Package evaluation to test RetentionParameterEstimator on Julia 1.12.7-DEV.42 (6f510b6086*) started at 2026-06-20T12:52:06.328 ################################################################################ # Set-up # Installing PkgEval dependencies (TestEnv)... Activating project at `~/.julia/environments/v1.12` Set-up completed after 7.85s ################################################################################ # Installation # Installing RetentionParameterEstimator... Resolving package versions... Updating `~/.julia/environments/v1.12/Project.toml` [0afdae40] + RetentionParameterEstimator v0.2.1 Updating `~/.julia/environments/v1.12/Manifest.toml` [47edcb42] + ADTypes v1.22.0 [14f7f29c] + AMD v0.5.3 [621f4979] + AbstractFFTs v1.5.0 [6e696c72] + AbstractPlutoDingetjes v1.4.0 [1520ce14] + AbstractTrees v0.4.5 [7d9f7c33] + Accessors v0.1.44 [79e6a3ab] + Adapt v4.6.1 [66dad0bd] + AliasTables v1.1.3 [7d9fca2a] + Arpack v0.5.4 [4fba245c] + ArrayInterface v7.25.0 [69666777] + Arrow v2.8.1 [31f734f8] + ArrowTypes v2.3.0 [13072b0f] + AxisAlgorithms v1.1.0 [6e4b80f9] + BenchmarkTools v1.8.0 [d1d4a3ce] + BitFlags v0.1.10 [c3b6d118] + BitIntegers v0.3.7 [62783981] + BitTwiddlingConvenienceFunctions v0.1.6 [a134a8b2] + BlackBoxOptim v0.6.5 [70df07ce] + BracketingNonlinearSolve v1.12.1 [8d3b24bd] + CMAEvolutionStrategy v0.2.6 [2a0fbf3d] + CPUSummary v0.2.7 [336ed68f] + CSV v0.10.16 [49dc2e85] + Calculus v0.5.2 [d360d2e6] + ChainRulesCore v1.26.1 [fa4ea961] + ChemicalIdentifiers v0.1.10 [fb6a15b2] + CloseOpenIntervals v0.1.13 [aaaa29a8] + Clustering v0.15.8 [5ba52731] + CodecLz4 v0.4.6 [944b1d66] + CodecZlib v0.7.8 [6b39b394] + CodecZstd v0.8.7 [35d6a980] + ColorSchemes v3.31.0 [3da002f7] + ColorTypes v0.12.1 [c3611d14] + ColorVectorSpace v0.11.0 [5ae59095] + Colors v0.13.1 [861a8166] + Combinatorics v1.1.0 [38540f10] + CommonSolve v0.2.7 [bbf7d656] + CommonSubexpressions v0.3.1 [f70d9fcc] + CommonWorldInvalidations v1.0.0 [34da2185] + Compat v4.18.1 [a33af91c] + CompositionsBase v0.1.2 [2569d6c7] + ConcreteStructs v0.2.4 [f0e56b4a] + ConcurrentUtilities v2.5.1 [88cd18e8] + ConsoleProgressMonitor v0.1.2 [187b0558] + ConstructionBase v1.6.0 [d38c429a] + Contour v0.6.3 [adafc99b] + CpuId v0.3.1 [a8cc5b0e] + Crayons v4.1.1 [9a962f9c] + DataAPI v1.16.0 [a93c6f00] + DataFrames v1.8.2 [864edb3b] + DataStructures v0.19.5 [e2d170a0] + DataValueInterfaces v1.0.0 [8bb1440f] + DelimitedFiles v1.9.1 ⌅ [2b5f629d] + DiffEqBase v6.218.0 [163ba53b] + DiffResults v1.1.0 [b552c78f] + DiffRules v1.16.0 [a0c0ee7d] + DifferentiationInterface v0.7.18 [b4f34e82] + Distances v0.10.12 [31c24e10] + Distributions v0.25.127 [ffbed154] + DocStringExtensions v0.9.5 [4e289a0a] + EnumX v1.0.7 [f151be2c] + EnzymeCore v0.8.20 [460bff9d] + ExceptionUnwrapping v0.1.11 [d4d017d3] + ExponentialUtilities v1.30.0 [e2ba6199] + ExprTools v0.1.10 [55351af7] + ExproniconLite v0.10.14 [c87230d0] + FFMPEG v0.4.5 [b86e33f2] + FFTA v0.3.1 [7034ab61] + FastBroadcast v1.3.2 [9aa1b823] + FastClosures v0.3.2 [442a2c76] + FastGaussQuadrature v1.3.0 [a4df4552] + FastPower v1.3.1 [48062228] + FilePathsBase v0.9.24 [1a297f60] + FillArrays v1.16.0 [6a86dc24] + FiniteDiff v2.31.0 ⌅ [53c48c17] + FixedPointNumbers v0.8.6 [1fa38f19] + Format v1.3.7 [f6369f11] + ForwardDiff v1.4.1 [9eb8ae02] + ForwardDiffOverMeasurements v0.1.5 [069b7b12] + FunctionWrappers v1.1.3 [77dc65aa] + FunctionWrappersWrappers v1.9.1 [d9f16b24] + Functors v0.5.2 [46192b85] + GPUArraysCore v0.2.0 [28b8d3ca] + GR v0.73.26 [dd82b6e2] + GasChromatographySimulator v0.6.1 [c145ed77] + GenericSchur v0.5.6 [42e2da0e] + Grisu v1.0.2 [19dc6840] + HCubature v1.8.0 ⌅ [cd3eb016] + HTTP v1.11.0 [34004b35] + HypergeometricFunctions v0.3.28 [47d2ed2b] + Hyperscript v0.0.5 ⌅ [ac1192a8] + HypertextLiteral v0.9.5 [b5f81e59] + IOCapture v1.0.0 [615f187c] + IfElse v0.1.1 [842dd82b] + InlineStrings v1.4.5 [18e54dd8] + IntegerMathUtils v0.1.3 ⌅ [de52edbc] + Integrals v4.10.0 [a98d9a8b] + Interpolations v0.16.3 [3587e190] + InverseFunctions v0.1.17 [41ab1584] + InvertedIndices v1.3.1 [92d709cd] + IrrationalConstants v0.2.6 [82899510] + IteratorInterfaceExtensions v1.0.0 [1019f520] + JLFzf v0.1.11 [692b3bcd] + JLLWrappers v1.8.0 [682c06a0] + JSON v1.6.1 [ae98c720] + Jieko v0.2.1 [5ab0869b] + KernelDensity v0.6.12 [ba0b0d4f] + Krylov v0.10.6 [b964fa9f] + LaTeXStrings v1.4.0 [23fbe1c1] + Latexify v0.16.10 [73f95e8e] + LatticeRules v0.0.1 [10f19ff3] + LayoutPointers v0.1.17 ⌅ [1d6d02ad] + LeftChildRightSiblingTrees v0.2.1 [87fe0de2] + LineSearch v0.1.9 [d3d80556] + LineSearches v7.7.1 [7ed4a6bd] + LinearSolve v3.86.0 ⌃ [2ab3a3ac] + LogExpFunctions v0.3.29 [e6f89c97] + LoggingExtras v1.2.0 [6c6e2e6c] + MIMEs v1.1.0 [1914dd2f] + MacroTools v0.5.16 [d125e4d3] + ManualMemory v0.1.8 [bb5d69b7] + MaybeInplace v0.1.4 [739be429] + MbedTLS v1.1.10 [eff96d63] + Measurements v2.14.1 [442fdcdd] + Measures v0.3.3 [e1d29d7a] + Missings v1.2.0 [78c3b35d] + Mocking v0.8.1 [4886b29c] + MonteCarloIntegration v0.2.0 [2e0e35c7] + Moshi v0.3.8 [46d2c3a1] + MuladdMacro v0.2.4 [6f286f6a] + MultivariateStats v0.10.4 [d41bc354] + NLSolversBase v8.0.0 [77ba4419] + NaNMath v1.1.4 [b8a86587] + NearestNeighbors v0.4.27 [8913a72c] + NonlinearSolve v4.19.1 ⌃ [be0214bd] + NonlinearSolveBase v2.30.3 [5959db7a] + NonlinearSolveFirstOrder v2.1.1 [9a2c21bd] + NonlinearSolveQuasiNewton v1.13.1 [26075421] + NonlinearSolveSpectralMethods v1.7.1 [510215fc] + Observables v0.5.5 [6fe1bfb0] + OffsetArrays v1.17.0 [4d8831e6] + OpenSSL v1.6.1 [429524aa] + Optim v2.2.1 [3bd65402] + Optimisers v0.4.7 [7f7a1694] + Optimization v5.6.1 [3e6eede4] + OptimizationBBO v0.4.7 [bca83a33] + OptimizationBase v5.1.3 [bd407f91] + OptimizationCMAEvolutionStrategy v0.3.8 [36348300] + OptimizationOptimJL v0.4.14 [42dfb2eb] + OptimizationOptimisers v0.3.17 ⌅ [bac558e1] + OrderedCollections v1.8.2 ⌅ [1dea7af3] + OrdinaryDiffEq v6.111.0 ⌅ [89bda076] + OrdinaryDiffEqAdamsBashforthMoulton v1.11.0 ⌅ [6ad6398a] + OrdinaryDiffEqBDF v1.26.0 ⌅ [bbf590c4] + OrdinaryDiffEqCore v3.33.1 ⌅ [50262376] + OrdinaryDiffEqDefault v1.14.0 ⌅ [4302a76b] + OrdinaryDiffEqDifferentiation v2.9.0 ⌅ [9286f039] + OrdinaryDiffEqExplicitRK v1.12.0 ⌅ [e0540318] + OrdinaryDiffEqExponentialRK v1.15.0 ⌅ [becaefa8] + OrdinaryDiffEqExtrapolation v1.18.0 ⌅ [5960d6e9] + OrdinaryDiffEqFIRK v1.26.0 ⌅ [101fe9f7] + OrdinaryDiffEqFeagin v1.10.0 ⌅ [d3585ca7] + OrdinaryDiffEqFunctionMap v1.11.0 ⌅ [d28bc4f8] + OrdinaryDiffEqHighOrderRK v1.12.0 ⌅ [9f002381] + OrdinaryDiffEqIMEXMultistep v1.14.0 ⌅ [521117fe] + OrdinaryDiffEqLinear v1.12.0 ⌅ [1344f307] + OrdinaryDiffEqLowOrderRK v1.13.0 ⌅ [b0944070] + OrdinaryDiffEqLowStorageRK v1.15.0 ⌅ [127b3ac7] + OrdinaryDiffEqNonlinearSolve v1.28.0 ⌅ [c9986a66] + OrdinaryDiffEqNordsieck v1.11.0 ⌅ [5dd0a6cf] + OrdinaryDiffEqPDIRK v1.14.0 ⌅ [5b33eab2] + OrdinaryDiffEqPRK v1.10.0 ⌅ [04162be5] + OrdinaryDiffEqQPRK v1.10.0 ⌅ [af6ede74] + OrdinaryDiffEqRKN v1.12.0 ⌅ [43230ef6] + OrdinaryDiffEqRosenbrock v1.31.1 ⌅ [2d112036] + OrdinaryDiffEqSDIRK v1.14.0 ⌅ [669c94d9] + OrdinaryDiffEqSSPRK v1.14.0 ⌅ [e3e12d00] + OrdinaryDiffEqStabilizedIRK v1.14.0 ⌅ [358294b1] + OrdinaryDiffEqStabilizedRK v1.11.1 ⌅ [fa646aed] + OrdinaryDiffEqSymplecticRK v1.13.0 ⌅ [b1df2697] + OrdinaryDiffEqTsit5 v1.12.0 ⌅ [79d7bb75] + OrdinaryDiffEqVerner v1.14.0 [90014a1f] + PDMats v0.11.37 [69de0a69] + Parsers v2.8.6 [ccf2f8ad] + PlotThemes v3.3.0 [995b91a9] + PlotUtils v1.4.4 [91a5bcdd] + Plots v1.41.6 [7f904dfe] + PlutoUI v0.7.83 [f517fe37] + Polyester v0.7.19 [1d0040c9] + 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UUIDs v1.11.0 [4ec0a83e] + Unicode v1.11.0 [e66e0078] + CompilerSupportLibraries_jll v1.3.0+1 [deac9b47] + LibCURL_jll v8.15.0+0 [e37daf67] + LibGit2_jll v1.9.0+0 [29816b5a] + LibSSH2_jll v1.11.3+1 [14a3606d] + MozillaCACerts_jll v2025.11.4 [4536629a] + OpenBLAS_jll v0.3.29+0 [05823500] + OpenLibm_jll v0.8.7+0 [458c3c95] + OpenSSL_jll v3.5.6+0 [efcefdf7] + PCRE2_jll v10.44.0+1 [bea87d4a] + SuiteSparse_jll v7.8.3+2 [83775a58] + Zlib_jll v1.3.1+2 [8e850b90] + libblastrampoline_jll v5.15.0+0 [8e850ede] + nghttp2_jll v1.64.0+1 [3f19e933] + p7zip_jll v17.7.0+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. To see why use `status --outdated -m` Installation completed after 7.27s ################################################################################ # Precompilation # Precompiling PkgEval dependencies... Precompiling package dependencies... Precompiling packages... 9370.4 ms ✓ ForwardDiffOverMeasurements 11124.1 ms ✓ OptimizationCMAEvolutionStrategy 20137.3 ms ✓ OptimizationOptimisers 606862.0 ms ✓ OptimizationBBO 18762.0 ms ✓ Integrals → IntegralsForwardDiffExt 16020.3 ms ✓ Integrals → IntegralsFastGaussQuadratureExt 444731.3 ms ✓ GasChromatographySimulator 359374.7 ms ? RetentionParameterEstimator 7 dependencies successfully precompiled in 1541 seconds. 521 already precompiled. 24 dependencies precompiled but different versions are currently loaded (ArgTools, Base64, Dates, Downloads, JuliaSyntaxHighlighting, LibCURL, LibCURL_jll, LibGit2, LibGit2_jll, LibSSH2_jll, Logging, Markdown, MozillaCACerts_jll, NetworkOptions, OpenSSL_jll, Pkg, Printf, StyledStrings, TOML, Tar, UUIDs, Zlib_jll, nghttp2_jll and p7zip_jll). Restart julia to access the new versions. Otherwise, 363 dependents of these packages may trigger further precompilation to work with the unexpected versions. 1 dependencies failed but may be precompilable after restarting julia 2 dependencies had output during precompilation: ┌ GasChromatographySimulator │ [ Info: :short database file not found, downloading from https://raw.githubusercontent.com/CalebBell/chemicals/refs/heads/master/chemicals/Identifiers/chemical%20identifiers%20pubchem%20small.tsv │ [ Info: :short database file downloaded. │ [ Info: :short arrow file not generated, processing... │ [ Info: :inorganic database file not found, downloading from https://raw.githubusercontent.com/CalebBell/chemicals/refs/heads/master/chemicals/Identifiers/Inorganic%20db.tsv │ [ Info: :inorganic database file downloaded. │ [ Info: :inorganic arrow file not generated, processing... │ [ Info: :long database file not found, downloading from https://raw.githubusercontent.com/CalebBell/chemicals/refs/heads/master/chemicals/Identifiers/chemical%20identifiers%20pubchem%20large.tsv │ [ Info: :long database file downloaded. │ [ Info: :long arrow file not generated, processing... └ ┌ RetentionParameterEstimator │ WARNING: Method definition unwrap_type(Type{var"#s1"} where var"#s1"<:(OffsetArrays.OffsetArray{T, N, AA} where AA<:AbstractArray{T, N} where N where T)) in module OffsetArraysAdaptExt at /home/pkgeval/.julia/packages/OffsetArrays/b7qpm/ext/OffsetArraysAdaptExt.jl:14 overwritten in module OffsetArraysAdaptExt on the same line (check for duplicate calls to `include`). │ ERROR: Method overwriting is not permitted during Module precompilation. Use `__precompile__(false)` to opt-out of precompilation. └ Precompilation completed after 1543.66s ################################################################################ # Testing # Testing RetentionParameterEstimator Status `/tmp/jl_rf43rp/Project.toml` [dd82b6e2] GasChromatographySimulator v0.6.1 [0afdae40] RetentionParameterEstimator v0.2.1 [8dfed614] Test v1.11.0 Status `/tmp/jl_rf43rp/Manifest.toml` [47edcb42] ADTypes v1.22.0 [14f7f29c] AMD v0.5.3 [621f4979] AbstractFFTs v1.5.0 [6e696c72] AbstractPlutoDingetjes v1.4.0 [1520ce14] AbstractTrees v0.4.5 [7d9f7c33] Accessors v0.1.44 [79e6a3ab] Adapt v4.6.1 [66dad0bd] AliasTables v1.1.3 [7d9fca2a] Arpack v0.5.4 [4fba245c] ArrayInterface v7.25.0 [69666777] Arrow v2.8.1 [31f734f8] ArrowTypes v2.3.0 [13072b0f] AxisAlgorithms v1.1.0 [6e4b80f9] BenchmarkTools v1.8.0 [d1d4a3ce] BitFlags v0.1.10 [c3b6d118] BitIntegers v0.3.7 [62783981] BitTwiddlingConvenienceFunctions v0.1.6 [a134a8b2] BlackBoxOptim v0.6.5 [70df07ce] 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p7zip_jll v17.7.0+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... Precompiling packages... 134023.5 ms ✓ RetentionParameterEstimator 1 dependency successfully precompiled in 158 seconds. 528 already precompiled. 8 dependencies precompiled but different versions are currently loaded (Base64, InteractiveUtils, JuliaSyntaxHighlighting, Logging, Markdown, Serialization, StyledStrings and Test). Restart julia to access the new versions. Otherwise, 196 dependents of these packages may trigger further precompilation to work with the unexpected versions. [ Info: :custom database file not found, downloading from https://raw.githubusercontent.com/JanLeppert/RetentionData/main/data/add_CI_db.tsv [ Info: :custom database file downloaded. [ Info: :custom arrow file not generated, processing... Test Summary: | Pass Total Time Simulation Test | 2 2 3m04.4s Test Summary: | Pass Total Time Loading Data | 9 9 26.5s ┌ Warning: Using arrays or dicts to store parameters of different types can hurt performance. │ Consider using tuples instead. └ @ SciMLBase ~/.julia/packages/SciMLBase/hLfdZ/src/performance_warnings.jl:32 ┌ Warning: Verbosity toggle: missing_second_order_ad │ The selected optimization algorithm requires second order derivatives, but `SecondOrder` ADtype was not provided. So a `SecondOrder` with ADTypes.AutoForwardDiff() for both inner and outer will be created, this can be suboptimal and not work in some cases so an explicit `SecondOrder` ADtype is recommended. └ @ OptimizationBase ~/.julia/packages/OptimizationBase/EAGYd/src/cache.jl:73 Test Summary: | Pass Total Time Loss Functions | 31 31 1m43.7s ┌ Warning: Verbosity toggle: missing_second_order_ad │ The selected optimization algorithm requires second order derivatives, but `SecondOrder` ADtype was not provided. So a `SecondOrder` with ADTypes.AutoForwardDiff() for both inner and outer will be created, this can be suboptimal and not work in some cases so an explicit `SecondOrder` ADtype is recommended. └ @ OptimizationBase ~/.julia/packages/OptimizationBase/EAGYd/src/cache.jl:73 ┌ Warning: Verbosity toggle: missing_second_order_ad │ The selected optimization algorithm requires second order derivatives, but `SecondOrder` ADtype was not provided. So a `SecondOrder` with ADTypes.AutoForwardDiff() for both inner and outer will be created, this can be suboptimal and not work in some cases so an explicit `SecondOrder` ADtype is recommended. └ @ OptimizationBase ~/.julia/packages/OptimizationBase/EAGYd/src/cache.jl:73 Test Summary: | Pass Total Time Optimize d_only | 5 5 42.7s ┌ Warning: Verbosity toggle: missing_second_order_ad │ The selected optimization algorithm requires second order derivatives, but `SecondOrder` ADtype was not provided. So a `SecondOrder` with ADTypes.AutoForwardDiff() for both inner and outer will be created, this can be suboptimal and not work in some cases so an explicit `SecondOrder` ADtype is recommended. └ @ OptimizationBase ~/.julia/packages/OptimizationBase/EAGYd/src/cache.jl:73 ┌ Warning: Verbosity toggle: missing_second_order_ad │ The selected optimization algorithm requires second order derivatives, but `SecondOrder` ADtype was not provided. So a `SecondOrder` with ADTypes.AutoForwardDiff() for both inner and outer will be created, this can be suboptimal and not work in some cases so an explicit `SecondOrder` ADtype is recommended. └ @ OptimizationBase ~/.julia/packages/OptimizationBase/EAGYd/src/cache.jl:73 ┌ Warning: Verbosity toggle: missing_second_order_ad │ The selected optimization algorithm requires second order derivatives, but `SecondOrder` ADtype was not provided. So a `SecondOrder` with ADTypes.AutoForwardDiff() for both inner and outer will be created, this can be suboptimal and not work in some cases so an explicit `SecondOrder` ADtype is recommended. └ @ OptimizationBase ~/.julia/packages/OptimizationBase/EAGYd/src/cache.jl:73 ┌ Warning: Verbosity toggle: missing_second_order_ad │ The selected optimization algorithm requires second order derivatives, but `SecondOrder` ADtype was not provided. So a `SecondOrder` with ADTypes.AutoForwardDiff() for both inner and outer will be created, this can be suboptimal and not work in some cases so an explicit `SecondOrder` ADtype is recommended. └ @ OptimizationBase ~/.julia/packages/OptimizationBase/EAGYd/src/cache.jl:73 ┌ Warning: Verbosity toggle: missing_second_order_ad │ The selected optimization algorithm requires second order derivatives, but `SecondOrder` ADtype was not provided. So a `SecondOrder` with ADTypes.AutoForwardDiff() for both inner and outer will be created, this can be suboptimal and not work in some cases so an explicit `SecondOrder` ADtype is recommended. └ @ OptimizationBase ~/.julia/packages/OptimizationBase/EAGYd/src/cache.jl:73 ┌ Warning: Verbosity toggle: missing_second_order_ad │ The selected optimization algorithm requires second order derivatives, but `SecondOrder` ADtype was not provided. So a `SecondOrder` with ADTypes.AutoForwardDiff() for both inner and outer will be created, this can be suboptimal and not work in some cases so an explicit `SecondOrder` ADtype is recommended. └ @ OptimizationBase ~/.julia/packages/OptimizationBase/EAGYd/src/cache.jl:73 ┌ Warning: Verbosity toggle: missing_second_order_ad │ The selected optimization algorithm requires second order derivatives, but `SecondOrder` ADtype was not provided. So a `SecondOrder` with ADTypes.AutoForwardDiff() for both inner and outer will be created, this can be suboptimal and not work in some cases so an explicit `SecondOrder` ADtype is recommended. └ @ OptimizationBase ~/.julia/packages/OptimizationBase/EAGYd/src/cache.jl:73 ┌ Warning: Verbosity toggle: missing_second_order_ad │ The selected optimization algorithm requires second order derivatives, but `SecondOrder` ADtype was not provided. So a `SecondOrder` with ADTypes.AutoForwardDiff() for both inner and outer will be created, this can be suboptimal and not work in some cases so an explicit `SecondOrder` ADtype is recommended. └ @ OptimizationBase ~/.julia/packages/OptimizationBase/EAGYd/src/cache.jl:73 ┌ Warning: Verbosity toggle: missing_second_order_ad │ The selected optimization algorithm requires second order derivatives, but `SecondOrder` ADtype was not provided. So a `SecondOrder` with ADTypes.AutoForwardDiff() for both inner and outer will be created, this can be suboptimal and not work in some cases so an explicit `SecondOrder` ADtype is recommended. └ @ OptimizationBase ~/.julia/packages/OptimizationBase/EAGYd/src/cache.jl:73 ┌ Warning: Verbosity toggle: missing_second_order_ad │ The selected optimization algorithm requires second order derivatives, but `SecondOrder` ADtype was not provided. So a `SecondOrder` with ADTypes.AutoForwardDiff() for both inner and outer will be created, this can be suboptimal and not work in some cases so an explicit `SecondOrder` ADtype is recommended. └ @ OptimizationBase ~/.julia/packages/OptimizationBase/EAGYd/src/cache.jl:73 ┌ Warning: Verbosity toggle: missing_second_order_ad │ The selected optimization algorithm requires second order derivatives, but `SecondOrder` ADtype was not provided. So a `SecondOrder` with ADTypes.AutoForwardDiff() for both inner and outer will be created, this can be suboptimal and not work in some cases so an explicit `SecondOrder` ADtype is recommended. └ @ OptimizationBase ~/.julia/packages/OptimizationBase/EAGYd/src/cache.jl:73 ┌ Warning: Verbosity toggle: missing_second_order_ad │ The selected optimization algorithm requires second order derivatives, but `SecondOrder` ADtype was not provided. So a `SecondOrder` with ADTypes.AutoForwardDiff() for both inner and outer will be created, this can be suboptimal and not work in some cases so an explicit `SecondOrder` ADtype is recommended. └ @ OptimizationBase ~/.julia/packages/OptimizationBase/EAGYd/src/cache.jl:73 ┌ Warning: Verbosity toggle: missing_second_order_ad │ The selected optimization algorithm requires second order derivatives, but `SecondOrder` ADtype was not provided. So a `SecondOrder` with ADTypes.AutoForwardDiff() for both inner and outer will be created, this can be suboptimal and not work in some cases so an explicit `SecondOrder` ADtype is recommended. └ @ OptimizationBase ~/.julia/packages/OptimizationBase/EAGYd/src/cache.jl:73 ┌ Warning: Verbosity toggle: missing_second_order_ad │ The selected optimization algorithm requires second order derivatives, but `SecondOrder` ADtype was not provided. So a `SecondOrder` with ADTypes.AutoForwardDiff() for both inner and outer will be created, this can be suboptimal and not work in some cases so an explicit `SecondOrder` ADtype is recommended. └ @ OptimizationBase ~/.julia/packages/OptimizationBase/EAGYd/src/cache.jl:73 ┌ Warning: Verbosity toggle: missing_second_order_ad │ The selected optimization algorithm requires second order derivatives, but `SecondOrder` ADtype was not provided. So a `SecondOrder` with ADTypes.AutoForwardDiff() for both inner and outer will be created, this can be suboptimal and not work in some cases so an explicit `SecondOrder` ADtype is recommended. └ @ OptimizationBase ~/.julia/packages/OptimizationBase/EAGYd/src/cache.jl:73 ┌ Warning: Verbosity toggle: missing_second_order_ad │ The selected optimization algorithm requires second order derivatives, but `SecondOrder` ADtype was not provided. So a `SecondOrder` with ADTypes.AutoForwardDiff() for both inner and outer will be created, this can be suboptimal and not work in some cases so an explicit `SecondOrder` ADtype is recommended. └ @ OptimizationBase ~/.julia/packages/OptimizationBase/EAGYd/src/cache.jl:73 ┌ Warning: Verbosity toggle: missing_second_order_ad │ The selected optimization algorithm requires second order derivatives, but `SecondOrder` ADtype was not provided. So a `SecondOrder` with ADTypes.AutoForwardDiff() for both inner and outer will be created, this can be suboptimal and not work in some cases so an explicit `SecondOrder` ADtype is recommended. └ @ OptimizationBase ~/.julia/packages/OptimizationBase/EAGYd/src/cache.jl:73 ┌ Warning: Verbosity toggle: missing_second_order_ad │ The selected optimization algorithm requires second order derivatives, but `SecondOrder` ADtype was not provided. So a `SecondOrder` with ADTypes.AutoForwardDiff() for both inner and outer will be created, this can be suboptimal and not work in some cases so an explicit `SecondOrder` ADtype is recommended. └ @ OptimizationBase ~/.julia/packages/OptimizationBase/EAGYd/src/cache.jl:73 Test Summary: | Pass Total Time Optimization | 14 14 3m18.4s ┌ Warning: Verbosity toggle: missing_second_order_ad │ The selected optimization algorithm requires second order derivatives, but `SecondOrder` ADtype was not provided. So a `SecondOrder` with ADTypes.AutoForwardDiff() for both inner and outer will be created, this can be suboptimal and not work in some cases so an explicit `SecondOrder` ADtype is recommended. └ @ OptimizationBase ~/.julia/packages/OptimizationBase/EAGYd/src/cache.jl:73 ┌ Warning: Verbosity toggle: missing_second_order_ad │ The selected optimization algorithm requires second order derivatives, but `SecondOrder` ADtype was not provided. So a `SecondOrder` with ADTypes.AutoForwardDiff() for both inner and outer will be created, this can be suboptimal and not work in some cases so an explicit `SecondOrder` ADtype is recommended. └ @ OptimizationBase ~/.julia/packages/OptimizationBase/EAGYd/src/cache.jl:73 ┌ Warning: Verbosity toggle: missing_second_order_ad │ The selected optimization algorithm requires second order derivatives, but `SecondOrder` ADtype was not provided. So a `SecondOrder` with ADTypes.AutoForwardDiff() for both inner and outer will be created, this can be suboptimal and not work in some cases so an explicit `SecondOrder` ADtype is recommended. └ @ OptimizationBase ~/.julia/packages/OptimizationBase/EAGYd/src/cache.jl:73 ┌ Warning: Verbosity toggle: missing_second_order_ad │ The selected optimization algorithm requires second order derivatives, but `SecondOrder` ADtype was not provided. So a `SecondOrder` with ADTypes.AutoForwardDiff() for both inner and outer will be created, this can be suboptimal and not work in some cases so an explicit `SecondOrder` ADtype is recommended. └ @ OptimizationBase ~/.julia/packages/OptimizationBase/EAGYd/src/cache.jl:73 ┌ Warning: Verbosity toggle: missing_second_order_ad │ The selected optimization algorithm requires second order derivatives, but `SecondOrder` ADtype was not provided. So a `SecondOrder` with ADTypes.AutoForwardDiff() for both inner and outer will be created, this can be suboptimal and not work in some cases so an explicit `SecondOrder` ADtype is recommended. └ @ OptimizationBase ~/.julia/packages/OptimizationBase/EAGYd/src/cache.jl:73 ┌ Warning: Verbosity toggle: missing_second_order_ad │ The selected optimization algorithm requires second order derivatives, but `SecondOrder` ADtype was not provided. So a `SecondOrder` with ADTypes.AutoForwardDiff() for both inner and outer will be created, this can be suboptimal and not work in some cases so an explicit `SecondOrder` ADtype is recommended. └ @ OptimizationBase ~/.julia/packages/OptimizationBase/EAGYd/src/cache.jl:73 ┌ Warning: Verbosity toggle: missing_second_order_ad │ The selected optimization algorithm requires second order derivatives, but `SecondOrder` ADtype was not provided. So a `SecondOrder` with ADTypes.AutoForwardDiff() for both inner and outer will be created, this can be suboptimal and not work in some cases so an explicit `SecondOrder` ADtype is recommended. └ @ OptimizationBase ~/.julia/packages/OptimizationBase/EAGYd/src/cache.jl:73 ┌ Warning: Verbosity toggle: missing_second_order_ad │ The selected optimization algorithm requires second order derivatives, but `SecondOrder` ADtype was not provided. So a `SecondOrder` with ADTypes.AutoForwardDiff() for both inner and outer will be created, this can be suboptimal and not work in some cases so an explicit `SecondOrder` ADtype is recommended. └ @ OptimizationBase ~/.julia/packages/OptimizationBase/EAGYd/src/cache.jl:73 ┌ Warning: Verbosity toggle: missing_second_order_ad │ The selected optimization algorithm requires second order derivatives, but `SecondOrder` ADtype was not provided. So a `SecondOrder` with ADTypes.AutoForwardDiff() for both inner and outer will be created, this can be suboptimal and not work in some cases so an explicit `SecondOrder` ADtype is recommended. └ @ OptimizationBase ~/.julia/packages/OptimizationBase/EAGYd/src/cache.jl:73 ┌ Warning: Verbosity toggle: missing_second_order_ad │ The selected optimization algorithm requires second order derivatives, but `SecondOrder` ADtype was not provided. So a `SecondOrder` with ADTypes.AutoForwardDiff() for both inner and outer will be created, this can be suboptimal and not work in some cases so an explicit `SecondOrder` ADtype is recommended. └ @ OptimizationBase ~/.julia/packages/OptimizationBase/EAGYd/src/cache.jl:73 ┌ Warning: Verbosity toggle: missing_second_order_ad │ The selected optimization algorithm requires second order derivatives, but `SecondOrder` ADtype was not provided. So a `SecondOrder` with ADTypes.AutoForwardDiff() for both inner and outer will be created, this can be suboptimal and not work in some cases so an explicit `SecondOrder` ADtype is recommended. └ @ OptimizationBase ~/.julia/packages/OptimizationBase/EAGYd/src/cache.jl:73 ┌ Warning: Verbosity toggle: missing_second_order_ad │ The selected optimization algorithm requires second order derivatives, but `SecondOrder` ADtype was not provided. So a `SecondOrder` with ADTypes.AutoForwardDiff() for both inner and outer will be created, this can be suboptimal and not work in some cases so an explicit `SecondOrder` ADtype is recommended. └ @ OptimizationBase ~/.julia/packages/OptimizationBase/EAGYd/src/cache.jl:73 ┌ Warning: Verbosity toggle: missing_second_order_ad │ The selected optimization algorithm requires second order derivatives, but `SecondOrder` ADtype was not provided. So a `SecondOrder` with ADTypes.AutoForwardDiff() for both inner and outer will be created, this can be suboptimal and not work in some cases so an explicit `SecondOrder` ADtype is recommended. └ @ OptimizationBase ~/.julia/packages/OptimizationBase/EAGYd/src/cache.jl:73 ┌ Warning: Verbosity toggle: missing_second_order_ad │ The selected optimization algorithm requires second order derivatives, but `SecondOrder` ADtype was not provided. So a `SecondOrder` with ADTypes.AutoForwardDiff() for both inner and outer will be created, this can be suboptimal and not work in some cases so an explicit `SecondOrder` ADtype is recommended. └ @ OptimizationBase ~/.julia/packages/OptimizationBase/EAGYd/src/cache.jl:73 ┌ Warning: Verbosity toggle: missing_second_order_ad │ The selected optimization algorithm requires second order derivatives, but `SecondOrder` ADtype was not provided. So a `SecondOrder` with ADTypes.AutoForwardDiff() for both inner and outer will be created, this can be suboptimal and not work in some cases so an explicit `SecondOrder` ADtype is recommended. └ @ OptimizationBase ~/.julia/packages/OptimizationBase/EAGYd/src/cache.jl:73 Test Summary: | Pass Total Time Standard Errors | 10 10 1m37.1s ┌ Warning: Verbosity toggle: missing_second_order_ad │ The selected optimization algorithm requires second order derivatives, but `SecondOrder` ADtype was not provided. So a `SecondOrder` with ADTypes.AutoForwardDiff() for both inner and outer will be created, this can be suboptimal and not work in some cases so an explicit `SecondOrder` ADtype is recommended. └ @ OptimizationBase ~/.julia/packages/OptimizationBase/EAGYd/src/cache.jl:73 ┌ Warning: Verbosity toggle: missing_second_order_ad │ The selected optimization algorithm requires second order derivatives, but `SecondOrder` ADtype was not provided. So a `SecondOrder` with ADTypes.AutoForwardDiff() for both inner and outer will be created, this can be suboptimal and not work in some cases so an explicit `SecondOrder` ADtype is recommended. └ @ OptimizationBase ~/.julia/packages/OptimizationBase/EAGYd/src/cache.jl:73 ┌ Warning: Verbosity toggle: missing_second_order_ad │ The selected optimization algorithm requires second order derivatives, but `SecondOrder` ADtype was not provided. So a `SecondOrder` with ADTypes.AutoForwardDiff() for both inner and outer will be created, this can be suboptimal and not work in some cases so an explicit `SecondOrder` ADtype is recommended. └ @ OptimizationBase ~/.julia/packages/OptimizationBase/EAGYd/src/cache.jl:73 ┌ Warning: Verbosity toggle: missing_second_order_ad │ The selected optimization algorithm requires second order derivatives, but `SecondOrder` ADtype was not provided. So a `SecondOrder` with ADTypes.AutoForwardDiff() for both inner and outer will be created, this can be suboptimal and not work in some cases so an explicit `SecondOrder` ADtype is recommended. └ @ OptimizationBase ~/.julia/packages/OptimizationBase/EAGYd/src/cache.jl:73 ┌ Warning: Verbosity toggle: missing_second_order_ad │ The selected optimization algorithm requires second order derivatives, but `SecondOrder` ADtype was not provided. So a `SecondOrder` with ADTypes.AutoForwardDiff() for both inner and outer will be created, this can be suboptimal and not work in some cases so an explicit `SecondOrder` ADtype is recommended. └ @ OptimizationBase ~/.julia/packages/OptimizationBase/EAGYd/src/cache.jl:73 ┌ Warning: Verbosity toggle: missing_second_order_ad │ The selected optimization algorithm requires second order derivatives, but `SecondOrder` ADtype was not provided. So a `SecondOrder` with ADTypes.AutoForwardDiff() for both inner and outer will be created, this can be suboptimal and not work in some cases so an explicit `SecondOrder` ADtype is recommended. └ @ OptimizationBase ~/.julia/packages/OptimizationBase/EAGYd/src/cache.jl:73 ┌ Warning: Verbosity toggle: missing_second_order_ad │ The selected optimization algorithm requires second order derivatives, but `SecondOrder` ADtype was not provided. So a `SecondOrder` with ADTypes.AutoForwardDiff() for both inner and outer will be created, this can be suboptimal and not work in some cases so an explicit `SecondOrder` ADtype is recommended. └ @ OptimizationBase ~/.julia/packages/OptimizationBase/EAGYd/src/cache.jl:73 ┌ Warning: Verbosity toggle: missing_second_order_ad │ The selected optimization algorithm requires second order derivatives, but `SecondOrder` ADtype was not provided. So a `SecondOrder` with ADTypes.AutoForwardDiff() for both inner and outer will be created, this can be suboptimal and not work in some cases so an explicit `SecondOrder` ADtype is recommended. └ @ OptimizationBase ~/.julia/packages/OptimizationBase/EAGYd/src/cache.jl:73 ┌ Warning: Verbosity toggle: missing_second_order_ad │ The selected optimization algorithm requires second order derivatives, but `SecondOrder` ADtype was not provided. So a `SecondOrder` with ADTypes.AutoForwardDiff() for both inner and outer will be created, this can be suboptimal and not work in some cases so an explicit `SecondOrder` ADtype is recommended. └ @ OptimizationBase ~/.julia/packages/OptimizationBase/EAGYd/src/cache.jl:73 ┌ Warning: Verbosity toggle: missing_second_order_ad │ The selected optimization algorithm requires second order derivatives, but `SecondOrder` ADtype was not provided. So a `SecondOrder` with ADTypes.AutoForwardDiff() for both inner and outer will be created, this can be suboptimal and not work in some cases so an explicit `SecondOrder` ADtype is recommended. └ @ OptimizationBase ~/.julia/packages/OptimizationBase/EAGYd/src/cache.jl:73 ┌ Warning: Verbosity toggle: missing_second_order_ad │ The selected optimization algorithm requires second order derivatives, but `SecondOrder` ADtype was not provided. So a `SecondOrder` with ADTypes.AutoForwardDiff() for both inner and outer will be created, this can be suboptimal and not work in some cases so an explicit `SecondOrder` ADtype is recommended. └ @ OptimizationBase ~/.julia/packages/OptimizationBase/EAGYd/src/cache.jl:73 ┌ Warning: Verbosity toggle: missing_second_order_ad │ The selected optimization algorithm requires second order derivatives, but `SecondOrder` ADtype was not provided. So a `SecondOrder` with ADTypes.AutoForwardDiff() for both inner and outer will be created, this can be suboptimal and not work in some cases so an explicit `SecondOrder` ADtype is recommended. └ @ OptimizationBase ~/.julia/packages/OptimizationBase/EAGYd/src/cache.jl:73 ┌ Warning: Verbosity toggle: missing_second_order_ad │ The selected optimization algorithm requires second order derivatives, but `SecondOrder` ADtype was not provided. So a `SecondOrder` with ADTypes.AutoForwardDiff() for both inner and outer will be created, this can be suboptimal and not work in some cases so an explicit `SecondOrder` ADtype is recommended. └ @ OptimizationBase ~/.julia/packages/OptimizationBase/EAGYd/src/cache.jl:73 ┌ Warning: Verbosity toggle: missing_second_order_ad │ The selected optimization algorithm requires second order derivatives, but `SecondOrder` ADtype was not provided. So a `SecondOrder` with ADTypes.AutoForwardDiff() for both inner and outer will be created, this can be suboptimal and not work in some cases so an explicit `SecondOrder` ADtype is recommended. └ @ OptimizationBase ~/.julia/packages/OptimizationBase/EAGYd/src/cache.jl:73 ┌ Warning: Verbosity toggle: missing_second_order_ad │ The selected optimization algorithm requires second order derivatives, but `SecondOrder` ADtype was not provided. So a `SecondOrder` with ADTypes.AutoForwardDiff() for both inner and outer will be created, this can be suboptimal and not work in some cases so an explicit `SecondOrder` ADtype is recommended. └ @ OptimizationBase ~/.julia/packages/OptimizationBase/EAGYd/src/cache.jl:73 ┌ Warning: Verbosity toggle: missing_second_order_ad │ The selected optimization algorithm requires second order derivatives, but `SecondOrder` ADtype was not provided. So a `SecondOrder` with ADTypes.AutoForwardDiff() for both inner and outer will be created, this can be suboptimal and not work in some cases so an explicit `SecondOrder` ADtype is recommended. └ @ OptimizationBase ~/.julia/packages/OptimizationBase/EAGYd/src/cache.jl:73 ┌ Warning: Verbosity toggle: missing_second_order_ad │ The selected optimization algorithm requires second order derivatives, but `SecondOrder` ADtype was not provided. So a `SecondOrder` with ADTypes.AutoForwardDiff() for both inner and outer will be created, this can be suboptimal and not work in some cases so an explicit `SecondOrder` ADtype is recommended. └ @ OptimizationBase ~/.julia/packages/OptimizationBase/EAGYd/src/cache.jl:73 ┌ Warning: Verbosity toggle: missing_second_order_ad │ The selected optimization algorithm requires second order derivatives, but `SecondOrder` ADtype was not provided. So a `SecondOrder` with ADTypes.AutoForwardDiff() for both inner and outer will be created, this can be suboptimal and not work in some cases so an explicit `SecondOrder` ADtype is recommended. └ @ OptimizationBase ~/.julia/packages/OptimizationBase/EAGYd/src/cache.jl:73 Test Summary: | Pass Total Time Optimization with Missing Values | 9 9 2m02.5s Testing RetentionParameterEstimator tests passed Testing completed after 1077.11s PkgEval succeeded after 2671.33s