Package evaluation of ArviZPythonPlots on Julia 1.13.0-DEV.140 (fac1ce7906*) started at 2025-03-02T15:41:56.622 ################################################################################ # Set-up # Installing PkgEval dependencies (TestEnv)... Set-up completed after 7.96s ################################################################################ # Installation # Installing ArviZPythonPlots... Resolving package versions... Updating `~/.julia/environments/v1.13/Project.toml` [4a6e88f0] + ArviZPythonPlots v0.1.7 Updating `~/.julia/environments/v1.13/Manifest.toml` [621f4979] + AbstractFFTs v1.5.0 [79e6a3ab] + Adapt v4.2.0 [66dad0bd] + AliasTables v1.1.3 [4fba245c] + ArrayInterface v7.18.0 [131c737c] + ArviZ v0.12.0 [4a6e88f0] + ArviZPythonPlots v0.1.7 [3da002f7] + ColorTypes v0.12.0 [5ae59095] + Colors v0.13.0 [bbf7d656] + CommonSubexpressions v0.3.1 [34da2185] + Compat v4.16.0 [992eb4ea] + CondaPkg v0.2.25 [187b0558] + ConstructionBase v1.5.8 [a8cc5b0e] + Crayons v4.1.1 [9a962f9c] + DataAPI v1.16.0 ⌅ [82cc6244] + DataInterpolations v6.6.0 [864edb3b] + DataStructures v0.18.20 [e2d170a0] + DataValueInterfaces v1.0.0 [163ba53b] + DiffResults v1.1.0 [b552c78f] + DiffRules v1.15.1 ⌅ [0703355e] + DimensionalData v0.27.9 [31c24e10] + Distributions v0.25.117 [ffbed154] + DocStringExtensions v0.9.3 [411431e0] + Extents v0.1.5 [1a297f60] + FillArrays v1.13.0 [64ca27bc] + FindFirstFunctions v1.4.1 [6a86dc24] + FiniteDiff v2.27.0 [53c48c17] + FixedPointNumbers v0.8.5 [f6369f11] + ForwardDiff v0.10.38 [34004b35] + HypergeometricFunctions v0.3.27 [b5cf5a8d] + InferenceObjects v0.4.9 [85a1e053] + Interfaces v0.3.2 [8197267c] + IntervalSets v0.7.10 [41ab1584] + InvertedIndices v1.3.1 [92d709cd] + IrrationalConstants v0.2.4 [82899510] + IteratorInterfaceExtensions v1.0.0 [692b3bcd] + JLLWrappers v1.7.0 [0f8b85d8] + JSON3 v1.14.1 [b964fa9f] + LaTeXStrings v1.4.0 [d3d80556] + LineSearches v7.3.0 [2ab3a3ac] + LogExpFunctions v0.3.29 [be115224] + MCMCDiagnosticTools v0.3.14 [e80e1ace] + MLJModelInterface v1.11.0 [1914dd2f] + MacroTools v0.5.15 [0b3b1443] + MicroMamba v0.1.14 [e1d29d7a] + Missings v1.2.0 [d41bc354] + NLSolversBase v7.8.3 [77ba4419] + NaNMath v1.1.2 [429524aa] + Optim v1.11.0 [bac558e1] + OrderedCollections v1.8.0 [90014a1f] + PDMats v0.11.32 [ce719bf2] + PSIS v0.9.7 [d96e819e] + Parameters v0.12.3 [69de0a69] + Parsers v2.8.1 [fa939f87] + Pidfile v1.3.0 [85a6dd25] + PositiveFactorizations v0.2.4 [7f36be82] + PosteriorStats v0.2.5 [aea7be01] + PrecompileTools v1.2.1 [21216c6a] + Preferences v1.4.3 [08abe8d2] + PrettyTables v2.4.0 [43287f4e] + PtrArrays v1.3.0 [6099a3de] + PythonCall v0.9.24 [274fc56d] + PythonPlot v1.0.6 [1fd47b50] + QuadGK v2.11.2 [3cdcf5f2] + RecipesBase v1.3.4 [189a3867] + Reexport v1.2.2 [ae029012] + Requires v1.3.1 [79098fc4] + Rmath v0.8.0 [30f210dd] + ScientificTypesBase v3.0.0 [6c6a2e73] + Scratch v1.2.1 [91c51154] + SentinelArrays v1.4.8 [efcf1570] + Setfield v1.1.2 [a2af1166] + SortingAlgorithms v1.2.1 [276daf66] + SpecialFunctions v2.5.0 [1e83bf80] + StaticArraysCore v1.4.3 [64bff920] + StatisticalTraits v3.4.0 [10745b16] + Statistics v1.11.1 [82ae8749] + StatsAPI v1.7.0 ⌅ [2913bbd2] + StatsBase v0.33.21 [4c63d2b9] + StatsFuns v1.3.2 [892a3eda] + StringManipulation v0.4.1 [856f2bd8] + StructTypes v1.11.0 [ab02a1b2] + TableOperations v1.2.0 [3783bdb8] + TableTraits v1.0.1 [bd369af6] + Tables v1.12.0 [3a884ed6] + UnPack v1.0.2 [e17b2a0c] + UnsafePointers v1.0.0 [81def892] + VersionParsing v1.3.0 [efe28fd5] + OpenSpecFun_jll v0.5.6+0 [f50d1b31] + Rmath_jll v0.5.1+0 [f8abcde7] + micromamba_jll v1.5.8+0 [4d7b5844] + pixi_jll v0.41.3+0 [0dad84c5] + ArgTools v1.1.2 [56f22d72] + Artifacts v1.11.0 [2a0f44e3] + Base64 v1.11.0 [ade2ca70] + Dates v1.11.0 [8ba89e20] + Distributed v1.11.0 [f43a241f] + Downloads v1.7.0 [7b1f6079] + FileWatching v1.11.0 [9fa8497b] + Future v1.11.0 [b77e0a4c] + InteractiveUtils v1.11.0 [ac6e5ff7] + JuliaSyntaxHighlighting v1.12.0 [4af54fe1] + LazyArtifacts v1.11.0 [b27032c2] + LibCURL v0.6.4 [76f85450] + LibGit2 v1.11.0 [8f399da3] + Libdl v1.11.0 [37e2e46d] + LinearAlgebra v1.12.0 [56ddb016] + Logging v1.11.0 [d6f4376e] + Markdown v1.11.0 [a63ad114] + Mmap v1.11.0 [ca575930] + NetworkOptions v1.3.0 [44cfe95a] + Pkg v1.12.0 [de0858da] + Printf v1.11.0 [9a3f8284] + Random v1.11.0 [ea8e919c] + SHA v0.7.0 [9e88b42a] + Serialization v1.11.0 [6462fe0b] + Sockets v1.11.0 [2f01184e] + SparseArrays v1.12.0 [f489334b] + StyledStrings v1.11.0 [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 v1.3.0+1 [deac9b47] + LibCURL_jll v8.11.1+1 [e37daf67] + LibGit2_jll v1.9.0+0 [29816b5a] + LibSSH2_jll v1.11.3+1 [14a3606d] + MozillaCACerts_jll v2024.12.31 [4536629a] + OpenBLAS_jll v0.3.29+0 [05823500] + OpenLibm_jll v0.8.5+0 [458c3c95] + OpenSSL_jll v3.0.16+0 [bea87d4a] + SuiteSparse_jll v7.8.3+2 [83775a58] + Zlib_jll v1.3.1+2 [8e850b90] + libblastrampoline_jll v5.12.0+0 [8e850ede] + nghttp2_jll v1.64.0+1 [3f19e933] + p7zip_jll v17.5.0+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 4.95s ################################################################################ # Precompilation # Precompiling PkgEval dependencies... Precompiling package dependencies... Precompilation completed after 507.3s ################################################################################ # Testing # Testing ArviZPythonPlots Status `/tmp/jl_x2wqV8/Project.toml` [131c737c] ArviZ v0.12.0 [2f96bb34] ArviZExampleData v0.1.12 [4a6e88f0] ArviZPythonPlots v0.1.7 [992eb4ea] CondaPkg v0.2.25 ⌅ [0703355e] DimensionalData v0.27.9 [bac558e1] OrderedCollections v1.8.0 [6099a3de] PythonCall v0.9.24 [274fc56d] PythonPlot v1.0.6 [189a3867] Reexport v1.2.2 [bd369af6] Tables v1.12.0 [d6f4376e] Markdown v1.11.0 [9a3f8284] Random v1.11.0 [8dfed614] Test v1.11.0 Status `/tmp/jl_x2wqV8/Manifest.toml` [621f4979] AbstractFFTs v1.5.0 [79e6a3ab] Adapt v4.2.0 [66dad0bd] AliasTables v1.1.3 [4fba245c] ArrayInterface v7.18.0 [131c737c] ArviZ v0.12.0 [2f96bb34] ArviZExampleData v0.1.12 [4a6e88f0] ArviZPythonPlots v0.1.7 [d1d4a3ce] BitFlags v0.1.9 [179af706] CFTime v0.1.4 [944b1d66] CodecZlib v0.7.8 [3da002f7] ColorTypes v0.12.0 [5ae59095] Colors v0.13.0 [1fbeeb36] CommonDataModel 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[8e850ede] nghttp2_jll v1.64.0+1 [3f19e933] p7zip_jll v17.5.0+2 Info Packages marked with ⌅ have new versions available but compatibility constraints restrict them from upgrading. Testing Running tests... Precompiling packages... Info Given ArviZPythonPlots was explicitly requested, output will be shown live   CondaPkg Found dependencies: /home/pkgeval/.julia/packages/PythonCall/WMWY0/CondaPkg.toml  CondaPkg Found dependencies: /home/pkgeval/.julia/packages/ArviZPythonPlots/2sLLG/CondaPkg.toml  CondaPkg Found dependencies: /home/pkgeval/.julia/packages/PythonPlot/oS8x4/CondaPkg.toml  CondaPkg Resolving changes  + arviz  + libstdcxx-ng  + matplotlib  + openssl  + pandas  + python  + xarray  CondaPkg Initialising pixi  │ /home/pkgeval/.julia/artifacts/cefba4912c2b400756d043a2563ef77a0088866b/bin/pixi  │ init  │ --format pixi  └ /tmp/jl_x2wqV8/.CondaPkg ✔ Created /tmp/jl_x2wqV8/.CondaPkg/pixi.toml  CondaPkg Wrote /tmp/jl_x2wqV8/.CondaPkg/pixi.toml  │ [dependencies]  │ openssl = ">=3, <3.1"  │ libstdcxx-ng = ">=3.4,<13.0"  │ matplotlib = ">=1"  │ pandas = "*"  │ xarray = "*"  │ arviz = ">=0.15.0,<0.16.0"  │  │ [dependencies.python]  │ channel = "conda-forge"  │ build = "*cpython*"  │ version = ">=3.8,<4"  │  │ [project]  │ name = ".CondaPkg"  │ platforms = ["linux-64"]  │ channels = ["conda-forge"]  │ channel-priority = "disabled"  └ description = "automatically generated by CondaPkg.jl"  CondaPkg Installing packages  │ /home/pkgeval/.julia/artifacts/cefba4912c2b400756d043a2563ef77a0088866b/bin/pixi  │ install  └ --manifest-path /tmp/jl_x2wqV8/.CondaPkg/pixi.toml ✔ The default environment has been installed. 72928.7 ms ✓ ArviZPythonPlots 1 dependency successfully precompiled in 76 seconds. 147 already precompiled. 1 dependency had output during precompilation: ┌ ArviZPythonPlots │ [Output was shown above] └ Precompiling packages... 8480.2 ms ✓ Distributions → DistributionsTestExt 1 dependency successfully precompiled in 10 seconds. 55 already precompiled. Precompiling packages... 6732.6 ms ✓ MPItrampoline_jll 6623.4 ms ✓ OpenMPI_jll 7640.8 ms ✓ DataDeps 18664.8 ms ✓ ArviZExampleData 4 dependencies successfully precompiled in 40 seconds. 106 already precompiled. ┌ Warning: 2 parameters had Pareto shape values 0.7 < k ≤ 1. Resulting importance sampling estimates are likely to be unstable. └ @ PSIS ~/.julia/packages/PSIS/fU76x/src/core.jl:373 /tmp/jl_x2wqV8/.CondaPkg/.pixi/envs/default/lib/python3.11/site-packages/arviz/stats/stats.py:803: UserWarning: Estimated shape parameter of Pareto distribution is greater than 0.7 for one or more samples. You should consider using a more robust model, this is because importance sampling is less likely to work well if the marginal posterior and LOO posterior are very different. This is more likely to happen with a non-robust model and highly influential observations. warnings.warn( /tmp/jl_x2wqV8/.CondaPkg/.pixi/envs/default/lib/python3.11/site-packages/arviz/plots/pairplot.py:232: FutureWarning: The return type of `Dataset.dims` will be changed to return a set of dimension names in future, in order to be more consistent with `DataArray.dims`. To access a mapping from dimension names to lengths, please use `Dataset.sizes`. gridsize = int(dataset.dims["draw"] ** 0.35) /tmp/jl_x2wqV8/.CondaPkg/.pixi/envs/default/lib/python3.11/site-packages/arviz/plots/essplot.py:205: FutureWarning: The return type of `Dataset.dims` will be changed to return a set of dimension names in future, in order to be more consistent with `DataArray.dims`. To access a mapping from dimension names to lengths, please use `Dataset.sizes`. n_draws = data.dims["draw"] /tmp/jl_x2wqV8/.CondaPkg/.pixi/envs/default/lib/python3.11/site-packages/arviz/plots/essplot.py:206: FutureWarning: The return type of `Dataset.dims` will be changed to return a set of dimension names in future, in order to be more consistent with `DataArray.dims`. To access a mapping from dimension names to lengths, please use `Dataset.sizes`. n_samples = n_draws * data.dims["chain"] /tmp/jl_x2wqV8/.CondaPkg/.pixi/envs/default/lib/python3.11/site-packages/arviz/plots/essplot.py:205: FutureWarning: The return type of `Dataset.dims` will be changed to return a set of dimension names in future, in order to be more consistent with `DataArray.dims`. To access a mapping from dimension names to lengths, please use `Dataset.sizes`. n_draws = data.dims["draw"] /tmp/jl_x2wqV8/.CondaPkg/.pixi/envs/default/lib/python3.11/site-packages/arviz/plots/essplot.py:206: FutureWarning: The return type of `Dataset.dims` will be changed to return a set of dimension names in future, in order to be more consistent with `DataArray.dims`. To access a mapping from dimension names to lengths, please use `Dataset.sizes`. n_samples = n_draws * data.dims["chain"] /tmp/jl_x2wqV8/.CondaPkg/.pixi/envs/default/lib/python3.11/site-packages/arviz/plots/essplot.py:205: FutureWarning: The return type of `Dataset.dims` will be changed to return a set of dimension names in future, in order to be more consistent with `DataArray.dims`. To access a mapping from dimension names to lengths, please use `Dataset.sizes`. n_draws = data.dims["draw"] /tmp/jl_x2wqV8/.CondaPkg/.pixi/envs/default/lib/python3.11/site-packages/arviz/plots/essplot.py:206: FutureWarning: The return type of `Dataset.dims` will be changed to return a set of dimension names in future, in order to be more consistent with `DataArray.dims`. To access a mapping from dimension names to lengths, please use `Dataset.sizes`. n_samples = n_draws * data.dims["chain"] /tmp/jl_x2wqV8/.CondaPkg/.pixi/envs/default/lib/python3.11/site-packages/arviz/plots/bpvplot.py:228: FutureWarning: The return type of `Dataset.dims` will be changed to return a set of dimension names in future, in order to be more consistent with `DataArray.dims`. To access a mapping from dimension names to lengths, please use `Dataset.sizes`. flatten_pp = list(predictive_dataset.dims.keys()) /tmp/jl_x2wqV8/.CondaPkg/.pixi/envs/default/lib/python3.11/site-packages/arviz/plots/bpvplot.py:232: FutureWarning: The return type of `Dataset.dims` will be changed to return a set of dimension names in future, in order to be more consistent with `DataArray.dims`. To access a mapping from dimension names to lengths, please use `Dataset.sizes`. flatten = list(observed.dims.keys()) /tmp/jl_x2wqV8/.CondaPkg/.pixi/envs/default/lib/python3.11/site-packages/arviz/plots/bpvplot.py:228: FutureWarning: The return type of `Dataset.dims` will be changed to return a set of dimension names in future, in order to be more consistent with `DataArray.dims`. To access a mapping from dimension names to lengths, please use `Dataset.sizes`. flatten_pp = list(predictive_dataset.dims.keys()) /tmp/jl_x2wqV8/.CondaPkg/.pixi/envs/default/lib/python3.11/site-packages/arviz/plots/bpvplot.py:232: FutureWarning: The return type of `Dataset.dims` will be changed to return a set of dimension names in future, in order to be more consistent with `DataArray.dims`. To access a mapping from dimension names to lengths, please use `Dataset.sizes`. flatten = list(observed.dims.keys()) ┌ Warning: 1 parameters had Pareto shape values 0.7 < k ≤ 1. Resulting importance sampling estimates are likely to be unstable. └ @ PSIS ~/.julia/packages/PSIS/fU76x/src/core.jl:373 /tmp/jl_x2wqV8/.CondaPkg/.pixi/envs/default/lib/python3.11/site-packages/arviz/plots/backends/matplotlib/compareplot.py:87: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]` scale = comp_df["scale"][0] /tmp/jl_x2wqV8/.CondaPkg/.pixi/envs/default/lib/python3.11/site-packages/arviz/plots/hdiplot.py:156: FutureWarning: hdi currently interprets 2d data as (draw, shape) but this will change in a future release to (chain, draw) for coherence with other functions hdi_data = hdi(y, hdi_prob=hdi_prob, circular=circular, multimodal=False, **hdi_kwargs) ┌ Warning: 1 parameters had Pareto shape values 0.7 < k ≤ 1. Resulting importance sampling estimates are likely to be unstable. └ @ PSIS ~/.julia/packages/PSIS/fU76x/src/core.jl:373 /tmp/jl_x2wqV8/.CondaPkg/.pixi/envs/default/lib/python3.11/site-packages/arviz/plots/ppcplot.py:268: FutureWarning: The return type of `Dataset.dims` will be changed to return a set of dimension names in future, in order to be more consistent with `DataArray.dims`. To access a mapping from dimension names to lengths, please use `Dataset.sizes`. flatten_pp = list(predictive_dataset.dims.keys()) /tmp/jl_x2wqV8/.CondaPkg/.pixi/envs/default/lib/python3.11/site-packages/arviz/plots/ppcplot.py:272: FutureWarning: The return type of `Dataset.dims` will be changed to return a set of dimension names in future, in order to be more consistent with `DataArray.dims`. To access a mapping from dimension names to lengths, please use `Dataset.sizes`. flatten = list(observed_data.dims.keys()) Test Summary: | Pass Total Time ArviZPythonPlots | 52 52 5m32.1s Testing ArviZPythonPlots tests passed Testing completed after 519.76s PkgEval succeeded after 1098.13s