Package evaluation to test DataTreatments on Julia 1.14.0-DEV.3055 (7e75a8061a*) started at 2026-08-28T04:36:24.765 ################################################################################ # Set-up # Installing PkgEval dependencies (TestEnv)... Activating project at `~/.julia/environments/v1.14` Set-up completed after 15.51s ################################################################################ # Installation # Installing DataTreatments... Resolving package versions... Installed CommonSolve ───────────────── v0.2.14 Installed DataDeps ──────────────────── v1.0.0 Installed Rmath_jll ─────────────────── v0.5.2+0 Installed MacroTools ────────────────── v0.5.16 Installed CompositionsBase ──────────── v0.1.2 Installed Normalization ─────────────── v0.9.3 Installed LearnAPI ──────────────────── v2.0.1 Installed FilePathsBase ─────────────── v0.9.24 Installed FillArrays ────────────────── v1.17.0 Installed DataStructures ────────────── v0.19.6 Installed Adapt ─────────────────────── v4.7.0 Installed HypergeometricFunctions ───── v0.3.30 Installed Calculus ──────────────────── v0.5.2 Installed DelimitedFiles ────────────── v1.9.1 Installed AbstractTrees ─────────────── v0.4.5 Installed ConstructionBase ──────────── v1.6.0 Installed InlineStrings ─────────────── v1.4.5 Installed CodecZlib ─────────────────── v0.7.9 Installed CSV ───────────────────────── v0.10.17 Installed StatsBase ─────────────────── v0.34.13 Installed AliasTables ───────────────── v1.1.3 Installed TableDistances ────────────── v1.2.0 Installed ScientificTypes ───────────── v3.3.0 Installed NearestNeighbors ──────────── v0.4.22 Installed OrderedCollections ────────── v2.0.1 Installed HashArrayMappedTries ──────── v0.2.0 Installed TranscodingStreams ────────── v0.11.3 Installed Compat ────────────────────── v4.18.1 Installed RecipesBase ───────────────── v1.3.4 Installed IteratorInterfaceExtensions ─ v1.0.0 Installed DataAPI ───────────────────── v1.16.0 Installed NelderMead ────────────────── v0.4.0 Installed Statistics ────────────────── v1.11.1 Installed NNlib ─────────────────────── v0.9.44 Installed InvertedIndices ───────────── v1.3.1 Installed StatsAPI ──────────────────── v1.8.0 Installed Atomix ────────────────────── v1.1.3 Installed Impute ────────────────────── v0.6.14 Installed PrecompileTools ───────────── v1.3.4 Installed DataValueInterfaces ───────── v1.0.0 Installed MLCore ────────────────────── v1.1.0 Installed SentinelArrays ────────────── v1.4.10 Installed Clustering ────────────────── v0.15.8 Installed TransformsBase ────────────── v1.6.0 Installed ProgressMeter ─────────────── v1.11.0 Installed StaticArrays ──────────────── v1.9.19 Installed MLUtils ───────────────────── v0.4.13 Installed StaticArraysCore ──────────── v1.4.4 Installed CodeTracking ──────────────── v3.0.2 Installed StructUtils ───────────────── v2.8.5 Installed IrrationalConstants ───────── v0.2.6 Installed Distances ─────────────────── v0.10.12 Installed NamedDims ─────────────────── v1.2.3 Installed ChainRulesCore ────────────── v1.26.1 Installed BSON ──────────────────────── v0.3.9 Installed Imbalance ─────────────────── v0.2.0 Installed SimpleTraits ──────────────── v0.9.6 Installed StringManipulation ────────── v0.5.0 Installed GPUArraysCore ─────────────── v0.2.0 Installed QuadGK ────────────────────── v2.11.3 Installed OpenSpecFun_jll ───────────── v0.5.6+0 Installed ColorTypes ────────────────── v0.12.1 Installed Requires ──────────────────── v1.3.1 Installed LogExpFunctions ───────────── v1.0.1 Installed StatisticalMeasuresBase ───── v0.1.4 Installed SpectralIndices ───────────── v0.2.20 Installed Roots ─────────────────────── v3.0.7 Installed ComputationalResources ────── v0.3.2 Installed KernelAbstractions ────────── v0.9.42 Installed JSON ──────────────────────── v1.7.1 Installed Parsers ───────────────────── v2.8.7 Installed CategoricalDistributions ──── v0.2.2 Installed Gamma ─────────────────────── v1.2.0 Installed MLJTestInterface ──────────── v0.2.9 Installed Distributions ─────────────── v0.25.131 Installed DataTreatments ────────────── v0.5.2 Installed MLJBase ───────────────────── v1.14.1 Installed PrettyTables ──────────────── v3.4.8 Installed UnsafeAtomics ─────────────── v0.3.2 Installed Parameters ────────────────── v0.13.1 Installed Tables ────────────────────── v1.14.0 Installed StatsFuns ─────────────────── v2.2.1 Installed Rmath ─────────────────────── v0.9.0 Installed ScopedValues ──────────────── v1.6.2 Installed Unitful ───────────────────── v1.28.0 Installed PtrArrays ─────────────────── v1.4.0 Installed DataFrames ────────────────── v1.8.2 Installed SpecialFunctions ──────────── v2.9.0 Installed TableTransforms ───────────── v1.38.10 Installed Scratch ───────────────────── v1.3.0 Installed IntervalSets ──────────────── v0.7.14 Installed InverseFunctions ──────────── v0.1.17 Installed Reexport ──────────────────── v1.2.2 Installed FixedPointNumbers ─────────── v0.8.6 Installed Preferences ───────────────── v1.5.2 Installed CoDa ──────────────────────── v1.5.1 Installed PooledArrays ──────────────── v1.4.3 Installed Missings ──────────────────── v1.2.0 Installed JLLWrappers ───────────────── v1.8.0 Installed TableTraits ───────────────── v1.0.1 Installed ScientificTypesBase ───────── v3.1.0 Installed ShowCases ─────────────────── v0.1.0 Installed WeakRefStrings ────────────── v1.4.3 Installed SortingAlgorithms ─────────── v1.2.3 Installed LaTeXStrings ──────────────── v1.4.1 Installed PDMats ────────────────────── v0.11.41 Installed BFloat16s ─────────────────── v0.6.1 Installed DataScienceTraits ─────────── v1.2.2 Installed ColumnSelectors ───────────── v1.0.0 Installed Crayons ───────────────────── v4.2.0 Installed AxisArrays ────────────────── v0.4.8 Installed IterTools ─────────────────── v1.10.0 Installed UnPack ────────────────────── v1.0.2 Installed WorkerUtilities ───────────── v1.6.1 Installed StatisticalTraits ─────────── v3.5.0 Installed TableOperations ───────────── v1.2.0 Installed RangeArrays ───────────────── v0.3.2 Installed DocStringExtensions ───────── v0.9.5 Installed CategoricalArrays ─────────── v1.1.1 Installed MLJModelInterface ─────────── v1.12.1 Installed Accessors ─────────────────── v0.1.45 Installed Measurements ──────────────── v2.14.1 Installing 2 artifacts Installed artifact Rmath 111.3 KiB Installed artifact OpenSpecFun 105.4 KiB Updating `~/.julia/environments/v1.14/Project.toml` [1b3ff5f2] + DataTreatments v0.5.2 Updating `~/.julia/environments/v1.14/Manifest.toml` [1520ce14] + AbstractTrees v0.4.5 [7d9f7c33] + Accessors v0.1.45 [79e6a3ab] + Adapt v4.7.0 [66dad0bd] + AliasTables v1.1.3 [a9b6321e] + Atomix v1.1.3 [39de3d68] + AxisArrays v0.4.8 [ab4f0b2a] + BFloat16s v0.6.1 [fbb218c0] + BSON v0.3.9 [336ed68f] + CSV v0.10.17 [49dc2e85] + Calculus v0.5.2 [324d7699] + CategoricalArrays v1.1.1 [af321ab8] + CategoricalDistributions v0.2.2 [d360d2e6] + ChainRulesCore v1.26.1 [aaaa29a8] + Clustering v0.15.8 [5900dafe] + CoDa v1.5.1 [da1fd8a2] + CodeTracking v3.0.2 [944b1d66] + CodecZlib v0.7.9 [3da002f7] + ColorTypes v0.12.1 [9cc86067] + ColumnSelectors v1.0.0 [38540f10] + CommonSolve v0.2.14 [34da2185] + Compat v4.18.1 [a33af91c] + CompositionsBase v0.1.2 [ed09eef8] + ComputationalResources v0.3.2 [187b0558] + ConstructionBase v1.6.0 [a8cc5b0e] + Crayons v4.2.0 [9a962f9c] + DataAPI v1.16.0 [124859b0] + DataDeps v1.0.0 [a93c6f00] + DataFrames v1.8.2 [6cb2f572] + DataScienceTraits v1.2.2 [864edb3b] + DataStructures v0.19.6 [1b3ff5f2] + DataTreatments v0.5.2 [e2d170a0] + DataValueInterfaces v1.0.0 [8bb1440f] + DelimitedFiles v1.9.1 [b4f34e82] + Distances v0.10.12 [31c24e10] + Distributions v0.25.131 [ffbed154] + DocStringExtensions v0.9.5 [48062228] + FilePathsBase v0.9.24 [1a297f60] + FillArrays v1.17.0 ⌅ [53c48c17] + FixedPointNumbers v0.8.6 [46192b85] + GPUArraysCore v0.2.0 [a0844989] + Gamma v1.2.0 [076d061b] + HashArrayMappedTries v0.2.0 [34004b35] + HypergeometricFunctions v0.3.30 [c709b415] + Imbalance v0.2.0 ⌅ [f7bf1975] + Impute v0.6.14 [842dd82b] + InlineStrings v1.4.5 [8197267c] + IntervalSets v0.7.14 [3587e190] + InverseFunctions v0.1.17 [41ab1584] + InvertedIndices v1.3.1 [92d709cd] + IrrationalConstants v0.2.6 [c8e1da08] + IterTools v1.10.0 [82899510] + IteratorInterfaceExtensions v1.0.0 [692b3bcd] + JLLWrappers v1.8.0 [682c06a0] + JSON v1.7.1 [63c18a36] + KernelAbstractions v0.9.42 [b964fa9f] + LaTeXStrings v1.4.1 [92ad9a40] + LearnAPI v2.0.1 [2ab3a3ac] + LogExpFunctions v1.0.1 [c2834f40] + MLCore v1.1.0 [a7f614a8] + MLJBase v1.14.1 [e80e1ace] + MLJModelInterface v1.12.1 [72560011] + MLJTestInterface v0.2.9 [f1d291b0] + MLUtils v0.4.13 [1914dd2f] + MacroTools v0.5.16 [eff96d63] + Measurements v2.14.1 [e1d29d7a] + Missings v1.2.0 [872c559c] + NNlib v0.9.44 [356022a1] + NamedDims v1.2.3 ⌅ [b8a86587] + NearestNeighbors v0.4.22 [2f6b4ddb] + NelderMead v0.4.0 [be38d6a3] + Normalization v0.9.3 [bac558e1] + OrderedCollections v2.0.1 [90014a1f] + PDMats v0.11.41 [d96e819e] + Parameters v0.13.1 ⌅ [69de0a69] + Parsers v2.8.7 [2dfb63ee] + PooledArrays v1.4.3 [aea7be01] + PrecompileTools v1.3.4 [21216c6a] + Preferences v1.5.2 [08abe8d2] + PrettyTables v3.4.8 [92933f4c] + ProgressMeter v1.11.0 [43287f4e] + PtrArrays v1.4.0 [1fd47b50] + QuadGK v2.11.3 [b3c3ace0] + RangeArrays v0.3.2 [3cdcf5f2] + RecipesBase v1.3.4 [189a3867] + Reexport v1.2.2 [ae029012] + Requires v1.3.1 [79098fc4] + Rmath v0.9.0 [f2b01f46] + Roots v3.0.7 [321657f4] + ScientificTypes v3.3.0 [30f210dd] + ScientificTypesBase v3.1.0 [7e506255] + ScopedValues v1.6.2 [6c6a2e73] + Scratch v1.3.0 [91c51154] + SentinelArrays v1.4.10 [605ecd9f] + ShowCases v0.1.0 [699a6c99] + SimpleTraits v0.9.6 [a2af1166] + SortingAlgorithms v1.2.3 [276daf66] + SpecialFunctions v2.9.0 [df0093a1] + SpectralIndices v0.2.20 [90137ffa] + StaticArrays v1.9.19 [1e83bf80] + StaticArraysCore v1.4.4 [c062fc1d] + StatisticalMeasuresBase v0.1.4 [64bff920] + StatisticalTraits v3.5.0 [10745b16] + Statistics v1.11.1 [82ae8749] + StatsAPI v1.8.0 [2913bbd2] + StatsBase v0.34.13 [4c63d2b9] + StatsFuns v2.2.1 [892a3eda] + StringManipulation v0.5.0 [ec057cc2] + StructUtils v2.8.5 [e5d66e97] + TableDistances v1.2.0 [ab02a1b2] + TableOperations v1.2.0 [3783bdb8] + TableTraits v1.0.1 [0d432bfd] + TableTransforms v1.38.10 [bd369af6] + Tables v1.14.0 [3bb67fe8] + TranscodingStreams v0.11.3 [28dd2a49] + TransformsBase v1.6.0 [3a884ed6] + UnPack v1.0.2 [1986cc42] + Unitful v1.28.0 [013be700] + UnsafeAtomics v0.3.2 [ea10d353] + WeakRefStrings v1.4.3 [76eceee3] + WorkerUtilities v1.6.1 [efe28fd5] + OpenSpecFun_jll v0.5.6+0 [f50d1b31] + Rmath_jll v0.5.2+0 [0dad84c5] + ArgTools v1.2.0 [56f22d72] + Artifacts v1.11.0 [2a0f44e3] + Base64 v1.11.0 [ade2ca70] + Dates v1.11.0 [8ba89e20] + Distributed v1.12.0 [f43a241f] + Downloads v1.7.0 [7b1f6079] + FileWatching v1.11.0 [9fa8497b] + Future v1.11.0 [b77e0a4c] + InteractiveUtils v1.11.0 [ac6e5ff7] + JuliaSyntaxHighlighting v1.13.0 [b27032c2] + LibCURL v1.0.0 [76f85450] + LibGit2 v1.11.0 [8f399da3] + Libdl v1.11.0 [37e2e46d] + LinearAlgebra v1.14.0 [56ddb016] + Logging v1.11.0 [d6f4376e] + Markdown v1.11.0 [a63ad114] + Mmap v1.11.0 [ca575930] + NetworkOptions v1.3.0 [44cfe95a] + Pkg v1.14.0 [de0858da] + Printf v1.11.0 [3fa0cd96] + REPL v1.11.0 [9a3f8284] + Random v1.11.0 [ea8e919c] + SHA v1.13.0 [9e88b42a] + Serialization v1.11.0 [6462fe0b] + Sockets v1.11.0 [2f01184e] + SparseArrays v1.13.0 [f489334b] + StyledStrings v1.13.0 [4607b0f0] + SuiteSparse [fa267f1f] + TOML v1.0.3 [a4e569a6] + Tar v1.10.0 [8dfed614] + Test v1.11.0 [cf7118a7] + UUIDs v1.11.0 [4ec0a83e] + Unicode v1.11.0 [e66e0078] + CompilerSupportLibraries_jll v1.5.7+0 [deac9b47] + LibCURL_jll v8.21.0+0 [e37daf67] + LibGit2_jll v1.9.7+0 [29816b5a] + LibSSH2_jll v1.11.104+0 [14a3606d] + MozillaCACerts_jll v2026.8.13 [4536629a] + OpenBLAS_jll v0.3.34+0 [05823500] + OpenLibm_jll v0.8.7+0 [458c3c95] + OpenSSL_jll v3.5.8+0 [efcefdf7] + PCRE2_jll v10.47.0+0 [bea87d4a] + SuiteSparse_jll v7.10.1+0 [83775a58] + Zlib_jll v1.3.2+0 [3161d3a3] + Zstd_jll v1.5.7+1 [8e850b90] + libblastrampoline_jll v5.15.0+0 [8e850ede] + nghttp2_jll v1.70.0+0 [3f19e933] + p7zip_jll v17.8.2+0 Info Packages marked with ⌅ have new versions available but compatibility constraints restrict them from upgrading. To see why use `status --outdated -m` Installation completed after 18.44s ################################################################################ # Precompilation # Precompiling PkgEval dependencies... Precompiling project... 5.6 s ✓ TestEnv 1 dependency successfully precompiled in 6 seconds. 27 already precompiled. Precompiling package dependencies... Precompiling project... 4.0 s ✓ MacroTools 1.4 s ✓ InlineStrings 0.5 s ✓ Reexport 1.0 s ✓ ConstructionBase 2.4 s ✓ IrrationalConstants 0.5 s ✓ DataValueInterfaces 0.6 s ✓ StatsAPI 1.0 s ✓ NelderMead 1.2 s ✓ Calculus 0.9 s ✓ IterTools 0.7 s ✓ IntervalSets 1.8 s ✓ Combinatorics 1.2 s ✓ TranscodingStreams 0.6 s ✓ LaTeXStrings 0.8 s ✓ Statistics 0.7 s ✓ StaticArraysCore 0.7 s ✓ StableRNGs 0.5 s ✓ PtrArrays 0.7 s ✓ Adapt 0.6 s ✓ DataAPI 1.2 s ✓ URIs 3.2 s ✓ UnsafeAtomics 1.3 s ✓ ShowCases 0.6 s ✓ InvertedIndices 0.9 s ✓ InverseFunctions 0.6 s ✓ CompositionsBase 1.0 s ✓ AbstractTrees 1.4 s ✓ PrettyPrinting 0.6 s ✓ EnumX 0.8 s ✓ WorkerUtilities 0.8 s ✓ ComputationalResources 2.0 s ✓ FillArrays 0.6 s ✓ ColumnSelectors 0.5 s ✓ UnPack 0.6 s ✓ RangeArrays 1.0 s ✓ OrderedCollections 0.6 s ✓ HashArrayMappedTries 0.9 s ✓ DocStringExtensions 1.3 s ✓ BSON 0.5 s ✓ IteratorInterfaceExtensions 1.8 s ✓ Crayons 0.7 s ✓ Requires 0.8 s ✓ BFloat16s 2.3 s ✓ ProgressMeter 0.7 s ✓ DelimitedFiles 1.1 s ✓ DataScienceTraits 0.9 s ✓ Scratch 29.8 s ✓ Unitful 1.8 s ✓ SentinelArrays 1.8 s ✓ StructUtils 2.1 s ✓ PDMats 0.8 s ✓ Compat 1.6 s ✓ Preferences 1.1 s ✓ ScientificTypesBase 3.0 s ✓ CodeTracking 2.4 s ✓ SimpleTraits 0.6 s ✓ ConstructionBase → ConstructionBaseLinearAlgebraExt 1.0 s ✓ Measurements 0.5 s ✓ IntervalSets → IntervalSetsRandomExt 0.5 s ✓ ConstructionBase → ConstructionBaseIntervalSetsExt 0.7 s ✓ CodecZlib 1.5 s ✓ Statistics → SparseArraysExt 2.5 s ✓ FixedPointNumbers 1.8 s ✓ NamedDims 1.1 s ✓ Distances 1.3 s ✓ EarlyStopping 0.5 s ✓ IntervalSets → IntervalSetsStatisticsExt 1.0 s ✓ AliasTables 1.4 s ✓ Adapt → AdaptSparseArraysExt 0.7 s ✓ GPUArraysCore 0.7 s ✓ Missings 0.7 s ✓ PooledArrays 0.6 s ✓ Atomix 0.9 s ✓ InverseFunctions → InverseFunctionsDatesExt 1.5 s ✓ InverseFunctions → InverseFunctionsTestExt 0.5 s ✓ CompositionsBase → CompositionsBaseInverseFunctionsExt 0.6 s ✓ TransformsBase 1.9 s ✓ FillArrays → FillArraysSparseArraysExt 0.9 s ✓ FillArrays → FillArraysStatisticsExt 0.7 s ✓ Parameters 3.4 s ✓ DataStructures 0.6 s ✓ ScopedValues 1.1 s ✓ LogExpFunctions 0.5 s ✓ TableTraits 1.4 s ✓ RelocatableFolders 2.7 s ✓ DataDeps 1.5 s ✓ Unitful → ConstructionBaseUnitfulExt 1.6 s ✓ Unitful → PrintfExt 1.5 s ✓ Unitful → InverseFunctionsUnitfulExt 1.5 s ✓ DataScienceTraits → DataScienceTraitsUnitfulExt 0.9 s ✓ StructUtils → StructUtilsStaticArraysCoreExt 1.8 s ✓ FillArrays → FillArraysPDMatsExt 0.5 s ✓ Compat → CompatLinearAlgebraExt 1.3 s ✓ PrecompileTools 1.2 s ✓ JLLWrappers 1.7 s ✓ LearnAPI 1.2 s ✓ StatisticalTraits 1.5 s ✓ Measurements → MeasurementsUnitfulExt 0.9 s ✓ StructUtils → StructUtilsMeasurementsExt 1.7 s ✓ AxisArrays 2.4 s ✓ ColorTypes 1.4 s ✓ Distances → DistancesSparseArraysExt 3.1 s ✓ IterationControl 3.8 s ✓ Accessors 0.8 s ✓ SortingAlgorithms 1.7 s ✓ QuadGK 0.6 s ✓ LogExpFunctions → LogExpFunctionsInverseFunctionsExt 1.3 s ✓ Gamma 1.6 s ✓ Tables 1.9 s ✓ ChainRulesCore 1.6 s ✓ FilePathsBase 3.4 s ✓ CategoricalArrays 6.5 s ✓ StringManipulation 1.5 s ✓ CommonSolve 13.1 s ✓ StaticArrays 2.9 s ✓ RecipesBase 38.5 s ✓ Reseau 10.6 s ✓ Parsers 1.8 s ✓ Rmath_jll 1.1 s ✓ OpenSpecFun_jll 3.7 s ✓ MLJModelInterface 1.5 s ✓ ColorTypes → StyledStringsExt 1.4 s ✓ DataScienceTraits → DataScienceTraitsColorTypesExt 1.8 s ✓ Accessors → TestExt 2.7 s ✓ Accessors → IntervalSetsExt 1.6 s ✓ Accessors → LinearAlgebraExt 1.8 s ✓ Accessors → UnitfulExt 5.4 s ✓ StatsBase 2.1 s ✓ HypergeometricFunctions 1.7 s ✓ TableOperations 1.0 s ✓ StructUtils → StructUtilsTablesExt 2.6 s ✓ MLCore 1.6 s ✓ ChainRulesCore → ChainRulesCoreSparseArraysExt 0.8 s ✓ NamedDims → ChainRulesCoreExt 0.8 s ✓ Distances → DistancesChainRulesCoreExt 3.0 s ✓ LogExpFunctions → LogExpFunctionsChainRulesCoreExt 2.9 s ✓ FilePathsBase → FilePathsBaseTestExt 0.9 s ✓ FilePathsBase → FilePathsBaseMmapExt 2.0 s ✓ CategoricalArrays → CategoricalArraysSentinelArraysExt 1.4 s ✓ DataScienceTraits → DataScienceTraitsCategoricalArraysExt 43.7 s ✓ PrettyTables 2.5 s ✓ BitBasis 1.4 s ✓ StaticArrays → StaticArraysStatisticsExt 1.5 s ✓ StaticArrays → StaticArraysChainRulesCoreExt 1.4 s ✓ ConstructionBase → ConstructionBaseStaticArraysExt 1.4 s ✓ Adapt → AdaptStaticArraysExt 2.2 s ✓ FillArrays → FillArraysStaticArraysExt 1.5 s ✓ Accessors → StaticArraysExt 1.4 s ✓ IntervalSets → IntervalSetsRecipesBaseExt 1.1 s ✓ Measurements → MeasurementsRecipesBaseExt 2.4 s ✓ CategoricalArrays → CategoricalArraysRecipesBaseExt 112.3 s ✓ HTTP 9.8 s ✓ JSON 1.1 s ✓ InlineStrings → ParsersExt 4.2 s ✓ ARFFFiles 1.8 s ✓ Rmath 5.6 s ✓ SpecialFunctions 3.4 s ✓ FeatureSelection 2.8 s ✓ MLJWrappers 2.6 s ✓ Normalization 5.6 s ✓ Roots 2.4 s ✓ LatinHypercubeSampling 2.0 s ✓ PDMats → StatsBaseExt 2.7 s ✓ CategoricalArrays → CategoricalArraysStatsBaseExt 2.5 s ✓ TableDistances 82.7 s ✓ DataFrames 3.7 s ✓ NearestNeighbors 8.1 s ✓ KernelAbstractions 18.2 s ✓ SpectralIndices 1.8 s ✓ CategoricalArrays → CategoricalArraysJSONExt 2.5 s ✓ WeakRefStrings 3.4 s ✓ SpecialFunctions → SpecialFunctionsChainRulesCoreExt 1.3 s ✓ Measurements → MeasurementsSpecialFunctionsExt 2.4 s ✓ StatsFuns 1.7 s ✓ Normalization → UnitfulExt 1.0 s ✓ Roots → RootsChainRulesCoreExt 1.6 s ✓ Roots → RootsUnitfulExt 6.2 s ✓ Normalization → DataFramesExt 3.9 s ✓ Clustering 2.5 s ✓ KernelAbstractions → SparseArraysExt 1.8 s ✓ KernelAbstractions → LinearAlgebraExt 5.1 s ✓ SpectralIndices → SpectralIndicesDataFramesExt 4.1 s ✓ OpenML 28.3 s ✓ CSV 3.0 s ✓ StatsFuns → StatsFunsChainRulesCoreExt 1.0 s ✓ StatsFuns → StatsFunsInverseFunctionsExt 11.7 s ✓ NNlib 7.4 s ✓ Impute 12.0 s ✓ Distributions 2.1 s ✓ NNlib → NNlibSpecialFunctionsExt 11.6 s ✓ MLUtils 4.9 s ✓ Distributions → DistributionsTestExt 4.1 s ✓ Distributions → DistributionsChainRulesCoreExt 3.2 s ✓ DataScienceTraits → DataScienceTraitsDistributionsExt 4.5 s ✓ CoDa 8.8 s ✓ ScientificTypes 17.6 s ✓ StatisticalMeasuresBase 4.7 s ✓ DataScienceTraits → DataScienceTraitsCoDaExt 9.1 s ✓ CategoricalDistributions 11.5 s ✓ MLJTransforms 13.1 s ✓ TableTransforms 39.9 s ✓ StatisticalMeasures 19.8 s ✓ MLJModels 12.8 s ✓ MLJEnsembles 17.7 s ✓ MLJBase 11.0 s ✓ StatisticalMeasures → ScientificTypesExt 11.3 s ✓ MLJBase → DefaultMeasuresExt 11.4 s ✓ MLJBalancing 13.6 s ✓ MLJTestInterface 15.0 s ✓ MLJIteration 12.6 s ✓ MLJTuning 12.7 s ✓ Imbalance 18.4 s ✓ MLJ 19.2 s ✓ DataTreatments 17.4 s ✓ DataTreatments → NormalizationExt 215 dependencies successfully precompiled in 1050 seconds. 39 already precompiled. Precompilation completed after 1039.94s ################################################################################ # Testing # Testing DataTreatments Status `/tmp/jl_K4pEZ5/Project.toml` [324d7699] CategoricalArrays v1.1.1 [a93c6f00] DataFrames v1.8.2 [1b3ff5f2] DataTreatments v0.5.2 [c709b415] Imbalance v0.2.0 ⌅ [f7bf1975] Impute v0.6.14 [add582a8] MLJ v0.23.3 [be38d6a3] Normalization v0.9.3 [189a3867] Reexport v1.2.2 [10745b16] Statistics v1.11.1 [2913bbd2] StatsBase v0.34.13 [37e2e46d] LinearAlgebra v1.14.0 [9a3f8284] Random v1.11.0 [8dfed614] Test v1.11.0 Status `/tmp/jl_K4pEZ5/Manifest.toml` [da404889] ARFFFiles v1.6.1 [1520ce14] AbstractTrees v0.4.5 [7d9f7c33] Accessors v0.1.45 [79e6a3ab] Adapt v4.7.0 [66dad0bd] AliasTables v1.1.3 [a9b6321e] Atomix v1.1.3 [39de3d68] AxisArrays v0.4.8 [ab4f0b2a] BFloat16s v0.6.1 [fbb218c0] BSON v0.3.9 [50ba71b6] BitBasis v0.9.10 [336ed68f] CSV v0.10.17 [49dc2e85] Calculus v0.5.2 [324d7699] CategoricalArrays v1.1.1 [af321ab8] 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FixedPointNumbers v0.8.6 [46192b85] GPUArraysCore v0.2.0 [a0844989] Gamma v1.2.0 [cd3eb016] HTTP v2.6.5 [076d061b] HashArrayMappedTries v0.2.0 [34004b35] HypergeometricFunctions v0.3.30 [c709b415] Imbalance v0.2.0 ⌅ [f7bf1975] Impute v0.6.14 [842dd82b] InlineStrings v1.4.5 [8197267c] IntervalSets v0.7.14 [3587e190] InverseFunctions v0.1.17 [41ab1584] InvertedIndices v1.3.1 [92d709cd] IrrationalConstants v0.2.6 [c8e1da08] IterTools v1.10.0 [b3c1a2ee] IterationControl v0.5.4 [82899510] IteratorInterfaceExtensions v1.0.0 [692b3bcd] JLLWrappers v1.8.0 [682c06a0] JSON v1.7.1 [63c18a36] KernelAbstractions v0.9.42 [b964fa9f] LaTeXStrings v1.4.1 [a5e1c1ea] LatinHypercubeSampling v1.9.0 [92ad9a40] LearnAPI v2.0.1 [2ab3a3ac] LogExpFunctions v1.0.1 [c2834f40] MLCore v1.1.0 [add582a8] MLJ v0.23.3 [45f359ea] MLJBalancing v0.1.6 [a7f614a8] MLJBase v1.14.1 [50ed68f4] MLJEnsembles v0.4.5 [614be32b] MLJIteration v0.6.5 [e80e1ace] MLJModelInterface v1.12.1 [d491faf4] MLJModels v0.18.9 [72560011] 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[1986cc42] Unitful v1.28.0 [013be700] UnsafeAtomics v0.3.2 [ea10d353] WeakRefStrings v1.4.3 [76eceee3] WorkerUtilities v1.6.1 [efe28fd5] OpenSpecFun_jll v0.5.6+0 [f50d1b31] Rmath_jll v0.5.2+0 [0dad84c5] ArgTools v1.2.0 [56f22d72] Artifacts v1.11.0 [2a0f44e3] Base64 v1.11.0 [ade2ca70] Dates v1.11.0 [8ba89e20] Distributed v1.12.0 [f43a241f] Downloads v1.7.0 [7b1f6079] FileWatching v1.11.0 [9fa8497b] Future v1.11.0 [b77e0a4c] InteractiveUtils v1.11.0 [ac6e5ff7] JuliaSyntaxHighlighting v1.13.0 [b27032c2] LibCURL v1.0.0 [76f85450] LibGit2 v1.11.0 [8f399da3] Libdl v1.11.0 [37e2e46d] LinearAlgebra v1.14.0 [56ddb016] Logging v1.11.0 [d6f4376e] Markdown v1.11.0 [a63ad114] Mmap v1.11.0 [ca575930] NetworkOptions v1.3.0 [44cfe95a] Pkg v1.14.0 [de0858da] Printf v1.11.0 [3fa0cd96] REPL v1.11.0 [9a3f8284] Random v1.11.0 [ea8e919c] SHA v1.13.0 [9e88b42a] Serialization v1.11.0 [6462fe0b] Sockets v1.11.0 [2f01184e] SparseArrays v1.13.0 [f489334b] StyledStrings v1.13.0 [4607b0f0] SuiteSparse [fa267f1f] TOML v1.0.3 [a4e569a6] Tar v1.10.0 [8dfed614] Test v1.11.0 [cf7118a7] UUIDs v1.11.0 [4ec0a83e] Unicode v1.11.0 [e66e0078] CompilerSupportLibraries_jll v1.5.7+0 [deac9b47] LibCURL_jll v8.21.0+0 [e37daf67] LibGit2_jll v1.9.7+0 [29816b5a] LibSSH2_jll v1.11.104+0 [14a3606d] MozillaCACerts_jll v2026.8.13 [4536629a] OpenBLAS_jll v0.3.34+0 [05823500] OpenLibm_jll v0.8.7+0 [458c3c95] OpenSSL_jll v3.5.8+0 [efcefdf7] PCRE2_jll v10.47.0+0 [bea87d4a] SuiteSparse_jll v7.10.1+0 [83775a58] Zlib_jll v1.3.2+0 [3161d3a3] Zstd_jll v1.5.7+1 [8e850b90] libblastrampoline_jll v5.15.0+0 [8e850ede] nghttp2_jll v1.70.0+0 [3f19e933] p7zip_jll v17.8.2+0 Info Packages marked with ⌅ have new versions available but compatibility constraints restrict them from upgrading. Testing Running tests... Julia version: 1.14.0-DEV.3055 ################################################## TEST: windowing.jl ################################################## TEST: inspecting.jl ################################################## TEST: impute.jl WARNING: Method definition make_matrix() in module Main at /home/pkgeval/.julia/packages/DataTreatments/y7AmF/test/impute.jl:26 overwritten at /home/pkgeval/.julia/packages/DataTreatments/y7AmF/test/impute.jl:30. WARNING: Method definition make_matrix(Any) in module Main at /home/pkgeval/.julia/packages/DataTreatments/y7AmF/test/impute.jl:26 overwritten at /home/pkgeval/.julia/packages/DataTreatments/y7AmF/test/impute.jl:30. WARNING: Method definition make_matrix(Any, Any) in module Main at /home/pkgeval/.julia/packages/DataTreatments/y7AmF/test/impute.jl:26 overwritten at /home/pkgeval/.julia/packages/DataTreatments/y7AmF/test/impute.jl:30. ┌ Warning: Imputing on matrices will require specifying `dims=2` or `dims=:cols` in a future release, to maintain the current behaviour. │ caller = impute!(data::Matrix{Union{Missing, Float64}}, imp::LOCF; dims::Nothing, kwargs::Base.Pairs{Symbol, Union{}, Nothing, @NamedTuple{}}) at imputors.jl:142 └ @ Impute ~/.julia/packages/Impute/NS9pa/src/imputors.jl:142 ┌ Warning: Imputing on matrices will require specifying `dims=2` or `dims=:cols` in a future release, to maintain the current behaviour. │ caller = impute!(data::Matrix{Union{Missing, Float64}}, imp::NOCB; dims::Nothing, kwargs::Base.Pairs{Symbol, Union{}, Nothing, @NamedTuple{}}) at imputors.jl:142 └ @ Impute ~/.julia/packages/Impute/NS9pa/src/imputors.jl:142 ┌ Warning: Imputing on matrices will require specifying `dims=2` or `dims=:cols` in a future release, to maintain the current behaviour. │ caller = impute!(data::Matrix{Union{Missing, Float64}}, imp::Interpolate; dims::Nothing, kwargs::Base.Pairs{Symbol, Union{}, Nothing, @NamedTuple{}}) at imputors.jl:142 └ @ Impute ~/.julia/packages/Impute/NS9pa/src/imputors.jl:142 ┌ Warning: Imputing on matrices will require specifying `dims=2` or `dims=:cols` in a future release, to maintain the current behaviour. │ caller = impute!(data::Matrix{Union{Missing, Float64}}, imp::Substitute{typeof(Impute.defaultstats)}; dims::Nothing, kwargs::Base.Pairs{Symbol, Union{}, Nothing, @NamedTuple{}}) at imputors.jl:142 └ @ Impute ~/.julia/packages/Impute/NS9pa/src/imputors.jl:142 ┌ Warning: Imputing on matrices will require specifying `dims=2` or `dims=:cols` in a future release, to maintain the current behaviour. │ caller = impute!(data::Matrix{Union{Missing, Float64}}, imp::Substitute{typeof(mean)}; dims::Nothing, kwargs::Base.Pairs{Symbol, Union{}, Nothing, @NamedTuple{}}) at imputors.jl:142 └ @ Impute ~/.julia/packages/Impute/NS9pa/src/imputors.jl:142 WARNING: Wrapping `Vararg` directly in UnionAll is deprecated (wrap the tuple instead). You may need to write `f(x::Vararg{T})` rather than `f(x::Vararg{<:T})` or `f(x::Vararg{T}) where T` instead of `f(x::Vararg{T} where T)`. To make this warning an error, and hence obtain a stack trace, use `julia --depwarn=error`. WARNING: Wrapping `Vararg` directly in UnionAll is deprecated (wrap the tuple instead). You may need to write `f(x::Vararg{T})` rather than `f(x::Vararg{<:T})` or `f(x::Vararg{T}) where T` instead of `f(x::Vararg{T} where T)`. To make this warning an error, and hence obtain a stack trace, use `julia --depwarn=error`. WARNING: Wrapping `Vararg` directly in UnionAll is deprecated (wrap the tuple instead). You may need to write `f(x::Vararg{T})` rather than `f(x::Vararg{<:T})` or `f(x::Vararg{T}) where T` instead of `f(x::Vararg{T} where T)`. To make this warning an error, and hence obtain a stack trace, use `julia --depwarn=error`. WARNING: Wrapping `Vararg` directly in UnionAll is deprecated (wrap the tuple instead). You may need to write `f(x::Vararg{T})` rather than `f(x::Vararg{<:T})` or `f(x::Vararg{T}) where T` instead of `f(x::Vararg{T} where T)`. To make this warning an error, and hence obtain a stack trace, use `julia --depwarn=error`. WARNING: Wrapping `Vararg` directly in UnionAll is deprecated (wrap the tuple instead). You may need to write `f(x::Vararg{T})` rather than `f(x::Vararg{<:T})` or `f(x::Vararg{T}) where T` instead of `f(x::Vararg{T} where T)`. To make this warning an error, and hence obtain a stack trace, use `julia --depwarn=error`. ┌ Warning: Imputing on matrices will require specifying `dims=2` or `dims=:cols` in a future release, to maintain the current behaviour. │ caller = impute!(data::Matrix{Union{Missing, Array{Float64}}}, imp::Substitute{typeof(mean)}; dims::Nothing, kwargs::Base.Pairs{Symbol, Union{}, Nothing, @NamedTuple{}}) at imputors.jl:142 └ @ Impute ~/.julia/packages/Impute/NS9pa/src/imputors.jl:142 ################################################## TEST: imbalance.jl WARNING: Wrapping `Vararg` directly in UnionAll is deprecated (wrap the tuple instead). You may need to write `f(x::Vararg{T})` rather than `f(x::Vararg{<:T})` or `f(x::Vararg{T}) where T` instead of `f(x::Vararg{T} where T)`. To make this warning an error, and hence obtain a stack trace, use `julia --depwarn=error`. Progress: 67%|███████████████████████████▍ | ETA: 0:00:01 class: virginica WARNING: Wrapping `Vararg` directly in UnionAll is deprecated (wrap the tuple instead). You may need to write `f(x::Vararg{T})` rather than `f(x::Vararg{<:T})` or `f(x::Vararg{T}) where T` instead of `f(x::Vararg{T} where T)`. To make this warning an error, and hence obtain a stack trace, use `julia --depwarn=error`. RandomWalkOversampler: Error During Test at /home/pkgeval/.julia/packages/DataTreatments/y7AmF/test/imbalance.jl:25 Got exception outside of a @test TaskFailedException nested task error: MethodError: no method matching reducedim1(::Matrix{Float64}, ::Matrix{Float64}) The function `reducedim1` exists, but no method is defined for this combination of argument types. Closest candidates are: reducedim1(::Any) @ Base reducedim.jl:1229 Stacktrace: [1] centralize_sumabs2!(R::Matrix{Float64}, A::Matrix{Float64}, means::Matrix{Float64}) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:282 [2] varm!(R::Matrix{Float64}, A::Matrix{Float64}, m::Matrix{Float64}; corrected::Bool) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:309 [3] _varm(A::Matrix{Float64}, m::Matrix{Float64}, corrected::Bool, region::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:341 [4] varm(A::Matrix{Float64}, m::Matrix{Float64}; corrected::Bool, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:339 [inlined] [5] _var(A::Matrix{Float64}, corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:386 [inlined] [6] var(A::Matrix{Float64}; corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:380 [inlined] [7] _std(A::Matrix{Float64}, corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:469 [8] std(A::Matrix{Float64}; corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:461 [inlined] [9] random_walk_per_class(X::SubArray{Float64, 2, LinearAlgebra.Transpose{Float64, Matrix{Float64}}, Tuple{Base.Slice{Base.OneTo{Int64}}, Vector{Int64}}, false}, n::Int64, cont_inds::Vector{Int64}, cat_inds::Vector{Int64}; rng::Xoshiro) @ Imbalance ~/.julia/packages/Imbalance/mQpnn/src/oversampling_methods/random_walk/random_walk.jl:101 [10] generic_oversample(::Matrix{Float64}, ::CategoricalVector{String, UInt32, String, CategoricalValue{String, UInt32}, Union{}}, ::typeof(Imbalance.random_walk_per_class), ::Vector{Int64}, ::Vararg{Vector{Int64}}; ratios::Float64, pass_inds::Bool, is_transposed::Bool, kwargs::@Kwargs{rng::Xoshiro}) @ Imbalance ~/.julia/packages/Imbalance/mQpnn/src/generic_resample.jl:50 [11] random_walk_oversample(X::Matrix{Float64}, y::CategoricalVector{String, UInt32, String, CategoricalValue{String, UInt32}, Union{}}, cat_inds::Vector{Int64}; ratios::Float64, rng::Int64, try_preserve_type::Bool) @ Imbalance ~/.julia/packages/Imbalance/mQpnn/src/oversampling_methods/random_walk/random_walk.jl:258 [inlined] [12] _random_walk_oversample(X::Matrix{Float64}, y::CategoricalVector{String, UInt32, String, CategoricalValue{String, UInt32}, Union{}}; kwargs::@Kwargs{ratios::Float64, rng::Int64, try_preserve_type::Bool}) @ DataTreatments ~/.julia/packages/DataTreatments/y7AmF/src/imbalance.jl:85 [inlined] [13] (::DataTreatments.var"#216#217"{Tuple{@NamedTuple{ratios::Float64, rng::Int64, try_preserve_type::Bool}}, Tuple{typeof(DataTreatments._random_walk_oversample)}})(acc::Tuple{Matrix{Float64}, CategoricalVector{String, UInt32, String, CategoricalValue{String, UInt32}, Union{}}}, i::Int64) @ DataTreatments ~/.julia/packages/DataTreatments/y7AmF/src/load_dataset.jl:321 [inlined] [14] (::Base.BottomRF{DataTreatments.var"#216#217"{Tuple{@NamedTuple{ratios::Float64, rng::Int64, try_preserve_type::Bool}}, Tuple{typeof(DataTreatments._random_walk_oversample)}}})(acc::Tuple{Matrix{Float64}, CategoricalVector{String, UInt32, String, CategoricalValue{String, UInt32}, Union{}}}, x::Int64) @ Base reduce.jl:84 [inlined] [15] _foldl_impl(op::Base.BottomRF{DataTreatments.var"#216#217"{Tuple{@NamedTuple{ratios::Float64, rng::Int64, try_preserve_type::Bool}}, Tuple{typeof(DataTreatments._random_walk_oversample)}}}, init::Tuple{Matrix{Float64}, CategoricalVector{String, UInt32, String, CategoricalValue{String, UInt32}, Union{}}}, itr::Base.OneTo{Int64}) @ Base reduce.jl:56 [16] foldl_impl(op::Base.BottomRF{DataTreatments.var"#216#217"{Tuple{@NamedTuple{ratios::Float64, rng::Int64, try_preserve_type::Bool}}, Tuple{typeof(DataTreatments._random_walk_oversample)}}}, nt::Tuple{Matrix{Float64}, CategoricalVector{String, UInt32, String, CategoricalValue{String, UInt32}, Union{}}}, itr::Base.OneTo{Int64}) @ Base reduce.jl:46 [inlined] [17] mapfoldl_impl(f::typeof(identity), op::DataTreatments.var"#216#217"{Tuple{@NamedTuple{ratios::Float64, rng::Int64, try_preserve_type::Bool}}, Tuple{typeof(DataTreatments._random_walk_oversample)}}, nt::Tuple{Matrix{Float64}, CategoricalVector{String, UInt32, String, CategoricalValue{String, UInt32}, Union{}}}, itr::Base.OneTo{Int64}) @ Base reduce.jl:42 [18] _mapreduce_dim(f::Function, op::Function, nt::Tuple{Matrix{Float64}, CategoricalVector{String, UInt32, String, CategoricalValue{String, UInt32}, Union{}}}, A::Base.OneTo{Int64}, ::Colon) @ Base reducedim.jl:333 [19] mapreduce(f::typeof(identity), op::Function, A::Base.OneTo{Int64}; dims::Colon, init::Tuple{Matrix{Float64}, CategoricalVector{String, UInt32, String, CategoricalValue{String, UInt32}, Union{}}}) @ Base reducedim.jl:328 [inlined] [20] reduce(op::Function, A::Base.OneTo{Int64}; kw::@Kwargs{init::Tuple{Matrix{Float64}, CategoricalVector{String, UInt32, String, CategoricalValue{String, UInt32}, Union{}}}}) @ Base reducedim.jl:383 [inlined] [21] macro expansion @ ~/.julia/packages/DataTreatments/y7AmF/src/load_dataset.jl:320 [inlined] [22] (::DataTreatments.var"#214#215"{Tuple{@NamedTuple{ratios::Float64, rng::Int64, try_preserve_type::Bool}}, Tuple{typeof(DataTreatments._random_walk_oversample)}, Vector{DataTreatments.AbstractDataset}})(tid::Int64) @ DataTreatments threadingconstructs.jl:555 [23] (::Base.Threads.var"#threading_run##2#threading_run##3"{Int64, DataTreatments.var"#214#215"{Tuple{@NamedTuple{ratios::Float64, rng::Int64, try_preserve_type::Bool}}, Tuple{typeof(DataTreatments._random_walk_oversample)}, Vector{DataTreatments.AbstractDataset}}})() @ Base.Threads threadingconstructs.jl:185 Stacktrace: [1] threading_run(fun::DataTreatments.var"#214#215"{Tuple{@NamedTuple{ratios::Float64, rng::Int64, try_preserve_type::Bool}}, Tuple{typeof(DataTreatments._random_walk_oversample)}, Vector{DataTreatments.AbstractDataset}}, static::Bool) @ Base.Threads threadingconstructs.jl:228 [2] macro expansion @ threadingconstructs.jl:240 [inlined] [3] load_dataset(data::Matrix{Float64}, vnames::Vector{String}, target::CategoricalVector{String, UInt32, String, CategoricalValue{String, UInt32}, Union{}}, treatments::DataTreatments.var"#123#124"{@Kwargs{aggrfunc::DataTreatments.var"#91#92"{Tuple{DataTreatments.var"#wholewindow##0#wholewindow##1"}, Tuple{typeof(maximum), typeof(minimum), typeof(mean)}}, grouped::Bool}}; balance::RandomWalkOversampler{Float64}, treatment_ds::Bool, leftover_ds::Bool, float_type::Type) @ DataTreatments ~/.julia/packages/DataTreatments/y7AmF/src/load_dataset.jl:319 [4] load_dataset(::DataFrame, ::CategoricalVector{String, UInt32, String, CategoricalValue{String, UInt32}, Union{}}; kwargs::@Kwargs{balance::RandomWalkOversampler{Float64}}) @ DataTreatments ~/.julia/packages/DataTreatments/y7AmF/src/load_dataset.jl:343 [5] top-level scope @ ~/.julia/packages/DataTreatments/y7AmF/test/imbalance.jl:16 [6] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [7] macro expansion @ ~/.julia/packages/DataTreatments/y7AmF/test/imbalance.jl:26 [inlined] [8] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [9] macro expansion @ ~/.julia/packages/DataTreatments/y7AmF/test/imbalance.jl:26 [inlined] WARNING: Wrapping `Vararg` directly in UnionAll is deprecated (wrap the tuple instead). You may need to write `f(x::Vararg{T})` rather than `f(x::Vararg{<:T})` or `f(x::Vararg{T}) where T` instead of `f(x::Vararg{T} where T)`. To make this warning an error, and hence obtain a stack trace, use `julia --depwarn=error`. ROSE: Error During Test at /home/pkgeval/.julia/packages/DataTreatments/y7AmF/test/imbalance.jl:34 Got exception outside of a @test TaskFailedException nested task error: MethodError: no method matching reducedim1(::Matrix{Float64}, ::SubArray{Float64, 2, LinearAlgebra.Transpose{Float64, Matrix{Float64}}, Tuple{Base.Slice{Base.OneTo{Int64}}, Vector{Int64}}, false}) The function `reducedim1` exists, but no method is defined for this combination of argument types. Closest candidates are: reducedim1(::Any) @ Base reducedim.jl:1229 Stacktrace: [1] centralize_sumabs2!(R::Matrix{Float64}, A::SubArray{Float64, 2, LinearAlgebra.Transpose{Float64, Matrix{Float64}}, Tuple{Base.Slice{Base.OneTo{Int64}}, Vector{Int64}}, false}, means::Matrix{Float64}) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:282 [2] varm!(R::Matrix{Float64}, A::SubArray{Float64, 2, LinearAlgebra.Transpose{Float64, Matrix{Float64}}, Tuple{Base.Slice{Base.OneTo{Int64}}, Vector{Int64}}, false}, m::Matrix{Float64}; corrected::Bool) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:309 [3] _varm(A::SubArray{Float64, 2, LinearAlgebra.Transpose{Float64, Matrix{Float64}}, Tuple{Base.Slice{Base.OneTo{Int64}}, Vector{Int64}}, false}, m::Matrix{Float64}, corrected::Bool, region::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:341 [4] varm(A::SubArray{Float64, 2, LinearAlgebra.Transpose{Float64, Matrix{Float64}}, Tuple{Base.Slice{Base.OneTo{Int64}}, Vector{Int64}}, false}, m::Matrix{Float64}; corrected::Bool, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:339 [inlined] [5] _var(A::SubArray{Float64, 2, LinearAlgebra.Transpose{Float64, Matrix{Float64}}, Tuple{Base.Slice{Base.OneTo{Int64}}, Vector{Int64}}, false}, corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:386 [inlined] [6] var(A::SubArray{Float64, 2, LinearAlgebra.Transpose{Float64, Matrix{Float64}}, Tuple{Base.Slice{Base.OneTo{Int64}}, Vector{Int64}}, false}; corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:380 [inlined] [7] _std(A::SubArray{Float64, 2, LinearAlgebra.Transpose{Float64, Matrix{Float64}}, Tuple{Base.Slice{Base.OneTo{Int64}}, Vector{Int64}}, false}, corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:469 [8] std(A::SubArray{Float64, 2, LinearAlgebra.Transpose{Float64, Matrix{Float64}}, Tuple{Base.Slice{Base.OneTo{Int64}}, Vector{Int64}}, false}; corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:461 [inlined] [9] rose_per_class(X::SubArray{Float64, 2, LinearAlgebra.Transpose{Float64, Matrix{Float64}}, Tuple{Base.Slice{Base.OneTo{Int64}}, Vector{Int64}}, false}, n::Int64; s::Float64, rng::Xoshiro) @ Imbalance ~/.julia/packages/Imbalance/mQpnn/src/oversampling_methods/rose/rose.jl:25 [10] generic_oversample(::Matrix{Float64}, ::CategoricalVector{String, UInt32, String, CategoricalValue{String, UInt32}, Union{}}, ::typeof(Imbalance.rose_per_class); ratios::Float64, pass_inds::Bool, is_transposed::Bool, kwargs::@Kwargs{s::Float64, rng::Xoshiro}) @ Imbalance ~/.julia/packages/Imbalance/mQpnn/src/generic_resample.jl:50 [11] rose(X::Matrix{Float64}, y::CategoricalVector{String, UInt32, String, CategoricalValue{String, UInt32}, Union{}}; s::Float64, ratios::Float64, rng::Int64, try_preserve_type::Bool) @ Imbalance ~/.julia/packages/Imbalance/mQpnn/src/oversampling_methods/rose/rose.jl:174 [inlined] [12] (::DataTreatments.var"#216#217"{Tuple{@NamedTuple{s::Float64, ratios::Float64, rng::Int64, try_preserve_type::Bool}}, Tuple{typeof(Imbalance.rose)}})(acc::Tuple{Matrix{Float64}, CategoricalVector{String, UInt32, String, CategoricalValue{String, UInt32}, Union{}}}, i::Int64) @ DataTreatments ~/.julia/packages/DataTreatments/y7AmF/src/load_dataset.jl:321 [inlined] [13] (::Base.BottomRF{DataTreatments.var"#216#217"{Tuple{@NamedTuple{s::Float64, ratios::Float64, rng::Int64, try_preserve_type::Bool}}, Tuple{typeof(Imbalance.rose)}}})(acc::Tuple{Matrix{Float64}, CategoricalVector{String, UInt32, String, CategoricalValue{String, UInt32}, Union{}}}, x::Int64) @ Base reduce.jl:84 [inlined] [14] _foldl_impl(op::Base.BottomRF{DataTreatments.var"#216#217"{Tuple{@NamedTuple{s::Float64, ratios::Float64, rng::Int64, try_preserve_type::Bool}}, Tuple{typeof(Imbalance.rose)}}}, init::Tuple{Matrix{Float64}, CategoricalVector{String, UInt32, String, CategoricalValue{String, UInt32}, Union{}}}, itr::Base.OneTo{Int64}) @ Base reduce.jl:56 [15] foldl_impl(op::Base.BottomRF{DataTreatments.var"#216#217"{Tuple{@NamedTuple{s::Float64, ratios::Float64, rng::Int64, try_preserve_type::Bool}}, Tuple{typeof(Imbalance.rose)}}}, nt::Tuple{Matrix{Float64}, CategoricalVector{String, UInt32, String, CategoricalValue{String, UInt32}, Union{}}}, itr::Base.OneTo{Int64}) @ Base reduce.jl:46 [inlined] [16] mapfoldl_impl(f::typeof(identity), op::DataTreatments.var"#216#217"{Tuple{@NamedTuple{s::Float64, ratios::Float64, rng::Int64, try_preserve_type::Bool}}, Tuple{typeof(Imbalance.rose)}}, nt::Tuple{Matrix{Float64}, CategoricalVector{String, UInt32, String, CategoricalValue{String, UInt32}, Union{}}}, itr::Base.OneTo{Int64}) @ Base reduce.jl:42 [17] _mapreduce_dim(f::Function, op::Function, nt::Tuple{Matrix{Float64}, CategoricalVector{String, UInt32, String, CategoricalValue{String, UInt32}, Union{}}}, A::Base.OneTo{Int64}, ::Colon) @ Base reducedim.jl:333 [18] mapreduce(f::typeof(identity), op::Function, A::Base.OneTo{Int64}; dims::Colon, init::Tuple{Matrix{Float64}, CategoricalVector{String, UInt32, String, CategoricalValue{String, UInt32}, Union{}}}) @ Base reducedim.jl:328 [inlined] [19] reduce(op::Function, A::Base.OneTo{Int64}; kw::@Kwargs{init::Tuple{Matrix{Float64}, CategoricalVector{String, UInt32, String, CategoricalValue{String, UInt32}, Union{}}}}) @ Base reducedim.jl:383 [inlined] [20] macro expansion @ ~/.julia/packages/DataTreatments/y7AmF/src/load_dataset.jl:320 [inlined] [21] (::DataTreatments.var"#214#215"{Tuple{@NamedTuple{s::Float64, ratios::Float64, rng::Int64, try_preserve_type::Bool}}, Tuple{typeof(Imbalance.rose)}, Vector{DataTreatments.AbstractDataset}})(tid::Int64) @ DataTreatments threadingconstructs.jl:555 [22] (::Base.Threads.var"#threading_run##2#threading_run##3"{Int64, DataTreatments.var"#214#215"{Tuple{@NamedTuple{s::Float64, ratios::Float64, rng::Int64, try_preserve_type::Bool}}, Tuple{typeof(Imbalance.rose)}, Vector{DataTreatments.AbstractDataset}}})() @ Base.Threads threadingconstructs.jl:185 Stacktrace: [1] threading_run(fun::DataTreatments.var"#214#215"{Tuple{@NamedTuple{s::Float64, ratios::Float64, rng::Int64, try_preserve_type::Bool}}, Tuple{typeof(Imbalance.rose)}, Vector{DataTreatments.AbstractDataset}}, static::Bool) @ Base.Threads threadingconstructs.jl:228 [2] macro expansion @ threadingconstructs.jl:240 [inlined] [3] load_dataset(data::Matrix{Float64}, vnames::Vector{String}, target::CategoricalVector{String, UInt32, String, CategoricalValue{String, UInt32}, Union{}}, treatments::DataTreatments.var"#123#124"{@Kwargs{aggrfunc::DataTreatments.var"#91#92"{Tuple{DataTreatments.var"#wholewindow##0#wholewindow##1"}, Tuple{typeof(maximum), typeof(minimum), typeof(mean)}}, grouped::Bool}}; balance::ROSE{Float64}, treatment_ds::Bool, leftover_ds::Bool, float_type::Type) @ DataTreatments ~/.julia/packages/DataTreatments/y7AmF/src/load_dataset.jl:319 [4] load_dataset(::DataFrame, ::CategoricalVector{String, UInt32, String, CategoricalValue{String, UInt32}, Union{}}; kwargs::@Kwargs{balance::ROSE{Float64}}) @ DataTreatments ~/.julia/packages/DataTreatments/y7AmF/src/load_dataset.jl:343 [5] top-level scope @ ~/.julia/packages/DataTreatments/y7AmF/test/imbalance.jl:16 [6] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [7] macro expansion @ ~/.julia/packages/DataTreatments/y7AmF/test/imbalance.jl:35 [inlined] [8] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [9] macro expansion @ ~/.julia/packages/DataTreatments/y7AmF/test/imbalance.jl:35 [inlined] WARNING: Wrapping `Vararg` directly in UnionAll is deprecated (wrap the tuple instead). You may need to write `f(x::Vararg{T})` rather than `f(x::Vararg{<:T})` or `f(x::Vararg{T}) where T` instead of `f(x::Vararg{T} where T)`. To make this warning an error, and hence obtain a stack trace, use `julia --depwarn=error`. Progress: 67%|███████████████████████████▍ | ETA: 0:00:02 class: virginica WARNING: Wrapping `Vararg` directly in UnionAll is deprecated (wrap the tuple instead). You may need to write `f(x::Vararg{T})` rather than `f(x::Vararg{<:T})` or `f(x::Vararg{T}) where T` instead of `f(x::Vararg{T} where T)`. To make this warning an error, and hence obtain a stack trace, use `julia --depwarn=error`. ┌ Warning: Cannot oversample a class with no borderline points. Skipping. └ @ Imbalance ~/.julia/packages/Imbalance/mQpnn/src/oversampling_methods/borderline_smote1/borderline_smote1.jl:67 Progress: 67%|███████████████████████████▍ | ETA: 0:00:00 class: virginica WARNING: Wrapping `Vararg` directly in UnionAll is deprecated (wrap the tuple instead). You may need to write `f(x::Vararg{T})` rather than `f(x::Vararg{<:T})` or `f(x::Vararg{T}) where T` instead of `f(x::Vararg{T} where T)`. To make this warning an error, and hence obtain a stack trace, use `julia --depwarn=error`. WARNING: Wrapping `Vararg` directly in UnionAll is deprecated (wrap the tuple instead). You may need to write `f(x::Vararg{T})` rather than `f(x::Vararg{<:T})` or `f(x::Vararg{T}) where T` instead of `f(x::Vararg{T} where T)`. To make this warning an error, and hence obtain a stack trace, use `julia --depwarn=error`. Progress: 67%|███████████████████████████▍ | ETA: 0:00:01 class: virginica WARNING: Wrapping `Vararg` directly in UnionAll is deprecated (wrap the tuple instead). You may need to write `f(x::Vararg{T})` rather than `f(x::Vararg{<:T})` or `f(x::Vararg{T}) where T` instead of `f(x::Vararg{T} where T)`. To make this warning an error, and hence obtain a stack trace, use `julia --depwarn=error`. Progress: 67%|███████████████████████████▍ | ETA: 0:00:09 class: virginica WARNING: Wrapping `Vararg` directly in UnionAll is deprecated (wrap the tuple instead). You may need to write `f(x::Vararg{T})` rather than `f(x::Vararg{<:T})` or `f(x::Vararg{T}) where T` instead of `f(x::Vararg{T} where T)`. To make this warning an error, and hence obtain a stack trace, use `julia --depwarn=error`. Progress: 67%|███████████████████████████▍ | ETA: 0:00:01 class: virginica WARNING: Wrapping `Vararg` directly in UnionAll is deprecated (wrap the tuple instead). You may need to write `f(x::Vararg{T})` rather than `f(x::Vararg{<:T})` or `f(x::Vararg{T}) where T` instead of `f(x::Vararg{T} where T)`. To make this warning an error, and hence obtain a stack trace, use `julia --depwarn=error`. WARNING: Wrapping `Vararg` directly in UnionAll is deprecated (wrap the tuple instead). You may need to write `f(x::Vararg{T})` rather than `f(x::Vararg{<:T})` or `f(x::Vararg{T}) where T` instead of `f(x::Vararg{T} where T)`. To make this warning an error, and hence obtain a stack trace, use `julia --depwarn=error`. WARNING: Wrapping `Vararg` directly in UnionAll is deprecated (wrap the tuple instead). You may need to write `f(x::Vararg{T})` rather than `f(x::Vararg{<:T})` or `f(x::Vararg{T}) where T` instead of `f(x::Vararg{T} where T)`. To make this warning an error, and hence obtain a stack trace, use `julia --depwarn=error`. Chained ROSE + ENNUndersampler: Error During Test at /home/pkgeval/.julia/packages/DataTreatments/y7AmF/test/imbalance.jl:124 Got exception outside of a @test TaskFailedException nested task error: MethodError: no method matching reducedim1(::Matrix{Float64}, ::SubArray{Float64, 2, LinearAlgebra.Transpose{Float64, Matrix{Float64}}, Tuple{Base.Slice{Base.OneTo{Int64}}, Vector{Int64}}, false}) The function `reducedim1` exists, but no method is defined for this combination of argument types. Closest candidates are: reducedim1(::Any) @ Base reducedim.jl:1229 Stacktrace: [1] centralize_sumabs2!(R::Matrix{Float64}, A::SubArray{Float64, 2, LinearAlgebra.Transpose{Float64, Matrix{Float64}}, Tuple{Base.Slice{Base.OneTo{Int64}}, Vector{Int64}}, false}, means::Matrix{Float64}) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:282 [2] varm!(R::Matrix{Float64}, A::SubArray{Float64, 2, LinearAlgebra.Transpose{Float64, Matrix{Float64}}, Tuple{Base.Slice{Base.OneTo{Int64}}, Vector{Int64}}, false}, m::Matrix{Float64}; corrected::Bool) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:309 [3] _varm(A::SubArray{Float64, 2, LinearAlgebra.Transpose{Float64, Matrix{Float64}}, Tuple{Base.Slice{Base.OneTo{Int64}}, Vector{Int64}}, false}, m::Matrix{Float64}, corrected::Bool, region::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:341 [4] varm(A::SubArray{Float64, 2, LinearAlgebra.Transpose{Float64, Matrix{Float64}}, Tuple{Base.Slice{Base.OneTo{Int64}}, Vector{Int64}}, false}, m::Matrix{Float64}; corrected::Bool, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:339 [inlined] [5] _var(A::SubArray{Float64, 2, LinearAlgebra.Transpose{Float64, Matrix{Float64}}, Tuple{Base.Slice{Base.OneTo{Int64}}, Vector{Int64}}, false}, corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:386 [inlined] [6] var(A::SubArray{Float64, 2, LinearAlgebra.Transpose{Float64, Matrix{Float64}}, Tuple{Base.Slice{Base.OneTo{Int64}}, Vector{Int64}}, false}; corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:380 [inlined] [7] _std(A::SubArray{Float64, 2, LinearAlgebra.Transpose{Float64, Matrix{Float64}}, Tuple{Base.Slice{Base.OneTo{Int64}}, Vector{Int64}}, false}, corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:469 [8] std(A::SubArray{Float64, 2, LinearAlgebra.Transpose{Float64, Matrix{Float64}}, Tuple{Base.Slice{Base.OneTo{Int64}}, Vector{Int64}}, false}; corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:461 [inlined] [9] rose_per_class(X::SubArray{Float64, 2, LinearAlgebra.Transpose{Float64, Matrix{Float64}}, Tuple{Base.Slice{Base.OneTo{Int64}}, Vector{Int64}}, false}, n::Int64; s::Float64, rng::Xoshiro) @ Imbalance ~/.julia/packages/Imbalance/mQpnn/src/oversampling_methods/rose/rose.jl:25 [10] generic_oversample(::Matrix{Float64}, ::CategoricalVector{String, UInt32, String, CategoricalValue{String, UInt32}, Union{}}, ::typeof(Imbalance.rose_per_class); ratios::Float64, pass_inds::Bool, is_transposed::Bool, kwargs::@Kwargs{s::Float64, rng::Xoshiro}) @ Imbalance ~/.julia/packages/Imbalance/mQpnn/src/generic_resample.jl:50 [11] rose(X::Matrix{Float64}, y::CategoricalVector{String, UInt32, String, CategoricalValue{String, UInt32}, Union{}}; s::Float64, ratios::Float64, rng::Int64, try_preserve_type::Bool) @ Imbalance ~/.julia/packages/Imbalance/mQpnn/src/oversampling_methods/rose/rose.jl:174 [inlined] [12] (::DataTreatments.var"#216#217"{Tuple{@NamedTuple{s::Float64, ratios::Float64, rng::Int64, try_preserve_type::Bool}, @NamedTuple{k::Int64, keep_condition::String, force_min_ratios::Bool, min_ratios::Float64, rng::Int64, try_preserve_type::Bool}}, Tuple{typeof(Imbalance.rose), typeof(Imbalance.enn_undersample)}})(acc::Tuple{Matrix{Float64}, CategoricalVector{String, UInt32, String, CategoricalValue{String, UInt32}, Union{}}}, i::Int64) @ DataTreatments ~/.julia/packages/DataTreatments/y7AmF/src/load_dataset.jl:321 [13] (::Base.BottomRF{DataTreatments.var"#216#217"{Tuple{@NamedTuple{s::Float64, ratios::Float64, rng::Int64, try_preserve_type::Bool}, @NamedTuple{k::Int64, keep_condition::String, force_min_ratios::Bool, min_ratios::Float64, rng::Int64, try_preserve_type::Bool}}, Tuple{typeof(Imbalance.rose), typeof(Imbalance.enn_undersample)}}})(acc::Tuple{Matrix{Float64}, CategoricalVector{String, UInt32, String, CategoricalValue{String, UInt32}, Union{}}}, x::Int64) @ Base reduce.jl:84 [inlined] [14] _foldl_impl(op::Base.BottomRF{DataTreatments.var"#216#217"{Tuple{@NamedTuple{s::Float64, ratios::Float64, rng::Int64, try_preserve_type::Bool}, @NamedTuple{k::Int64, keep_condition::String, force_min_ratios::Bool, min_ratios::Float64, rng::Int64, try_preserve_type::Bool}}, Tuple{typeof(Imbalance.rose), typeof(Imbalance.enn_undersample)}}}, init::Tuple{Matrix{Float64}, CategoricalVector{String, UInt32, String, CategoricalValue{String, UInt32}, Union{}}}, itr::Base.OneTo{Int64}) @ Base reduce.jl:56 [15] foldl_impl(op::Base.BottomRF{DataTreatments.var"#216#217"{Tuple{@NamedTuple{s::Float64, ratios::Float64, rng::Int64, try_preserve_type::Bool}, @NamedTuple{k::Int64, keep_condition::String, force_min_ratios::Bool, min_ratios::Float64, rng::Int64, try_preserve_type::Bool}}, Tuple{typeof(Imbalance.rose), typeof(Imbalance.enn_undersample)}}}, nt::Tuple{Matrix{Float64}, CategoricalVector{String, UInt32, String, CategoricalValue{String, UInt32}, Union{}}}, itr::Base.OneTo{Int64}) @ Base reduce.jl:46 [inlined] [16] mapfoldl_impl(f::typeof(identity), op::DataTreatments.var"#216#217"{Tuple{@NamedTuple{s::Float64, ratios::Float64, rng::Int64, try_preserve_type::Bool}, @NamedTuple{k::Int64, keep_condition::String, force_min_ratios::Bool, min_ratios::Float64, rng::Int64, try_preserve_type::Bool}}, Tuple{typeof(Imbalance.rose), typeof(Imbalance.enn_undersample)}}, nt::Tuple{Matrix{Float64}, CategoricalVector{String, UInt32, String, CategoricalValue{String, UInt32}, Union{}}}, itr::Base.OneTo{Int64}) @ Base reduce.jl:42 [17] _mapreduce_dim(f::Function, op::Function, nt::Tuple{Matrix{Float64}, CategoricalVector{String, UInt32, String, CategoricalValue{String, UInt32}, Union{}}}, A::Base.OneTo{Int64}, ::Colon) @ Base reducedim.jl:333 [18] mapreduce(f::typeof(identity), op::Function, A::Base.OneTo{Int64}; dims::Colon, init::Tuple{Matrix{Float64}, CategoricalVector{String, UInt32, String, CategoricalValue{String, UInt32}, Union{}}}) @ Base reducedim.jl:328 [inlined] [19] reduce(op::Function, A::Base.OneTo{Int64}; kw::@Kwargs{init::Tuple{Matrix{Float64}, CategoricalVector{String, UInt32, String, CategoricalValue{String, UInt32}, Union{}}}}) @ Base reducedim.jl:383 [inlined] [20] macro expansion @ ~/.julia/packages/DataTreatments/y7AmF/src/load_dataset.jl:320 [inlined] [21] (::DataTreatments.var"#214#215"{Tuple{@NamedTuple{s::Float64, ratios::Float64, rng::Int64, try_preserve_type::Bool}, @NamedTuple{k::Int64, keep_condition::String, force_min_ratios::Bool, min_ratios::Float64, rng::Int64, try_preserve_type::Bool}}, Tuple{typeof(Imbalance.rose), typeof(Imbalance.enn_undersample)}, Vector{DataTreatments.AbstractDataset}})(tid::Int64) @ DataTreatments threadingconstructs.jl:555 [22] (::Base.Threads.var"#threading_run##2#threading_run##3"{Int64, DataTreatments.var"#214#215"{Tuple{@NamedTuple{s::Float64, ratios::Float64, rng::Int64, try_preserve_type::Bool}, @NamedTuple{k::Int64, keep_condition::String, force_min_ratios::Bool, min_ratios::Float64, rng::Int64, try_preserve_type::Bool}}, Tuple{typeof(Imbalance.rose), typeof(Imbalance.enn_undersample)}, Vector{DataTreatments.AbstractDataset}}})() @ Base.Threads threadingconstructs.jl:185 Stacktrace: [1] threading_run(fun::DataTreatments.var"#214#215"{Tuple{@NamedTuple{s::Float64, ratios::Float64, rng::Int64, try_preserve_type::Bool}, @NamedTuple{k::Int64, keep_condition::String, force_min_ratios::Bool, min_ratios::Float64, rng::Int64, try_preserve_type::Bool}}, Tuple{typeof(Imbalance.rose), typeof(Imbalance.enn_undersample)}, Vector{DataTreatments.AbstractDataset}}, static::Bool) @ Base.Threads threadingconstructs.jl:228 [2] macro expansion @ threadingconstructs.jl:240 [inlined] [3] load_dataset(data::Matrix{Float64}, vnames::Vector{String}, target::CategoricalVector{String, UInt32, String, CategoricalValue{String, UInt32}, Union{}}, treatments::DataTreatments.var"#123#124"{@Kwargs{aggrfunc::DataTreatments.var"#91#92"{Tuple{DataTreatments.var"#wholewindow##0#wholewindow##1"}, Tuple{typeof(maximum), typeof(minimum), typeof(mean)}}, grouped::Bool}}; balance::Tuple{ROSE{Float64}, ENNUndersampler{Float64}}, treatment_ds::Bool, leftover_ds::Bool, float_type::Type) @ DataTreatments ~/.julia/packages/DataTreatments/y7AmF/src/load_dataset.jl:319 [4] load_dataset(::DataFrame, ::CategoricalVector{String, UInt32, String, CategoricalValue{String, UInt32}, Union{}}; kwargs::@Kwargs{balance::Tuple{ROSE{Float64}, ENNUndersampler{Float64}}}) @ DataTreatments ~/.julia/packages/DataTreatments/y7AmF/src/load_dataset.jl:343 [5] top-level scope @ ~/.julia/packages/DataTreatments/y7AmF/test/imbalance.jl:16 [6] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [7] macro expansion @ ~/.julia/packages/DataTreatments/y7AmF/test/imbalance.jl:125 [inlined] [8] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [9] macro expansion @ ~/.julia/packages/DataTreatments/y7AmF/test/imbalance.jl:125 [inlined] WARNING: Wrapping `Vararg` directly in UnionAll is deprecated (wrap the tuple instead). You may need to write `f(x::Vararg{T})` rather than `f(x::Vararg{<:T})` or `f(x::Vararg{T}) where T` instead of `f(x::Vararg{T} where T)`. To make this warning an error, and hence obtain a stack trace, use `julia --depwarn=error`. Progress: 67%|███████████████████████████▍ | ETA: 0:00:02 class: virginica WARNING: Wrapping `Vararg` directly in UnionAll is deprecated (wrap the tuple instead). You may need to write `f(x::Vararg{T})` rather than `f(x::Vararg{<:T})` or `f(x::Vararg{T}) where T` instead of `f(x::Vararg{T} where T)`. To make this warning an error, and hence obtain a stack trace, use `julia --depwarn=error`. ################################################## TEST: normalization.jl ################################################## TEST: load_dataset.jl WARNING: Method definition create_image(Int64) in module Main at /home/pkgeval/.julia/packages/DataTreatments/y7AmF/test/inspecting.jl:9 overwritten at /home/pkgeval/.julia/packages/DataTreatments/y7AmF/test/load_dataset.jl:13. WARNING: Method definition kwcall(NamedTuple{names, T} where T<:Tuple where names, typeof(Main.create_image), Int64) in module Main at /home/pkgeval/.julia/packages/DataTreatments/y7AmF/test/inspecting.jl:9 overwritten at /home/pkgeval/.julia/packages/DataTreatments/y7AmF/test/load_dataset.jl:13. WARNING: Method definition build_test_df() in module Main at /home/pkgeval/.julia/packages/DataTreatments/y7AmF/test/inspecting.jl:14 overwritten at /home/pkgeval/.julia/packages/DataTreatments/y7AmF/test/load_dataset.jl:18. WARNING: Wrapping `Vararg` directly in UnionAll is deprecated (wrap the tuple instead). You may need to write `f(x::Vararg{T})` rather than `f(x::Vararg{<:T})` or `f(x::Vararg{T}) where T` instead of `f(x::Vararg{T} where T)`. To make this warning an error, and hence obtain a stack trace, use `julia --depwarn=error`. WARNING: Wrapping `Vararg` directly in UnionAll is deprecated (wrap the tuple instead). You may need to write `f(x::Vararg{T})` rather than `f(x::Vararg{<:T})` or `f(x::Vararg{T}) where T` instead of `f(x::Vararg{T} where T)`. To make this warning an error, and hence obtain a stack trace, use `julia --depwarn=error`. WARNING: Wrapping `Vararg` directly in UnionAll is deprecated (wrap the tuple instead). You may need to write `f(x::Vararg{T})` rather than `f(x::Vararg{<:T})` or `f(x::Vararg{T}) where T` instead of `f(x::Vararg{T} where T)`. To make this warning an error, and hence obtain a stack trace, use `julia --depwarn=error`. ┌ Warning: Imputing on matrices will require specifying `dims=2` or `dims=:cols` in a future release, to maintain the current behaviour. │ caller = impute!(data::Matrix{Union{Missing, Float64}}, imp::Substitute{typeof(Impute.defaultstats)}; dims::Nothing, kwargs::Base.Pairs{Symbol, Union{}, Nothing, @NamedTuple{}}) at imputors.jl:142 └ @ Impute ~/.julia/packages/Impute/NS9pa/src/imputors.jl:142 WARNING: Wrapping `Vararg` directly in UnionAll is deprecated (wrap the tuple instead). You may need to write `f(x::Vararg{T})` rather than `f(x::Vararg{<:T})` or `f(x::Vararg{T}) where T` instead of `f(x::Vararg{T} where T)`. To make this warning an error, and hence obtain a stack trace, use `julia --depwarn=error`. WARNING: Wrapping `Vararg` directly in UnionAll is deprecated (wrap the tuple instead). You may need to write `f(x::Vararg{T})` rather than `f(x::Vararg{<:T})` or `f(x::Vararg{T}) where T` instead of `f(x::Vararg{T} where T)`. To make this warning an error, and hence obtain a stack trace, use `julia --depwarn=error`. WARNING: Wrapping `Vararg` directly in UnionAll is deprecated (wrap the tuple instead). You may need to write `f(x::Vararg{T})` rather than `f(x::Vararg{<:T})` or `f(x::Vararg{T}) where T` instead of `f(x::Vararg{T} where T)`. To make this warning an error, and hence obtain a stack trace, use `julia --depwarn=error`. WARNING: Wrapping `Vararg` directly in UnionAll is deprecated (wrap the tuple instead). You may need to write `f(x::Vararg{T})` rather than `f(x::Vararg{<:T})` or `f(x::Vararg{T}) where T` instead of `f(x::Vararg{T} where T)`. To make this warning an error, and hence obtain a stack trace, use `julia --depwarn=error`. WARNING: Wrapping `Vararg` directly in UnionAll is deprecated (wrap the tuple instead). You may need to write `f(x::Vararg{T})` rather than `f(x::Vararg{<:T})` or `f(x::Vararg{T}) where T` instead of `f(x::Vararg{T} where T)`. To make this warning an error, and hence obtain a stack trace, use `julia --depwarn=error`. WARNING: Wrapping `Vararg` directly in UnionAll is deprecated (wrap the tuple instead). You may need to write `f(x::Vararg{T})` rather than `f(x::Vararg{<:T})` or `f(x::Vararg{T}) where T` instead of `f(x::Vararg{T} where T)`. To make this warning an error, and hence obtain a stack trace, use `julia --depwarn=error`. ┌ Warning: Imputing on matrices will require specifying `dims=2` or `dims=:cols` in a future release, to maintain the current behaviour. │ caller = impute!(data::Matrix{Union{Missing, Array{Float64}}}, imp::Substitute{typeof(mean)}; dims::Nothing, kwargs::Base.Pairs{Symbol, Union{}, Nothing, @NamedTuple{}}) at imputors.jl:142 └ @ Impute ~/.julia/packages/Impute/NS9pa/src/imputors.jl:142 WARNING: Wrapping `Vararg` directly in UnionAll is deprecated (wrap the tuple instead). You may need to write `f(x::Vararg{T})` rather than `f(x::Vararg{<:T})` or `f(x::Vararg{T}) where T` instead of `f(x::Vararg{T} where T)`. To make this warning an error, and hence obtain a stack trace, use `julia --depwarn=error`. ┌ Warning: Imputing on matrices will require specifying `dims=2` or `dims=:cols` in a future release, to maintain the current behaviour. │ caller = impute!(data::Matrix{Union{Missing, Array{Float64}}}, imp::LOCF; dims::Nothing, kwargs::Base.Pairs{Symbol, Union{}, Nothing, @NamedTuple{}}) at imputors.jl:142 └ @ Impute ~/.julia/packages/Impute/NS9pa/src/imputors.jl:142 ┌ Warning: Imputing on matrices will require specifying `dims=2` or `dims=:cols` in a future release, to maintain the current behaviour. │ caller = impute!(data::Matrix{Union{Missing, Array{Float64}}}, imp::NOCB; dims::Nothing, kwargs::Base.Pairs{Symbol, Union{}, Nothing, @NamedTuple{}}) at imputors.jl:142 └ @ Impute ~/.julia/packages/Impute/NS9pa/src/imputors.jl:142 ┌ Warning: Imputing on matrices will require specifying `dims=2` or `dims=:cols` in a future release, to maintain the current behaviour. │ caller = impute!(data::Matrix{Union{Missing, Float64}}, imp::Impute.Replace; dims::Nothing, kwargs::Base.Pairs{Symbol, Union{}, Nothing, @NamedTuple{}}) at imputors.jl:142 └ @ Impute ~/.julia/packages/Impute/NS9pa/src/imputors.jl:142 ################################################## TEST: examples.jl WARNING: Method definition create_image(Int64) in module Main at /home/pkgeval/.julia/packages/DataTreatments/y7AmF/test/load_dataset.jl:13 overwritten at /home/pkgeval/.julia/packages/DataTreatments/y7AmF/test/examples.jl:13. WARNING: Method definition kwcall(NamedTuple{names, T} where T<:Tuple where names, typeof(Main.create_image), Int64) in module Main at /home/pkgeval/.julia/packages/DataTreatments/y7AmF/test/load_dataset.jl:13 overwritten at /home/pkgeval/.julia/packages/DataTreatments/y7AmF/test/examples.jl:13. WARNING: Method definition build_test_df() in module Main at /home/pkgeval/.julia/packages/DataTreatments/y7AmF/test/load_dataset.jl:18 overwritten at /home/pkgeval/.julia/packages/DataTreatments/y7AmF/test/examples.jl:18. WARNING: Wrapping `Vararg` directly in UnionAll is deprecated (wrap the tuple instead). You may need to write `f(x::Vararg{T})` rather than `f(x::Vararg{<:T})` or `f(x::Vararg{T}) where T` instead of `f(x::Vararg{T} where T)`. To make this warning an error, and hence obtain a stack trace, use `julia --depwarn=error`. WARNING: Wrapping `Vararg` directly in UnionAll is deprecated (wrap the tuple instead). You may need to write `f(x::Vararg{T})` rather than `f(x::Vararg{<:T})` or `f(x::Vararg{T}) where T` instead of `f(x::Vararg{T} where T)`. To make this warning an error, and hence obtain a stack trace, use `julia --depwarn=error`. WARNING: Wrapping `Vararg` directly in UnionAll is deprecated (wrap the tuple instead). You may need to write `f(x::Vararg{T})` rather than `f(x::Vararg{<:T})` or `f(x::Vararg{T}) where T` instead of `f(x::Vararg{T} where T)`. To make this warning an error, and hence obtain a stack trace, use `julia --depwarn=error`. WARNING: Wrapping `Vararg` directly in UnionAll is deprecated (wrap the tuple instead). You may need to write `f(x::Vararg{T})` rather than `f(x::Vararg{<:T})` or `f(x::Vararg{T}) where T` instead of `f(x::Vararg{T} where T)`. To make this warning an error, and hence obtain a stack trace, use `julia --depwarn=error`. WARNING: Wrapping `Vararg` directly in UnionAll is deprecated (wrap the tuple instead). You may need to write `f(x::Vararg{T})` rather than `f(x::Vararg{<:T})` or `f(x::Vararg{T}) where T` instead of `f(x::Vararg{T} where T)`. To make this warning an error, and hence obtain a stack trace, use `julia --depwarn=error`. WARNING: Wrapping `Vararg` directly in UnionAll is deprecated (wrap the tuple instead). You may need to write `f(x::Vararg{T})` rather than `f(x::Vararg{<:T})` or `f(x::Vararg{T}) where T` instead of `f(x::Vararg{T} where T)`. To make this warning an error, and hence obtain a stack trace, use `julia --depwarn=error`. WARNING: Wrapping `Vararg` directly in UnionAll is deprecated (wrap the tuple instead). You may need to write `f(x::Vararg{T})` rather than `f(x::Vararg{<:T})` or `f(x::Vararg{T}) where T` instead of `f(x::Vararg{T} where T)`. To make this warning an error, and hence obtain a stack trace, use `julia --depwarn=error`. WARNING: Wrapping `Vararg` directly in UnionAll is deprecated (wrap the tuple instead). You may need to write `f(x::Vararg{T})` rather than `f(x::Vararg{<:T})` or `f(x::Vararg{T}) where T` instead of `f(x::Vararg{T} where T)`. To make this warning an error, and hence obtain a stack trace, use `julia --depwarn=error`. ################################################## TEST: multidim_treatment.jl WARNING: Method definition create_image(Int64) in module Main at /home/pkgeval/.julia/packages/DataTreatments/y7AmF/test/examples.jl:13 overwritten at /home/pkgeval/.julia/packages/DataTreatments/y7AmF/test/multidim_treatment.jl:8. WARNING: Method definition kwcall(NamedTuple{names, T} where T<:Tuple where names, typeof(Main.create_image), Int64) in module Main at /home/pkgeval/.julia/packages/DataTreatments/y7AmF/test/examples.jl:13 overwritten at /home/pkgeval/.julia/packages/DataTreatments/y7AmF/test/multidim_treatment.jl:8. WARNING: Method definition build_test_df() in module Main at /home/pkgeval/.julia/packages/DataTreatments/y7AmF/test/examples.jl:18 overwritten at /home/pkgeval/.julia/packages/DataTreatments/y7AmF/test/multidim_treatment.jl:13. ################################################## TEST: treatment_group.jl WARNING: Method definition create_image(Int64) in module Main at /home/pkgeval/.julia/packages/DataTreatments/y7AmF/test/multidim_treatment.jl:8 overwritten at /home/pkgeval/.julia/packages/DataTreatments/y7AmF/test/treatment_group.jl:8. WARNING: Method definition kwcall(NamedTuple{names, T} where T<:Tuple where names, typeof(Main.create_image), Int64) in module Main at /home/pkgeval/.julia/packages/DataTreatments/y7AmF/test/multidim_treatment.jl:8 overwritten at /home/pkgeval/.julia/packages/DataTreatments/y7AmF/test/treatment_group.jl:8. WARNING: Method definition build_test_df() in module Main at /home/pkgeval/.julia/packages/DataTreatments/y7AmF/test/multidim_treatment.jl:13 overwritten at /home/pkgeval/.julia/packages/DataTreatments/y7AmF/test/treatment_group.jl:13. ################################################## TEST: datatreatment.jl WARNING: Method definition create_image(Int64) in module Main at /home/pkgeval/.julia/packages/DataTreatments/y7AmF/test/treatment_group.jl:8 overwritten at /home/pkgeval/.julia/packages/DataTreatments/y7AmF/test/datatreatment.jl:9. WARNING: Method definition kwcall(NamedTuple{names, T} where T<:Tuple where names, typeof(Main.create_image), Int64) in module Main at /home/pkgeval/.julia/packages/DataTreatments/y7AmF/test/treatment_group.jl:8 overwritten at /home/pkgeval/.julia/packages/DataTreatments/y7AmF/test/datatreatment.jl:9. WARNING: Method definition build_test_df() in module Main at /home/pkgeval/.julia/packages/DataTreatments/y7AmF/test/treatment_group.jl:13 overwritten at /home/pkgeval/.julia/packages/DataTreatments/y7AmF/test/datatreatment.jl:14. Test Summary: | Pass Error Total Time DataTreatments.jl | 334 3 337 7m20.4s Windowing | 42 42 6.6s Dataset Inspect | 13 13 16.0s Imputation | 21 21 1m21.1s Imbalance | 11 3 14 2m57.7s Imbalance structs | 11 3 14 2m15.5s RandomOversampler | 1 1 40.0s RandomWalkOversampler | 1 1 15.4s ROSE | 1 1 3.4s SMOTE | 1 1 5.9s BorderlineSMOTE1 | 1 1 9.5s SMOTENC | 1 1 1.6s RandomUndersampler | 1 1 4.0s ClusterUndersampler | 1 1 23.3s ENNUndersampler | 1 1 6.4s TomekUndersampler | 1 1 1.6s Chained SMOTE + TomekUndersampler | 1 1 2.0s Chained ROSE + ENNUndersampler | 1 1 1.0s SMOTEN | 1 1 19.3s No balance | 1 1 0.2s Normalization | 46 46 33.9s Load Dataset | 72 72 1m24.5s Examples | 35 35 6.4s Multidim Treatments | 38 38 5.2s Treatment Groups | 18 18 4.1s DataTreatment | 38 38 24.7s RNG of the outermost testset: Xoshiro(0x49c11612fe90ae76, 0xd479258590276f27, 0x829db96824fcdea9, 0x08649743778f4c17, 0x8f014884ace269d9) ERROR: LoadError: Some tests did not pass: 334 passed, 0 failed, 3 errored, 0 broken. in expression starting at /home/pkgeval/.julia/packages/DataTreatments/y7AmF/test/runtests.jl:27 Testing failed after 466.93s ERROR: LoadError: Package DataTreatments errored during testing Stacktrace: [1] pkgerror(msg::String) @ Pkg.Types /opt/julia/share/julia/stdlib/v1.14/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/v1.14/Pkg/src/Operations.jl:3283 [3] 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/v1.14/Pkg/src/API.jl:587 [4] test(pkgs::Vector{PackageSpec}; io::IOContext{IO}, kwargs::@Kwargs{julia_args::Cmd}) @ Pkg.API /opt/julia/share/julia/stdlib/v1.14/Pkg/src/API.jl:172 [5] test(pkgs::Vector{String}; kwargs::@Kwargs{julia_args::Cmd}) @ Pkg.API /opt/julia/share/julia/stdlib/v1.14/Pkg/src/API.jl:160 [6] test(pkg::String; kwargs::@Kwargs{julia_args::Cmd}) @ Pkg.API /opt/julia/share/julia/stdlib/v1.14/Pkg/src/API.jl:159 [inlined] [7] top-level scope @ /PkgEval.jl/scripts/evaluate.jl:223 in expression starting at /PkgEval.jl/scripts/evaluate.jl:214 PkgEval failed after 1644.82s: package tests unexpectedly errored