEval.jl/scripts/evaluate.jl:210 PkgEval failed after 1804.2s: package tests unexpectedly errored