Package evaluation of CherenkovDeconvolution on Julia 1.10.9 (96dc2d8c45*) started at 2025-06-06T20:26:49.742 ################################################################################ # Set-up # Installing PkgEval dependencies (TestEnv)... Set-up completed after 4.85s ################################################################################ # Installation # Installing CherenkovDeconvolution... Resolving package versions... Installed Conda ── v1.10.2 Installed PyCall ─ v1.94.1 Updating `~/.julia/environments/v1.10/Project.toml` [7995dc16] + CherenkovDeconvolution v0.3.0 Updating `~/.julia/environments/v1.10/Manifest.toml` [47edcb42] + ADTypes v1.14.0 [79e6a3ab] + Adapt v4.3.0 [4fba245c] + ArrayInterface v7.19.0 [7995dc16] + CherenkovDeconvolution v0.3.0 [bbf7d656] + CommonSubexpressions v0.3.1 [34da2185] + Compat v4.16.0 [8f4d0f93] + Conda v1.10.2 [187b0558] + ConstructionBase v1.5.8 [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 [163ba53b] + DiffResults v1.1.0 [b552c78f] + DiffRules v1.15.1 ⌅ [a0c0ee7d] + DifferentiationInterface v0.6.54 [6e83dbb3] + Discretizers v3.2.4 [ffbed154] + DocStringExtensions v0.9.4 [4e289a0a] + EnumX v1.0.5 [1a297f60] + FillArrays v1.13.0 [6a86dc24] + FiniteDiff v2.27.0 [f6369f11] + ForwardDiff v1.0.1 [842dd82b] + InlineStrings v1.4.3 [41ab1584] + InvertedIndices v1.3.1 [92d709cd] + IrrationalConstants v0.2.4 [c8e1da08] + IterTools v1.10.0 [82899510] + IteratorInterfaceExtensions v1.0.0 [692b3bcd] + JLLWrappers v1.7.0 [682c06a0] + JSON v0.21.4 [b964fa9f] + LaTeXStrings v1.4.0 [d3d80556] + LineSearches v7.3.0 [2ab3a3ac] + LogExpFunctions v0.3.29 [1914dd2f] + MacroTools v0.5.16 [e1d29d7a] + Missings v1.2.0 [d8a4904e] + MutableArithmetics v1.6.4 [d41bc354] + NLSolversBase v7.9.1 [77ba4419] + NaNMath v1.1.3 [429524aa] + Optim v1.12.0 [bac558e1] + OrderedCollections v1.8.1 [d96e819e] + Parameters v0.12.3 [69de0a69] + Parsers v2.8.3 ⌅ [f27b6e38] + Polynomials v3.1.8 [2dfb63ee] + PooledArrays v1.4.3 [85a6dd25] + PositiveFactorizations v0.2.4 ⌅ [aea7be01] + PrecompileTools v1.2.1 [21216c6a] + Preferences v1.4.3 [08abe8d2] + PrettyTables v2.4.0 ⌅ [438e738f] + PyCall v1.94.1 [3cdcf5f2] + RecipesBase v1.3.4 [189a3867] + Reexport v1.2.2 [ae029012] + Requires v1.3.1 ⌅ [3646fa90] + ScikitLearn v0.6.6 [6e75b9c4] + ScikitLearnBase v0.5.0 [91c51154] + SentinelArrays v1.4.8 [efcf1570] + Setfield v1.1.2 [a2af1166] + SortingAlgorithms v1.2.1 [276daf66] + SpecialFunctions v2.5.1 [1e83bf80] + StaticArraysCore v1.4.3 [82ae8749] + StatsAPI v1.7.1 ⌅ [2913bbd2] + StatsBase v0.33.21 [892a3eda] + StringManipulation v0.4.1 [3783bdb8] + TableTraits v1.0.1 [bd369af6] + Tables v1.12.1 [3a884ed6] + UnPack v1.0.2 [81def892] + VersionParsing v1.3.0 [efe28fd5] + OpenSpecFun_jll v0.5.6+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 [8f399da3] + Libdl [37e2e46d] + LinearAlgebra [56ddb016] + Logging [d6f4376e] + Markdown [a63ad114] + Mmap [ca575930] + NetworkOptions v1.2.0 [de0858da] + Printf [9a3f8284] + Random [ea8e919c] + SHA v0.7.0 [9e88b42a] + Serialization [6462fe0b] + Sockets [2f01184e] + SparseArrays v1.10.0 [10745b16] + Statistics v1.10.0 [fa267f1f] + TOML v1.0.3 [8dfed614] + Test [cf7118a7] + UUIDs [4ec0a83e] + Unicode [e66e0078] + CompilerSupportLibraries_jll v1.1.1+0 [deac9b47] + LibCURL_jll v8.4.0+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 Info Packages marked with ⌅ have new versions available but compatibility constraints restrict them from upgrading. To see why use `status --outdated -m` Building Conda ─→ `~/.julia/scratchspaces/44cfe95a-1eb2-52ea-b672-e2afdf69b78f/b19db3927f0db4151cb86d073689f2428e524576/build.log` Building PyCall → `~/.julia/scratchspaces/44cfe95a-1eb2-52ea-b672-e2afdf69b78f/53b8b07b721b77144a0fbbbc2675222ebf40a02d/build.log` Installation completed after 63.6s ################################################################################ # Precompilation # Precompiling PkgEval dependencies... Precompiling package dependencies... Precompilation completed after 117.6s ################################################################################ # Testing # Testing CherenkovDeconvolution Status `/tmp/jl_vGZsfS/Project.toml` [7995dc16] CherenkovDeconvolution v0.3.0 [a93c6f00] DataFrames v1.7.0 [6e83dbb3] Discretizers v3.2.4 [b4f34e82] Distances v0.10.12 [cc2ba9b6] MLDataUtils v0.5.4 [0db19996] NBInclude v2.4.0 [429524aa] Optim v1.12.0 ⌅ [f27b6e38] Polynomials v3.1.8 ⌅ [438e738f] PyCall v1.94.1 ⌅ [3646fa90] ScikitLearn v0.6.6 [6e75b9c4] ScikitLearnBase v0.5.0 ⌅ [2913bbd2] StatsBase v0.33.21 [ddb6d928] YAML v0.4.14 [37e2e46d] LinearAlgebra [9a3f8284] Random [2f01184e] SparseArrays v1.10.0 [10745b16] Statistics v1.10.0 [8dfed614] Test Status `/tmp/jl_vGZsfS/Manifest.toml` [47edcb42] ADTypes v1.14.0 [79e6a3ab] Adapt v4.3.0 [4fba245c] ArrayInterface v7.19.0 [7995dc16] CherenkovDeconvolution v0.3.0 [bbf7d656] CommonSubexpressions v0.3.1 [34da2185] Compat v4.16.0 [8f4d0f93] Conda v1.10.2 [187b0558] ConstructionBase v1.5.8 [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 [8bb1440f] DelimitedFiles v1.9.1 [163ba53b] DiffResults v1.1.0 [b552c78f] DiffRules v1.15.1 ⌅ [a0c0ee7d] DifferentiationInterface v0.6.54 [6e83dbb3] Discretizers v3.2.4 [b4f34e82] Distances v0.10.12 [ffbed154] DocStringExtensions v0.9.4 [4e289a0a] EnumX v1.0.5 [1a297f60] FillArrays v1.13.0 [6a86dc24] FiniteDiff v2.27.0 [f6369f11] ForwardDiff v1.0.1 [842dd82b] InlineStrings v1.4.3 [41ab1584] InvertedIndices v1.3.1 [92d709cd] IrrationalConstants v0.2.4 [c8e1da08] IterTools v1.10.0 [82899510] IteratorInterfaceExtensions v1.0.0 [692b3bcd] JLLWrappers v1.7.0 [682c06a0] JSON v0.21.4 [b964fa9f] LaTeXStrings v1.4.0 ⌅ [7f8f8fb0] LearnBase v0.3.0 [d3d80556] LineSearches v7.3.0 [2ab3a3ac] LogExpFunctions v0.3.29 ⌃ [9920b226] MLDataPattern v0.5.4 [cc2ba9b6] MLDataUtils v0.5.4 [66a33bbf] MLLabelUtils v0.5.7 [1914dd2f] MacroTools v0.5.16 [dbb5928d] MappedArrays v0.4.2 [e1d29d7a] Missings v1.2.0 [d8a4904e] MutableArithmetics v1.6.4 [0db19996] NBInclude v2.4.0 [d41bc354] NLSolversBase v7.9.1 [77ba4419] NaNMath v1.1.3 [429524aa] Optim v1.12.0 [bac558e1] OrderedCollections v1.8.1 [d96e819e] Parameters v0.12.3 [69de0a69] Parsers v2.8.3 ⌅ [f27b6e38] Polynomials v3.1.8 [2dfb63ee] PooledArrays v1.4.3 [85a6dd25] PositiveFactorizations v0.2.4 ⌅ [aea7be01] PrecompileTools v1.2.1 [21216c6a] Preferences v1.4.3 [08abe8d2] PrettyTables v2.4.0 ⌅ [438e738f] PyCall v1.94.1 [3cdcf5f2] RecipesBase v1.3.4 [189a3867] Reexport v1.2.2 [ae029012] Requires v1.3.1 ⌅ [3646fa90] ScikitLearn v0.6.6 [6e75b9c4] ScikitLearnBase v0.5.0 [91c51154] SentinelArrays v1.4.8 [efcf1570] Setfield v1.1.2 [b85f4697] SoftGlobalScope v1.1.0 [a2af1166] SortingAlgorithms v1.2.1 [276daf66] SpecialFunctions v2.5.1 [1e83bf80] StaticArraysCore v1.4.3 [82ae8749] StatsAPI v1.7.1 ⌅ [2913bbd2] StatsBase v0.33.21 [69024149] StringEncodings v0.3.7 [892a3eda] StringManipulation v0.4.1 [3783bdb8] TableTraits v1.0.1 [bd369af6] Tables v1.12.1 [3a884ed6] UnPack v1.0.2 [81def892] VersionParsing v1.3.0 [ddb6d928] YAML v0.4.14 [94ce4f54] Libiconv_jll v1.18.0+0 [efe28fd5] OpenSpecFun_jll v0.5.6+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 [8f399da3] Libdl [37e2e46d] LinearAlgebra [56ddb016] Logging [d6f4376e] Markdown [a63ad114] Mmap [ca575930] NetworkOptions v1.2.0 [de0858da] Printf [3fa0cd96] REPL [9a3f8284] Random [ea8e919c] SHA v0.7.0 [9e88b42a] Serialization [6462fe0b] Sockets [2f01184e] SparseArrays v1.10.0 [10745b16] Statistics v1.10.0 [fa267f1f] TOML v1.0.3 [8dfed614] Test [cf7118a7] UUIDs [4ec0a83e] Unicode [e66e0078] CompilerSupportLibraries_jll v1.1.1+0 [deac9b47] LibCURL_jll v8.4.0+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 Info Packages marked with ⌃ and ⌅ have new versions available. Those with ⌃ may be upgradable, but those with ⌅ are restricted by compatibility constraints from upgrading. Testing Running tests... [ Info: Running `conda install -q -y -c anaconda conda` in root environment Channels: - anaconda - conda-forge Platform: linux-64 Collecting package metadata (repodata.json): ...working... done Solving environment: ...working... done ## Package Plan ## environment location: /home/pkgeval/.julia/conda/3/x86_64 added / updated specs: - conda The following packages will be downloaded: package | build ---------------------------|----------------- conda-25.5.1 | py312h06a4308_0 1.2 MB anaconda ------------------------------------------------------------ Total: 1.2 MB The following packages will be UPDATED: conda conda-forge::conda-25.3.0-py312h7900f~ --> anaconda::conda-25.5.1-py312h06a4308_0 Preparing transaction: ...working... done Verifying transaction: ...working... done Executing transaction: ...working... done [ Info: Running `conda install -q -y -c conda-forge 'libstdcxx-ng>=3.4,<13.0'` in root environment Channels: - conda-forge Platform: linux-64 Collecting package metadata (repodata.json): ...working... done Solving environment: ...working... done ## Package Plan ## environment location: /home/pkgeval/.julia/conda/3/x86_64 added / updated specs: - libstdcxx-ng[version='>=3.4,<13.0'] The following packages will be downloaded: package | build ---------------------------|----------------- libstdcxx-ng-12.3.0 | hc0a3c3a_7 3.3 MB conda-forge ------------------------------------------------------------ Total: 3.3 MB The following packages will be DOWNGRADED: libstdcxx-ng 15.1.0-h4852527_2 --> 12.3.0-hc0a3c3a_7 Preparing transaction: ...working... done Verifying transaction: ...working... done Executing transaction: ...working... done [ Info: Installing sklearn via the Conda scikit-learn package... [ Info: Running `conda install -q -y scikit-learn` in root environment Channels: - conda-forge Platform: linux-64 Collecting package metadata (repodata.json): ...working... done Solving environment: ...working... done ## Package Plan ## environment location: /home/pkgeval/.julia/conda/3/x86_64 added / updated specs: - scikit-learn The following packages will be downloaded: package | build ---------------------------|----------------- joblib-1.5.1 | pyhd8ed1ab_0 219 KB conda-forge scikit-learn-1.7.0 | py312h7a48858_0 9.9 MB conda-forge scipy-1.15.2 | py312ha707e6e_0 16.3 MB conda-forge threadpoolctl-3.6.0 | pyhecae5ae_0 23 KB conda-forge ------------------------------------------------------------ Total: 26.4 MB The following NEW packages will be INSTALLED: joblib conda-forge/noarch::joblib-1.5.1-pyhd8ed1ab_0 scikit-learn conda-forge/linux-64::scikit-learn-1.7.0-py312h7a48858_0 scipy conda-forge/linux-64::scipy-1.15.2-py312ha707e6e_0 threadpoolctl conda-forge/noarch::threadpoolctl-3.6.0-pyhecae5ae_0 Preparing transaction: ...working... done Verifying transaction: ...working... done Executing transaction: ...working... done Test Summary: | Pass Total Time CherenkovDeconvolution.DeconvUtil, as tested in test/DeconvUtil.jl | 363 363 19.2s Test Summary: | Pass Total Time CherenkovDeconvolution.Binnings, as tested in test/Binnings.jl | 12 12 5.6s Test Summary: | Pass Total Time CherenkovDeconvolution.Smoothings, as tested in test/Smoothings.jl | 30 30 1.0s Test Summary: | Pass Total Time Methods.LabelSanitizer, as tested in test/Methods.jl | 16 16 1.1s [ Info: 12 weights are not equal - checking Laplace correction Test Summary: | Pass Total Time Methods related to DSEA, as tested in test/methods/dsea.jl | 42 42 4.9s This is iteration 0 with chi2s=NaN This is iteration 1 with chi2s=0.02186166714804993 This is iteration 2 with chi2s=0.0010847259272459995 This is iteration 3 with chi2s=6.686604272813053e-5 no smoothing (0): 0.3333333333333333 no smoothing (1): 0.2732169187378448 no smoothing (2): 0.26004314938701845 no smoothing (3): 0.2567902411972386 impact=1.0, O=1 (0): 0.3333333333333333 impact=1.0, O=1 (1): 0.2732169187378448 impact=1.0, O=1 (2): 0.27025256658803415 impact=1.0, O=1 (3): 0.2701107743053669 impact=0.5, O=1 (0): 0.3333333333333333 impact=0.5, O=1 (1): 0.2732169187378448 impact=0.5, O=1 (2): 0.2654380929239672 impact=0.5, O=1 (3): 0.2644011451856979 impact=0.0, O=1 (0): 0.3333333333333333 impact=0.0, O=1 (1): 0.2732169187378448 impact=0.0, O=1 (2): 0.26004314938701845 impact=0.0, O=1 (3): 0.2567902411972386 ┌ Warning: Deprecated `dsea(data, config)` ignores train_predict and uses GaussianNB; please call `deconvolve(DSEA(config), data)` instead │ caller = dsea(X_obs::SubArray{Float64, 2, LinearAlgebra.Adjoint{Float64, Matrix{Float64}}, Tuple{Vector{Int64}, Base.Slice{Base.OneTo{Int64}}}, false}, X_trn::SubArray{Float64, 2, LinearAlgebra.Adjoint{Float64, Matrix{Float64}}, Tuple{Vector{Int64}, Base.Slice{Base.OneTo{Int64}}}, false}, y_trn::SubArray{Int64, 1, Vector{Int64}, Tuple{Vector{Int64}}, false}, train_predict::Function) at dsea.jl:196 └ @ CherenkovDeconvolution.Methods ~/.julia/packages/CherenkovDeconvolution/Mui86/src/methods/dsea.jl:196 ┌ Warning: `TreeDiscretizer(data, config)` is deprecated; call `BinningDiscretizer(TreeBinning(config), data)` instead │ caller = TreeDiscretizer(X_trn::SubArray{Float64, 2, LinearAlgebra.Adjoint{Float64, Matrix{Float64}}, Tuple{Vector{Int64}, Base.Slice{Base.OneTo{Int64}}}, false}, y_trn::SubArray{Int64, 1, Vector{Int64}, Tuple{Vector{Int64}}, false}, J::Int64) at Binnings.jl:241 └ @ CherenkovDeconvolution.Binnings ~/.julia/packages/CherenkovDeconvolution/Mui86/src/Binnings.jl:241 ┌ Warning: `run(data, config)` is deprecated; please call `deconvolve(RUN(config), data)` instead │ caller = run(x_obs::Vector{Int64}, x_trn::Vector{Int64}, y_trn::SubArray{Int64, 1, Vector{Int64}, Tuple{Vector{Int64}}, false}) at run.jl:408 └ @ CherenkovDeconvolution.Methods ~/.julia/packages/CherenkovDeconvolution/Mui86/src/methods/run.jl:408 ┌ Warning: Normalization replaced a zero vector by a uniform density └ @ CherenkovDeconvolution.DeconvUtil ~/.julia/packages/CherenkovDeconvolution/Mui86/src/DeconvUtil.jl:166 ┌ Warning: `p_run(data, config)` is deprecated; please call `deconvolve(PRUN(config), data)` instead │ caller = p_run(x_obs::Vector{Int64}, x_trn::Vector{Int64}, y_trn::SubArray{Int64, 1, Vector{Int64}, Tuple{Vector{Int64}}, false}) at prun.jl:196 └ @ CherenkovDeconvolution.Methods ~/.julia/packages/CherenkovDeconvolution/Mui86/src/methods/prun.jl:196 ┌ Warning: Normalization replaced a zero vector by a uniform density └ @ CherenkovDeconvolution.DeconvUtil ~/.julia/packages/CherenkovDeconvolution/Mui86/src/DeconvUtil.jl:166 ┌ Warning: `ibu(data, config)` is deprecated; please call `deconvolve(IBU(config), data)` instead │ caller = ibu(x_obs::Vector{Int64}, x_trn::Vector{Int64}, y_trn::SubArray{Int64, 1, Vector{Int64}, Tuple{Vector{Int64}}, false}) at ibu.jl:173 └ @ CherenkovDeconvolution.Methods ~/.julia/packages/CherenkovDeconvolution/Mui86/src/methods/ibu.jl:173 ┌ Warning: Normalization replaced a zero vector by a uniform density └ @ CherenkovDeconvolution.DeconvUtil ~/.julia/packages/CherenkovDeconvolution/Mui86/src/DeconvUtil.jl:166 ┌ Warning: `svd(data, config)` is deprecated; please call `deconvolve(SVD(config), data)` instead │ caller = svd(x_obs::Vector{Int64}, x_trn::Vector{Int64}, y_trn::SubArray{Int64, 1, Vector{Int64}, Tuple{Vector{Int64}}, false}) at svd.jl:137 └ @ CherenkovDeconvolution.Methods ~/.julia/packages/CherenkovDeconvolution/Mui86/src/methods/svd.jl:137 ┌ Warning: Normalization set negative values to zero └ @ CherenkovDeconvolution.DeconvUtil ~/.julia/packages/CherenkovDeconvolution/Mui86/src/DeconvUtil.jl:151 ┌ Warning: Deprecated `dsea(data, config)` ignores train_predict and uses GaussianNB; please call `deconvolve(DSEA(config), data)` instead │ caller = kwcall(::@NamedTuple{K::Int64, inspect::Main.deprecatedinspectionipynb.var"#1#2"}, ::typeof(dsea), X_obs::SubArray{Float64, 2, LinearAlgebra.Adjoint{Float64, Matrix{Float64}}, Tuple{Vector{Int64}, Base.Slice{Base.OneTo{Int64}}}, false}, X_trn::SubArray{Float64, 2, LinearAlgebra.Adjoint{Float64, Matrix{Float64}}, Tuple{Vector{Int64}, Base.Slice{Base.OneTo{Int64}}}, false}, y_trn::SubArray{Int64, 1, Vector{Int64}, Tuple{Vector{Int64}}, false}, train_predict::Function) at dsea.jl:196 └ @ CherenkovDeconvolution.Methods ~/.julia/packages/CherenkovDeconvolution/Mui86/src/methods/dsea.jl:196 ┌ Warning: `ibu(data, config)` is deprecated; please call `deconvolve(IBU(config), data)` instead │ caller = kwcall(::@NamedTuple{inspect::Main.deprecatedinspectionipynb.var"#3#4"}, ::typeof(ibu), x_obs::Vector{Int64}, x_trn::Vector{Int64}, y_trn::SubArray{Int64, 1, Vector{Int64}, Tuple{Vector{Int64}}, false}) at ibu.jl:173 └ @ CherenkovDeconvolution.Methods ~/.julia/packages/CherenkovDeconvolution/Mui86/src/methods/ibu.jl:173 This is iteration 0 with chi2s=NaN This is iteration 1 with chi2s=0.02186166714804993 This is iteration 2 with chi2s=0.0010847259272459995 This is iteration 3 with chi2s=6.686604272813053e-5 ┌ Warning: `RunStepsize(data, config)` is deprecated; please call `initialize_deconvolve!(initialize_prefit!(RunStepsize(config), X_trn, y_trn), X_obs)` instead │ caller = ip:0x0 └ @ Core :-1 ┌ Warning: Deprecated `dsea(data, config)` ignores train_predict and uses GaussianNB; please call `deconvolve(DSEA(config), data)` instead │ caller = kwcall(::@NamedTuple{K::Int64, epsilon::Float64, alpha::RunStepsize}, ::typeof(dsea), X_obs::SubArray{Float64, 2, LinearAlgebra.Adjoint{Float64, Matrix{Float64}}, Tuple{Vector{Int64}, Base.Slice{Base.OneTo{Int64}}}, false}, X_trn::SubArray{Float64, 2, LinearAlgebra.Adjoint{Float64, Matrix{Float64}}, Tuple{Vector{Int64}, Base.Slice{Base.OneTo{Int64}}}, false}, y_trn::SubArray{Int64, 1, Vector{Int64}, Tuple{Vector{Int64}}, false}, train_predict::Function) at dsea.jl:196 └ @ CherenkovDeconvolution.Methods ~/.julia/packages/CherenkovDeconvolution/Mui86/src/methods/dsea.jl:196 Testing CherenkovDeconvolution tests passed Testing completed after 215.79s PkgEval succeeded after 435.92s