Package evaluation of TMLE on Julia 1.10.9 (96dc2d8c45*) started at 2025-06-06T22:53:49.556 ################################################################################ # Set-up # Installing PkgEval dependencies (TestEnv)... Set-up completed after 5.23s ################################################################################ # Installation # Installing TMLE... Resolving package versions... Installed TMLE ─ v0.19.0 Updating `~/.julia/environments/v1.10/Project.toml` [8afdd2fb] + TMLE v0.19.0 Updating `~/.julia/environments/v1.10/Manifest.toml` [47edcb42] + ADTypes v1.14.0 [621f4979] + AbstractFFTs v1.5.0 [7d9f7c33] + Accessors v0.1.42 [79e6a3ab] + Adapt v4.3.0 [66dad0bd] + AliasTables v1.1.3 [dce04be8] + ArgCheck v2.5.0 [ec485272] + ArnoldiMethod v0.4.0 [a9b6321e] + Atomix v1.1.1 [15f4f7f2] + AutoHashEquals v2.2.0 [198e06fe] + BangBang v0.4.4 [9718e550] + Baselet v0.1.1 [324d7699] + CategoricalArrays v0.10.8 [af321ab8] + CategoricalDistributions v0.1.15 [082447d4] + ChainRules v1.72.4 [d360d2e6] + ChainRulesCore v1.25.1 [3da002f7] + ColorTypes v0.12.1 [861a8166] + Combinatorics v1.0.3 [38540f10] + CommonSolve v0.2.4 [bbf7d656] + CommonSubexpressions v0.3.1 [34da2185] + Compat v4.16.0 [a33af91c] + CompositionsBase v0.1.2 [ed09eef8] + ComputationalResources v0.3.2 [187b0558] + ConstructionBase v1.5.8 [6add18c4] + ContextVariablesX v0.1.3 [a8cc5b0e] + Crayons v4.1.1 [9a962f9c] + DataAPI v1.16.0 [a93c6f00] + DataFrames v1.7.0 [864edb3b] + DataStructures v0.18.22 [e2d170a0] + DataValueInterfaces v1.0.0 [244e2a9f] + DefineSingletons v0.1.2 [8bb1440f] + DelimitedFiles v1.9.1 [85a47980] + Dictionaries v0.4.5 [163ba53b] + DiffResults v1.1.0 [b552c78f] + DiffRules v1.15.1 ⌅ [a0c0ee7d] + DifferentiationInterface v0.6.54 [b4f34e82] + Distances v0.10.12 [31c24e10] + Distributions v0.25.120 [ffbed154] + DocStringExtensions v0.9.4 [cc61a311] + FLoops v0.2.2 [b9860ae5] + FLoopsBase v0.1.1 [5789e2e9] + FileIO v1.17.0 [1a297f60] + FillArrays v1.13.0 [53c48c17] + FixedPointNumbers v0.8.5 [f6369f11] + ForwardDiff v1.0.1 [38e38edf] + GLM v1.9.0 [46192b85] + GPUArraysCore v0.2.0 [86223c79] + Graphs v1.13.0 [076d061b] + HashArrayMappedTries v0.2.0 [34004b35] + HypergeometricFunctions v0.3.28 [09f84164] + HypothesisTests v0.11.5 [7869d1d1] + IRTools v0.4.14 [313cdc1a] + Indexing v1.1.1 [d25df0c9] + Inflate v0.1.5 [22cec73e] + InitialValues v0.3.1 [842dd82b] + InlineStrings v1.4.3 [3587e190] + InverseFunctions v0.1.17 [41ab1584] + InvertedIndices v1.3.1 [92d709cd] + IrrationalConstants v0.2.4 [82899510] + IteratorInterfaceExtensions v1.0.0 [033835bb] + JLD2 v0.5.13 [692b3bcd] + JLLWrappers v1.7.0 [b14d175d] + JuliaVariables v0.2.4 [63c18a36] + KernelAbstractions v0.9.34 [b964fa9f] + LaTeXStrings v1.4.0 [92ad9a40] + LearnAPI v1.0.1 [2ab3a3ac] + LogExpFunctions v0.3.29 [c2834f40] + MLCore v1.0.0 [a7f614a8] + MLJBase v1.8.1 [caf8df21] + MLJGLMInterface v0.3.7 [e80e1ace] + MLJModelInterface v1.11.1 [d491faf4] + MLJModels v0.17.9 [d8e11817] + MLStyle v0.4.17 [f1d291b0] + MLUtils v0.4.8 [1914dd2f] + MacroTools v0.5.16 [fa8bd995] + MetaGraphsNext v0.7.3 [128add7d] + MicroCollections v0.2.0 [e1d29d7a] + Missings v1.2.0 [872c559c] + NNlib v0.9.30 [77ba4419] + NaNMath v1.1.3 [71a1bf82] + NameResolution v0.1.5 [bac558e1] + OrderedCollections v1.8.1 [90014a1f] + PDMats v0.11.35 [d96e819e] + Parameters v0.12.3 [2dfb63ee] + PooledArrays v1.4.3 ⌅ [aea7be01] + PrecompileTools v1.2.1 [21216c6a] + Preferences v1.4.3 [8162dcfd] + PrettyPrint v0.2.0 [54e16d92] + PrettyPrinting v0.4.2 [08abe8d2] + PrettyTables v2.4.0 [92933f4c] + ProgressMeter v1.10.4 [43287f4e] + PtrArrays v1.3.0 [1fd47b50] + QuadGK v2.11.2 [c1ae055f] + RealDot v0.1.0 [3cdcf5f2] + RecipesBase v1.3.4 [189a3867] + Reexport v1.2.2 [05181044] + RelocatableFolders v1.0.1 [ae029012] + Requires v1.3.1 [79098fc4] + Rmath v0.8.0 [f2b01f46] + Roots v2.2.7 [321657f4] + ScientificTypes v3.1.0 [30f210dd] + ScientificTypesBase v3.0.0 [7e506255] + ScopedValues v1.3.0 [6c6a2e73] + Scratch v1.2.1 [91c51154] + SentinelArrays v1.4.8 [efcf1570] + Setfield v1.1.2 [1277b4bf] + ShiftedArrays v2.0.0 [605ecd9f] + ShowCases v0.1.0 [699a6c99] + SimpleTraits v0.9.4 [a2af1166] + SortingAlgorithms v1.2.1 [dc90abb0] + SparseInverseSubset v0.1.2 [276daf66] + SpecialFunctions v2.5.1 [03a91e81] + SplitApplyCombine v1.2.3 [171d559e] + SplittablesBase v0.1.15 [90137ffa] + StaticArrays v1.9.13 [1e83bf80] + StaticArraysCore v1.4.3 [a19d573c] + StatisticalMeasures v0.2.1 [c062fc1d] + StatisticalMeasuresBase v0.1.2 [64bff920] + StatisticalTraits v3.4.0 [82ae8749] + StatsAPI v1.7.1 [2913bbd2] + StatsBase v0.34.5 [4c63d2b9] + StatsFuns v1.5.0 [3eaba693] + StatsModels v0.7.4 [892a3eda] + StringManipulation v0.4.1 [09ab397b] + StructArrays v0.7.1 [8afdd2fb] + TMLE v0.19.0 [ab02a1b2] + TableOperations v1.2.0 [3783bdb8] + TableTraits v1.0.1 [bd369af6] + Tables v1.12.1 [3bb67fe8] + TranscodingStreams v0.11.3 [28d57a85] + Transducers v0.4.84 [3a884ed6] + UnPack v1.0.2 [013be700] + UnsafeAtomics v0.3.0 [e88e6eb3] + Zygote v0.7.8 [700de1a5] + ZygoteRules v0.2.7 [efe28fd5] + OpenSpecFun_jll v0.5.6+0 [f50d1b31] + Rmath_jll v0.5.1+0 [0dad84c5] + ArgTools v1.1.1 [56f22d72] + Artifacts [2a0f44e3] + Base64 [ade2ca70] + Dates [8ba89e20] + Distributed [f43a241f] + Downloads v1.6.0 [7b1f6079] + FileWatching [9fa8497b] + Future [b77e0a4c] + InteractiveUtils [b27032c2] + LibCURL v0.6.4 [76f85450] + LibGit2 [8f399da3] + Libdl [37e2e46d] + LinearAlgebra [56ddb016] + Logging [d6f4376e] + Markdown [a63ad114] + Mmap [ca575930] + NetworkOptions v1.2.0 [44cfe95a] + Pkg v1.10.0 [de0858da] + Printf [3fa0cd96] + REPL [9a3f8284] + Random [ea8e919c] + SHA v0.7.0 [9e88b42a] + Serialization [1a1011a3] + SharedArrays [6462fe0b] + Sockets [2f01184e] + SparseArrays v1.10.0 [10745b16] + Statistics v1.10.0 [4607b0f0] + SuiteSparse [fa267f1f] + TOML v1.0.3 [a4e569a6] + Tar v1.10.0 [8dfed614] + Test [cf7118a7] + UUIDs [4ec0a83e] + Unicode [e66e0078] + CompilerSupportLibraries_jll v1.1.1+0 [deac9b47] + LibCURL_jll v8.4.0+0 [e37daf67] + LibGit2_jll v1.6.4+0 [29816b5a] + LibSSH2_jll v1.11.0+1 [c8ffd9c3] + MbedTLS_jll v2.28.2+1 [14a3606d] + MozillaCACerts_jll v2023.1.10 [4536629a] + OpenBLAS_jll v0.3.23+4 [05823500] + OpenLibm_jll v0.8.5+0 [bea87d4a] + SuiteSparse_jll v7.2.1+1 [83775a58] + Zlib_jll v1.2.13+1 [8e850b90] + libblastrampoline_jll v5.11.0+0 [8e850ede] + nghttp2_jll v1.52.0+1 [3f19e933] + p7zip_jll v17.4.0+2 Info Packages marked with ⌅ have new versions available but compatibility constraints restrict them from upgrading. To see why use `status --outdated -m` Installation completed after 8.9s ################################################################################ # Precompilation # Precompiling PkgEval dependencies... Precompiling package dependencies... Precompilation completed after 1365.69s ################################################################################ # Testing # Testing TMLE Status `/tmp/jl_0VRVlD/Project.toml` [336ed68f] CSV v0.10.15 [324d7699] CategoricalArrays v0.10.8 [6af48e0c] CausalTables v1.2.7 [861a8166] Combinatorics v1.0.3 [a93c6f00] DataFrames v1.7.0 [31c24e10] Distributions v0.25.120 [09f84164] HypothesisTests v0.11.5 [682c06a0] JSON v0.21.4 [2ab3a3ac] LogExpFunctions v0.3.29 [a7f614a8] MLJBase v1.8.1 [caf8df21] MLJGLMInterface v0.3.7 [6ee0df7b] MLJLinearModels v0.10.1 [d491faf4] MLJModels v0.17.9 [54119dfa] MLJXGBoostInterface v0.3.12 [bac558e1] OrderedCollections v1.8.1 [860ef19b] StableRNGs v1.0.3 [a19d573c] StatisticalMeasures v0.2.1 [2913bbd2] StatsBase v0.34.5 [8afdd2fb] TMLE v0.19.0 [ab02a1b2] TableOperations v1.2.0 [bd369af6] Tables v1.12.1 [ddb6d928] YAML v0.4.14 [9a3f8284] Random [9e88b42a] Serialization [10745b16] Statistics v1.10.0 [8dfed614] Test Status `/tmp/jl_0VRVlD/Manifest.toml` [47edcb42] ADTypes v1.14.0 [621f4979] AbstractFFTs v1.5.0 [1520ce14] AbstractTrees v0.4.5 [7d9f7c33] Accessors v0.1.42 [79e6a3ab] Adapt v4.3.0 [66dad0bd] AliasTables v1.1.3 [dce04be8] ArgCheck v2.5.0 [ec485272] ArnoldiMethod v0.4.0 [4fba245c] ArrayInterface v7.19.0 [a9b6321e] Atomix v1.1.1 [15f4f7f2] AutoHashEquals v2.2.0 [198e06fe] BangBang v0.4.4 [9718e550] Baselet v0.1.1 [fa961155] CEnum v0.5.0 [336ed68f] CSV v0.10.15 [324d7699] CategoricalArrays v0.10.8 [af321ab8] CategoricalDistributions v0.1.15 [6af48e0c] CausalTables v1.2.7 [082447d4] ChainRules v1.72.4 [d360d2e6] ChainRulesCore v1.25.1 [944b1d66] CodecZlib v0.7.8 [3da002f7] ColorTypes v0.12.1 [861a8166] Combinatorics v1.0.3 [38540f10] CommonSolve v0.2.4 [bbf7d656] CommonSubexpressions v0.3.1 [34da2185] Compat v4.16.0 [a33af91c] CompositionsBase v0.1.2 [ed09eef8] ComputationalResources v0.3.2 [187b0558] ConstructionBase v1.5.8 [6add18c4] ContextVariablesX v0.1.3 [a8cc5b0e] Crayons v4.1.1 [9a962f9c] DataAPI v1.16.0 [a93c6f00] DataFrames v1.7.0 [864edb3b] DataStructures v0.18.22 [e2d170a0] DataValueInterfaces v1.0.0 [244e2a9f] DefineSingletons v0.1.2 [8bb1440f] DelimitedFiles v1.9.1 [85a47980] Dictionaries v0.4.5 [163ba53b] DiffResults v1.1.0 [b552c78f] DiffRules v1.15.1 ⌅ [a0c0ee7d] DifferentiationInterface v0.6.54 [b4f34e82] Distances v0.10.12 [31c24e10] Distributions v0.25.120 [ffbed154] DocStringExtensions v0.9.4 [4e289a0a] EnumX v1.0.5 [cc61a311] FLoops v0.2.2 [b9860ae5] FLoopsBase v0.1.1 [5789e2e9] FileIO v1.17.0 [48062228] FilePathsBase v0.9.24 [1a297f60] FillArrays v1.13.0 [6a86dc24] FiniteDiff v2.27.0 [53c48c17] FixedPointNumbers v0.8.5 [f6369f11] ForwardDiff v1.0.1 [38e38edf] GLM v1.9.0 [46192b85] GPUArraysCore v0.2.0 [86223c79] Graphs v1.13.0 [076d061b] HashArrayMappedTries v0.2.0 [34004b35] HypergeometricFunctions v0.3.28 [09f84164] HypothesisTests v0.11.5 [7869d1d1] IRTools v0.4.14 [313cdc1a] Indexing v1.1.1 [d25df0c9] Inflate v0.1.5 [22cec73e] InitialValues v0.3.1 [842dd82b] InlineStrings v1.4.3 [3587e190] InverseFunctions v0.1.17 [41ab1584] InvertedIndices v1.3.1 [92d709cd] IrrationalConstants v0.2.4 [42fd0dbc] IterativeSolvers v0.9.4 [82899510] IteratorInterfaceExtensions v1.0.0 [033835bb] JLD2 v0.5.13 [692b3bcd] JLLWrappers v1.7.0 [682c06a0] JSON v0.21.4 [0f8b85d8] JSON3 v1.14.3 [b14d175d] JuliaVariables v0.2.4 [63c18a36] KernelAbstractions v0.9.34 [b964fa9f] LaTeXStrings v1.4.0 [92ad9a40] LearnAPI v1.0.1 [d3d80556] LineSearches v7.3.0 [7a12625a] LinearMaps v3.11.4 [2ab3a3ac] LogExpFunctions v0.3.29 [c2834f40] MLCore v1.0.0 [a7f614a8] MLJBase v1.8.1 [caf8df21] MLJGLMInterface v0.3.7 [6ee0df7b] MLJLinearModels v0.10.1 [e80e1ace] MLJModelInterface v1.11.1 [d491faf4] MLJModels v0.17.9 [54119dfa] MLJXGBoostInterface v0.3.12 [d8e11817] MLStyle v0.4.17 [f1d291b0] MLUtils v0.4.8 [1914dd2f] MacroTools v0.5.16 [fa8bd995] MetaGraphsNext v0.7.3 [128add7d] MicroCollections v0.2.0 [e1d29d7a] Missings v1.2.0 [d41bc354] NLSolversBase v7.9.1 [872c559c] NNlib v0.9.30 [77ba4419] NaNMath v1.1.3 [71a1bf82] NameResolution v0.1.5 [d9ec5142] NamedTupleTools v0.14.3 [429524aa] Optim v1.12.0 [bac558e1] OrderedCollections v1.8.1 [90014a1f] PDMats v0.11.35 [d96e819e] Parameters v0.12.3 [69de0a69] Parsers v2.8.3 [2dfb63ee] PooledArrays v1.4.3 [85a6dd25] PositiveFactorizations v0.2.4 ⌅ [aea7be01] PrecompileTools v1.2.1 [21216c6a] Preferences v1.4.3 [8162dcfd] PrettyPrint v0.2.0 [54e16d92] PrettyPrinting v0.4.2 [08abe8d2] PrettyTables v2.4.0 [92933f4c] ProgressMeter v1.10.4 [43287f4e] PtrArrays v1.3.0 [1fd47b50] QuadGK v2.11.2 [c1ae055f] RealDot v0.1.0 [3cdcf5f2] RecipesBase v1.3.4 [189a3867] Reexport v1.2.2 [05181044] RelocatableFolders v1.0.1 [ae029012] Requires v1.3.1 [79098fc4] Rmath v0.8.0 [f2b01f46] Roots v2.2.7 [321657f4] ScientificTypes v3.1.0 [30f210dd] ScientificTypesBase v3.0.0 [7e506255] ScopedValues v1.3.0 [6c6a2e73] Scratch v1.2.1 [91c51154] SentinelArrays v1.4.8 [efcf1570] Setfield v1.1.2 [1277b4bf] ShiftedArrays v2.0.0 [605ecd9f] ShowCases v0.1.0 [699a6c99] SimpleTraits v0.9.4 [a2af1166] SortingAlgorithms v1.2.1 [dc90abb0] SparseInverseSubset v0.1.2 [a0a7dd2c] SparseMatricesCSR v0.6.9 [276daf66] SpecialFunctions v2.5.1 [03a91e81] SplitApplyCombine v1.2.3 [171d559e] SplittablesBase v0.1.15 [860ef19b] StableRNGs v1.0.3 [90137ffa] StaticArrays v1.9.13 [1e83bf80] StaticArraysCore v1.4.3 [a19d573c] StatisticalMeasures v0.2.1 [c062fc1d] StatisticalMeasuresBase v0.1.2 [64bff920] StatisticalTraits v3.4.0 [82ae8749] StatsAPI v1.7.1 [2913bbd2] StatsBase v0.34.5 [4c63d2b9] StatsFuns v1.5.0 [3eaba693] StatsModels v0.7.4 [69024149] StringEncodings v0.3.7 [892a3eda] StringManipulation v0.4.1 [09ab397b] StructArrays v0.7.1 [856f2bd8] StructTypes v1.11.0 [8afdd2fb] TMLE v0.19.0 [ab02a1b2] TableOperations v1.2.0 [3783bdb8] TableTraits v1.0.1 [bd369af6] Tables v1.12.1 [3bb67fe8] TranscodingStreams v0.11.3 [28d57a85] Transducers v0.4.84 [3a884ed6] UnPack v1.0.2 [013be700] UnsafeAtomics v0.3.0 [ea10d353] WeakRefStrings v1.4.2 [76eceee3] WorkerUtilities v1.6.1 [009559a3] XGBoost v2.5.1 [ddb6d928] YAML v0.4.14 [e88e6eb3] Zygote v0.7.8 [700de1a5] ZygoteRules v0.2.7 [4ee394cb] CUDA_Driver_jll v0.13.0+0 [76a88914] CUDA_Runtime_jll v0.17.0+0 [1d63c593] LLVMOpenMP_jll v18.1.8+0 [94ce4f54] Libiconv_jll v1.18.0+0 [efe28fd5] OpenSpecFun_jll v0.5.6+0 [f50d1b31] Rmath_jll v0.5.1+0 [a5c6f535] XGBoost_jll v2.0.1+0 [0dad84c5] ArgTools v1.1.1 [56f22d72] Artifacts [2a0f44e3] Base64 [ade2ca70] Dates [8ba89e20] Distributed [f43a241f] Downloads v1.6.0 [7b1f6079] FileWatching [9fa8497b] Future [b77e0a4c] InteractiveUtils [4af54fe1] LazyArtifacts [b27032c2] LibCURL v0.6.4 [76f85450] LibGit2 [8f399da3] Libdl [37e2e46d] LinearAlgebra [56ddb016] Logging [d6f4376e] Markdown [a63ad114] Mmap [ca575930] NetworkOptions v1.2.0 [44cfe95a] Pkg v1.10.0 [de0858da] Printf [3fa0cd96] REPL [9a3f8284] Random [ea8e919c] SHA v0.7.0 [9e88b42a] Serialization [1a1011a3] SharedArrays [6462fe0b] Sockets [2f01184e] SparseArrays v1.10.0 [10745b16] Statistics v1.10.0 [4607b0f0] SuiteSparse [fa267f1f] TOML v1.0.3 [a4e569a6] Tar v1.10.0 [8dfed614] Test [cf7118a7] UUIDs [4ec0a83e] Unicode [e66e0078] CompilerSupportLibraries_jll v1.1.1+0 [deac9b47] LibCURL_jll v8.4.0+0 [e37daf67] LibGit2_jll v1.6.4+0 [29816b5a] LibSSH2_jll v1.11.0+1 [c8ffd9c3] MbedTLS_jll v2.28.2+1 [14a3606d] MozillaCACerts_jll v2023.1.10 [4536629a] OpenBLAS_jll v0.3.23+4 [05823500] OpenLibm_jll v0.8.5+0 [bea87d4a] SuiteSparse_jll v7.2.1+1 [83775a58] Zlib_jll v1.2.13+1 [8e850b90] libblastrampoline_jll v5.11.0+0 [8e850ede] nghttp2_jll v1.52.0+1 [3f19e933] p7zip_jll v17.4.0+2 Info Packages marked with ⌅ have new versions available but compatibility constraints restrict them from upgrading. Testing Running tests... Test Summary: | Pass Total Time Test expected_value | 3 3 1m01.3s Test Summary: | Pass Total Time Test counterfactualTreatment | 3 3 8.0s Test Summary: | Pass Total Time Test positivity_constraint & get_frequency_table | 28 28 13.5s Test Summary: | Pass Total Time Test selectcols | 5 5 1.1s Test Summary: | Pass Total Time Test SCM | 17 17 2.6s Test Summary: | Pass Total Time Test StaticSCM | 9 9 0.2s Test Summary: | Pass Total Time Test BackdoorAdjustment | 16 16 3.7s Test Summary: | Pass Total Time Test TMLE.to_dict | 2 2 0.4s Test Summary: | Pass Total Time Test ConditionalDistribution | 3 3 0.3s Test Summary: | Pass Total Time Test CMRelevantFactors | 2 2 0.5s Test Summary: | Pass Total Time Test JointEstimand and ComposedEstimand | 5 5 5.6s Test Summary: | Pass Total Time Test MLConditionalDistributionEstimator: binary outcome | 9 9 27.4s Test Summary: | Pass Total Time Test MLConditionalDistributionEstimator: continuous outcome | 7 7 8.3s Test Summary: | Pass Total Time Test SampleSplitMLConditionalDistributionEstimator: Binary outcome | 13 13 6.0s Test Summary: | Pass Total Time Test SampleSplitMLConditionalDistributionEstimator: Continuous outcome | 7 7 0.7s Test Summary: | Pass Total Time Test Conditional Distribution with no parents fits a marginal | 3 3 1.4s Test Summary: | Pass Total Time Test nomissing | 5 5 4.7s Test Summary: | Pass Total Time Test estimation with missing values and ordered factor treatment | 2 2 1m16.6s Test Summary: | Pass Total Time Test cov | 2 2 5.1s Test Summary: | Pass Total Time Test composition CM(1) - CM(0) = ATE(1,0) | 8 8 52.1s Test Summary: | Pass Total Time Test compose multidimensional function | 8 8 2.8s Test Summary: | Pass Total Time Test Joint Interaction | 19 19 34.5s Test Summary: | Pass Total Time Test CausalStratifiedCV | 8 8 3.7s WARNING: replacing module TestEstimands. Test Summary: | Pass Total Time Test StatisticalCMCompositeEstimand | 10 10 5.6s Test Summary: | Pass Total Time Test standardization of StatisticalCMCompositeEstimand | 10 10 2.1s Test Summary: | Pass Total Time Test structs are concrete types | 3 3 0.0s Test Summary: | Pass Total Time Test dictionary conversion | 8 8 6.9s Test Summary: | Pass Total Time Test control_case_settings | 6 6 5.7s Test Summary: | Pass Total Time Test unique_treatment_values | 2 2 5.4s Test Summary: | Pass Total Time factorialEstimand errors | 2 2 1.8s Test Summary: | Pass Total Time Test factorial CM | 2 2 2.5s Test Summary: | Pass Total Time Test factorial ATE | 4 4 5.4s Test Summary: | Pass Total Time Test factorial AIE | 3 3 3.1s Test Summary: | Pass Total Time Test factorialEstimands | 2 2 0.1s Test Summary: | Pass Total Time Test ps_lower_bound | 5 5 0.1s Test Summary: | Pass Total Time Test clever_covariate_and_weights: 1 treatment | 4 4 10.6s Test Summary: | Pass Total Time Test clever_covariate_and_weights: 2 treatments | 2 2 0.2s Test Summary: | Pass Total Time Test compute_offset, clever_covariate_and_weights: 3 treatments | 2 2 11.7s Test Summary: | Pass Total Time Test gradient_and_plugin_estimate | 5 5 15.5s Test Summary: | Pass Total Time Test Fluctuation with 1 Treatments | 21 21 6.6s Test Summary: | Pass Total Time Test Fluctuation with 2 Treatments | 11 11 6.1s Test Summary: | Pass Total Time Test same_type_nt | 6 6 0.5s ┌ Warning: `TMLEE(args...; kwargs...)` is deprecated, use `Tmle(args...; kwargs...)` instead. │ caller = macro expansion at Test.jl:669 [inlined] └ @ Core /opt/julia/share/julia/stdlib/v1.10/Test/src/Test.jl:669 ┌ Warning: `OSE(args...; kwargs...)` is deprecated, use `Ose(args...; kwargs...)` instead. │ caller = macro expansion at Test.jl:669 [inlined] └ @ Core /opt/julia/share/julia/stdlib/v1.10/Test/src/Test.jl:669 ┌ Warning: `NAIVE(args...; kwargs...)` is deprecated, use `Plugin(args...; kwargs...)` instead. │ caller = macro expansion at Test.jl:669 [inlined] └ @ Core /opt/julia/share/julia/stdlib/v1.10/Test/src/Test.jl:669 Test Summary: | Pass Total Time Deprecation | 3 3 4.4s Test Summary: | Pass Total Time Test CMRelevantFactorsEstimator | 11 11 5.4s ┌ Warning: The number and/or types of data arguments do not match what the specified model │ supports. Suppress this type check by specifying `scitype_check_level=0`. │ │ Run `@doc MLJLinearModels.LinearRegressor` to learn more about your model's requirements. │ │ Commonly, but non exclusively, supervised models are constructed using the syntax │ `machine(model, X, y)` or `machine(model, X, y, w)` while most other models are │ constructed with `machine(model, X)`. Here `X` are features, `y` a target, and `w` │ sample or class weights. │ │ In general, data in `machine(model, data...)` is expected to satisfy │ │ scitype(data) <: MLJ.fit_data_scitype(model) │ │ In the present case: │ │ scitype(data) = Tuple{ScientificTypesBase.Table{AbstractVector{ScientificTypesBase.Continuous}}, AbstractVector{ScientificTypesBase.OrderedFactor{2}}} │ │ fit_data_scitype(model) = Tuple{ScientificTypesBase.Table{<:AbstractVector{<:ScientificTypesBase.Continuous}}, AbstractVector{ScientificTypesBase.Continuous}} └ @ MLJBase ~/.julia/packages/MLJBase/F1Eh6/src/machines.jl:237 ┌ Error: Problem fitting the machine machine(LinearRegressor(fit_intercept = true, …), …). └ @ MLJBase ~/.julia/packages/MLJBase/F1Eh6/src/machines.jl:694 [ Info: Running type checks... ┌ Warning: The number and/or types of data arguments do not match what the specified model │ supports. Suppress this type check by specifying `scitype_check_level=0`. │ │ Run `@doc MLJLinearModels.LinearRegressor` to learn more about your model's requirements. │ │ Commonly, but non exclusively, supervised models are constructed using the syntax │ `machine(model, X, y)` or `machine(model, X, y, w)` while most other models are │ constructed with `machine(model, X)`. Here `X` are features, `y` a target, and `w` │ sample or class weights. │ │ In general, data in `machine(model, data...)` is expected to satisfy │ │ scitype(data) <: MLJ.fit_data_scitype(model) │ │ In the present case: │ │ scitype(data) = Tuple{ScientificTypesBase.Table{AbstractVector{ScientificTypesBase.Continuous}}, AbstractVector{ScientificTypesBase.OrderedFactor{2}}} │ │ fit_data_scitype(model) = Tuple{ScientificTypesBase.Table{<:AbstractVector{<:ScientificTypesBase.Continuous}}, AbstractVector{ScientificTypesBase.Continuous}} └ @ MLJBase ~/.julia/packages/MLJBase/F1Eh6/src/machines.jl:237 [ Info: It seems an upstream node in a learning network is providing data of incompatible scitype. See above. ┌ Warning: The number and/or types of data arguments do not match what the specified model │ supports. Suppress this type check by specifying `scitype_check_level=0`. │ │ Run `@doc MLJLinearModels.LogisticClassifier` to learn more about your model's requirements. │ │ Commonly, but non exclusively, supervised models are constructed using the syntax │ `machine(model, X, y)` or `machine(model, X, y, w)` while most other models are │ constructed with `machine(model, X)`. Here `X` are features, `y` a target, and `w` │ sample or class weights. │ │ In general, data in `machine(model, data...)` is expected to satisfy │ │ scitype(data) <: MLJ.fit_data_scitype(model) │ │ In the present case: │ │ scitype(data) = Tuple{ScientificTypesBase.Table{Union{AbstractVector{ScientificTypesBase.Continuous}, AbstractVector{ScientificTypesBase.OrderedFactor{2}}}}, AbstractVector{ScientificTypesBase.Continuous}} │ │ fit_data_scitype(model) = Tuple{ScientificTypesBase.Table{<:AbstractVector{<:ScientificTypesBase.Continuous}}, AbstractVector{<:ScientificTypesBase.Finite}} └ @ MLJBase ~/.julia/packages/MLJBase/F1Eh6/src/machines.jl:237 ┌ Error: Problem fitting the machine machine(LogisticClassifier(lambda = 2.220446049250313e-16, …), …). └ @ MLJBase ~/.julia/packages/MLJBase/F1Eh6/src/machines.jl:694 [ Info: Running type checks... ┌ Warning: The number and/or types of data arguments do not match what the specified model │ supports. Suppress this type check by specifying `scitype_check_level=0`. │ │ Run `@doc MLJLinearModels.LogisticClassifier` to learn more about your model's requirements. │ │ Commonly, but non exclusively, supervised models are constructed using the syntax │ `machine(model, X, y)` or `machine(model, X, y, w)` while most other models are │ constructed with `machine(model, X)`. Here `X` are features, `y` a target, and `w` │ sample or class weights. │ │ In general, data in `machine(model, data...)` is expected to satisfy │ │ scitype(data) <: MLJ.fit_data_scitype(model) │ │ In the present case: │ │ scitype(data) = Tuple{ScientificTypesBase.Table{Union{AbstractVector{ScientificTypesBase.Continuous}, AbstractVector{ScientificTypesBase.OrderedFactor{2}}}}, AbstractVector{ScientificTypesBase.Continuous}} │ │ fit_data_scitype(model) = Tuple{ScientificTypesBase.Table{<:AbstractVector{<:ScientificTypesBase.Continuous}}, AbstractVector{<:ScientificTypesBase.Finite}} └ @ MLJBase ~/.julia/packages/MLJBase/F1Eh6/src/machines.jl:237 [ Info: It seems an upstream node in a learning network is providing data of incompatible scitype. See above. [ Info: Estimating nuisance parameters. [ Info: Estimating: P₀(G25 Other extrapyramidal and movement disorders | 2:14983:G:A, PC1, PC2, PC3, PC4, PC5, PC6) ┌ Error: Problem fitting the machine machine(LinearBinaryClassifier(fit_intercept = false, …), …). └ @ MLJBase ~/.julia/packages/MLJBase/F1Eh6/src/machines.jl:694 [ Info: Running type checks... [ Info: Type checks okay. ┌ Error: Problem fitting the machine machine(Fluctuation(Ψ = TMLE.StatisticalATE(Symbol("G25 Other extrapyramidal and movement disorders"), OrderedCollections.OrderedDict{Symbol, @NamedTuple{control::String, case::String}}(Symbol("2:14983:G:A") => (control = "AG", case = "GG")), OrderedCollections.OrderedDict(Symbol("2:14983:G:A") => (:PC1, :PC2, :PC3, :PC4, :PC5, :PC6)), ()), …), …). └ @ MLJBase ~/.julia/packages/MLJBase/F1Eh6/src/machines.jl:694 [ Info: Running type checks... [ Info: Type checks okay. Test Summary: | Pass Total Time Test FitFailedError | 6 6 52.2s Test Summary: | Pass Total Time Test structs are concrete types | 3 3 0.0s Test Summary: | Pass Total Time Test ATE on perinatal dataset. | 13 13 24.4s Test Summary: | Pass Total Time Test accelerations | 6 6 33.9s Test Summary: | Pass Total Time Test Double Robustness ATE on continuous_outcome_categorical_treatment_pb | 19 19 20.3s Test Summary: | Pass Total Time Test Double Robustness ATE on binary_outcome_binary_treatment_pb | 16 16 15.1s Test Summary: | Pass Total Time Test Double Robustness ATE on continuous_outcome_binary_treatment_pb | 16 16 19.5s Test Summary: | Pass Total Time Test Double Robustness ATE with two treatment variables | 30 30 51.9s Test Summary: | Pass Total Time Test Double Robustness AIE on binary_outcome_binary_treatment_pb | 18 18 45.5s Test Summary: | Pass Total Time Test Double Robustness AIE on continuous_outcome_binary_treatment_pb | 16 16 17.2s Test Summary: | Pass Total Time Test Double Robustness AIE on binary_outcome_categorical_treatment_pb | 18 18 2m14.2s ┌ Warning: The number and/or types of data arguments do not match what the specified model │ supports. Suppress this type check by specifying `scitype_check_level=0`. │ │ Run `@doc MLJLinearModels.LogisticClassifier` to learn more about your model's requirements. │ │ Commonly, but non exclusively, supervised models are constructed using the syntax │ `machine(model, X, y)` or `machine(model, X, y, w)` while most other models are │ constructed with `machine(model, X)`. Here `X` are features, `y` a target, and `w` │ sample or class weights. │ │ In general, data in `machine(model, data...)` is expected to satisfy │ │ scitype(data) <: MLJ.fit_data_scitype(model) │ │ In the present case: │ │ scitype(data) = Tuple{ScientificTypesBase.Table{Union{AbstractVector{ScientificTypesBase.Continuous}, AbstractVector{ScientificTypesBase.Multiclass{2}}}}, AbstractVector{ScientificTypesBase.Multiclass{2}}} │ │ fit_data_scitype(model) = Tuple{ScientificTypesBase.Table{<:AbstractVector{<:ScientificTypesBase.Continuous}}, AbstractVector{<:ScientificTypesBase.Finite}} └ @ MLJBase ~/.julia/packages/MLJBase/F1Eh6/src/machines.jl:237 ┌ Warning: The number and/or types of data arguments do not match what the specified model │ supports. Suppress this type check by specifying `scitype_check_level=0`. │ │ Run `@doc MLJLinearModels.LogisticClassifier` to learn more about your model's requirements. │ │ Commonly, but non exclusively, supervised models are constructed using the syntax │ `machine(model, X, y)` or `machine(model, X, y, w)` while most other models are │ constructed with `machine(model, X)`. Here `X` are features, `y` a target, and `w` │ sample or class weights. │ │ In general, data in `machine(model, data...)` is expected to satisfy │ │ scitype(data) <: MLJ.fit_data_scitype(model) │ │ In the present case: │ │ scitype(data) = Tuple{ScientificTypesBase.Table{Union{AbstractVector{ScientificTypesBase.Continuous}, AbstractVector{ScientificTypesBase.Multiclass{2}}}}, AbstractVector{ScientificTypesBase.Multiclass{2}}} │ │ fit_data_scitype(model) = Tuple{ScientificTypesBase.Table{<:AbstractVector{<:ScientificTypesBase.Continuous}}, AbstractVector{<:ScientificTypesBase.Finite}} └ @ MLJBase ~/.julia/packages/MLJBase/F1Eh6/src/machines.jl:237 ┌ Warning: The number and/or types of data arguments do not match what the specified model │ supports. Suppress this type check by specifying `scitype_check_level=0`. │ │ Run `@doc MLJLinearModels.LogisticClassifier` to learn more about your model's requirements. │ │ Commonly, but non exclusively, supervised models are constructed using the syntax │ `machine(model, X, y)` or `machine(model, X, y, w)` while most other models are │ constructed with `machine(model, X)`. Here `X` are features, `y` a target, and `w` │ sample or class weights. │ │ In general, data in `machine(model, data...)` is expected to satisfy │ │ scitype(data) <: MLJ.fit_data_scitype(model) │ │ In the present case: │ │ scitype(data) = Tuple{ScientificTypesBase.Table{Union{AbstractVector{ScientificTypesBase.Continuous}, AbstractVector{ScientificTypesBase.Multiclass{2}}}}, AbstractVector{ScientificTypesBase.Multiclass{2}}} │ │ fit_data_scitype(model) = Tuple{ScientificTypesBase.Table{<:AbstractVector{<:ScientificTypesBase.Continuous}}, AbstractVector{<:ScientificTypesBase.Finite}} └ @ MLJBase ~/.julia/packages/MLJBase/F1Eh6/src/machines.jl:237 ┌ Warning: The number and/or types of data arguments do not match what the specified model │ supports. Suppress this type check by specifying `scitype_check_level=0`. │ │ Run `@doc MLJLinearModels.LogisticClassifier` to learn more about your model's requirements. │ │ Commonly, but non exclusively, supervised models are constructed using the syntax │ `machine(model, X, y)` or `machine(model, X, y, w)` while most other models are │ constructed with `machine(model, X)`. Here `X` are features, `y` a target, and `w` │ sample or class weights. │ │ In general, data in `machine(model, data...)` is expected to satisfy │ │ scitype(data) <: MLJ.fit_data_scitype(model) │ │ In the present case: │ │ scitype(data) = Tuple{ScientificTypesBase.Table{Union{AbstractVector{ScientificTypesBase.Continuous}, AbstractVector{ScientificTypesBase.Multiclass{2}}}}, AbstractVector{ScientificTypesBase.Multiclass{2}}} │ │ fit_data_scitype(model) = Tuple{ScientificTypesBase.Table{<:AbstractVector{<:ScientificTypesBase.Continuous}}, AbstractVector{<:ScientificTypesBase.Finite}} └ @ MLJBase ~/.julia/packages/MLJBase/F1Eh6/src/machines.jl:237 Test Summary: | Pass Total Time Test 3-points interactions | 12 12 10.3s Test Summary: | Pass Total Time Test compute_loss | 5 5 3.3s WARNING: replacing module TestCollaborative. Test Summary: | Pass Total Time Test AdaptiveCorrelationStrategy Interface | 19 19 15.1s Test Summary: | Pass Total Time Test GreedyStrategy Interface | 13 13 13.1s Test Summary: | Pass Total Time Integration Test using the AdaptiveCorrelationStrategy | 122 122 4.1s Test Summary: | Pass Total Time Test Configurations | 8 8 2.6s Test Summary: | Pass Total Time Test with an SCM and causal estimands | 6 6 0.9s Test Summary: | Pass Total Time Test serialization | 3 3 3.1s Test Summary: | Pass Total Time Fit TMLE and OSE on CausalTable | 2 2 10.3s Test Summary: | Pass Total Time Test misc | 127 127 13.2s Test Summary: | Pass Total Time Test ordering strategies | 8 8 2.5s Test Summary: | Pass Total Time Test ordering strategies with Joint Estimands | 4 4 2.8s 1006.286788 seconds (1.24 G allocations: 75.222 GiB, 3.22% gc time, 70.97% compilation time: 1% of which was recompilation) Testing TMLE tests passed Testing completed after 1030.36s PkgEval succeeded after 2473.97s