Package evaluation to test GaussianMixtures on Julia 1.14.0-DEV.14 (ec5cf08762*) started at 2025-10-30T17:53:48.912 ################################################################################ # Set-up # Installing PkgEval dependencies (TestEnv)... Set-up completed after 9.65s ################################################################################ # Installation # Installing GaussianMixtures... Resolving package versions... Updating `~/.julia/environments/v1.14/Project.toml` [cc18c42c] + GaussianMixtures v0.3.13 Updating `~/.julia/environments/v1.14/Manifest.toml` [66dad0bd] + AliasTables v1.1.3 [7d9fca2a] + Arpack v0.5.4 [aaaa29a8] + Clustering v0.15.8 [34da2185] + Compat v4.18.1 [9a962f9c] + DataAPI v1.16.0 [864edb3b] + DataStructures v0.19.1 [8bb1440f] + DelimitedFiles v1.9.1 [b4f34e82] + Distances v0.10.12 [31c24e10] + Distributions v0.25.122 [ffbed154] + DocStringExtensions v0.9.5 [5789e2e9] + FileIO v1.17.1 [1a297f60] + FillArrays v1.14.0 [cc18c42c] + GaussianMixtures v0.3.13 [076d061b] + HashArrayMappedTries v0.2.0 [34004b35] + HypergeometricFunctions v0.3.28 [92d709cd] + IrrationalConstants v0.2.6 ⌅ [033835bb] + JLD2 v0.5.15 [692b3bcd] + JLLWrappers v1.7.1 [2ab3a3ac] + LogExpFunctions v0.3.29 [1914dd2f] + MacroTools v0.5.16 [e1d29d7a] + Missings v1.2.0 [b8a86587] + NearestNeighbors v0.4.22 [bac558e1] + OrderedCollections v1.8.1 [90014a1f] + PDMats v0.11.36 [aea7be01] + PrecompileTools v1.3.3 [21216c6a] + Preferences v1.5.0 [43287f4e] + PtrArrays v1.3.0 [1fd47b50] + QuadGK v2.11.2 [189a3867] + Reexport v1.2.2 [ae029012] + Requires v1.3.1 [79098fc4] + Rmath v0.9.0 [6e75b9c4] + ScikitLearnBase v0.5.0 [7e506255] + ScopedValues v1.5.0 [a2af1166] + SortingAlgorithms v1.2.2 [276daf66] + SpecialFunctions v2.6.1 [90137ffa] + StaticArrays v1.9.15 [1e83bf80] + StaticArraysCore v1.4.4 [10745b16] + Statistics v1.11.1 [82ae8749] + StatsAPI v1.7.1 [2913bbd2] + StatsBase v0.34.7 [4c63d2b9] + StatsFuns v1.5.2 [3bb67fe8] + TranscodingStreams v0.11.3 ⌅ [68821587] + Arpack_jll v3.5.1+1 [efe28fd5] + OpenSpecFun_jll v0.5.6+0 [f50d1b31] + Rmath_jll v0.5.1+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 [ac6e5ff7] + JuliaSyntaxHighlighting v1.12.0 [b27032c2] + LibCURL v1.0.0 [76f85450] + LibGit2 v1.11.0 [8f399da3] + Libdl v1.11.0 [37e2e46d] + LinearAlgebra v1.13.0 [56ddb016] + Logging v1.11.0 [d6f4376e] + Markdown v1.11.0 [a63ad114] + Mmap v1.11.0 [ca575930] + NetworkOptions v1.3.0 [44cfe95a] + Pkg v1.13.0 [de0858da] + Printf v1.11.0 [9a3f8284] + Random v1.11.0 [ea8e919c] + SHA v1.0.0 [9e88b42a] + Serialization v1.11.0 [6462fe0b] + Sockets v1.11.0 [2f01184e] + SparseArrays v1.13.0 [f489334b] + StyledStrings v1.11.0 [4607b0f0] + SuiteSparse [fa267f1f] + TOML v1.0.3 [a4e569a6] + Tar v1.10.0 [cf7118a7] + UUIDs v1.11.0 [4ec0a83e] + Unicode v1.11.0 [e66e0078] + CompilerSupportLibraries_jll v1.3.0+1 [deac9b47] + LibCURL_jll v8.16.0+0 [e37daf67] + LibGit2_jll v1.9.1+0 [29816b5a] + LibSSH2_jll v1.11.3+1 [14a3606d] + MozillaCACerts_jll v2025.9.9 [4536629a] + OpenBLAS_jll v0.3.29+0 [05823500] + OpenLibm_jll v0.8.7+0 [458c3c95] + OpenSSL_jll v3.5.4+0 [efcefdf7] + PCRE2_jll v10.47.0+0 [bea87d4a] + SuiteSparse_jll v7.10.1+0 [83775a58] + Zlib_jll v1.3.1+2 [3161d3a3] + Zstd_jll v1.5.7+1 [8e850b90] + libblastrampoline_jll v5.15.0+0 [8e850ede] + nghttp2_jll v1.67.1+0 [3f19e933] + p7zip_jll v17.6.0+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 4.94s ################################################################################ # Precompilation # Precompiling PkgEval dependencies... ┌ Error: Failed to use TestEnv.jl; test dependencies will not be precompiled │ exception = │ UndefVarError: `project_rel_path` not defined in `TestEnv` │ Suggestion: this global was defined as `Pkg.Operations.project_rel_path` but not assigned a value. │ Stacktrace: │ [1] get_test_dir(ctx::Pkg.Types.Context, pkgspec::PackageSpec) │ @ TestEnv ~/.julia/packages/TestEnv/nGMfF/src/julia-1.11/common.jl:75 │ [2] test_dir_has_project_file │ @ ~/.julia/packages/TestEnv/nGMfF/src/julia-1.11/common.jl:52 [inlined] │ [3] maybe_gen_project_override! │ @ ~/.julia/packages/TestEnv/nGMfF/src/julia-1.11/common.jl:83 [inlined] │ [4] activate(pkg::String; allow_reresolve::Bool) │ @ TestEnv ~/.julia/packages/TestEnv/nGMfF/src/julia-1.11/activate_set.jl:12 │ [5] activate(pkg::String) │ @ TestEnv ~/.julia/packages/TestEnv/nGMfF/src/julia-1.11/activate_set.jl:9 │ [6] top-level scope │ @ /PkgEval.jl/scripts/precompile.jl:24 │ [7] include(mod::Module, _path::String) │ @ Base ./Base.jl:309 │ [8] exec_options(opts::Base.JLOptions) │ @ Base ./client.jl:344 │ [9] _start() │ @ Base ./client.jl:577 └ @ Main /PkgEval.jl/scripts/precompile.jl:26 Precompiling package dependencies... Precompiling packages... 45767.0 ms ✓ JLD2 4131.2 ms ✓ Clustering 10122.1 ms ✓ Distributions 10222.0 ms ✓ GaussianMixtures 4 dependencies successfully precompiled in 72 seconds. 83 already precompiled. Precompilation completed after 85.04s ################################################################################ # Testing # Testing GaussianMixtures Status `/tmp/jl_WBQHca/Project.toml` [7d9fca2a] Arpack v0.5.4 [aaaa29a8] Clustering v0.15.8 [34da2185] Compat v4.18.1 [8bb1440f] DelimitedFiles v1.9.1 [31c24e10] Distributions v0.25.122 [5789e2e9] FileIO v1.17.1 [cc18c42c] GaussianMixtures v0.3.13 ⌅ [033835bb] JLD2 v0.5.15 [90014a1f] PDMats v0.11.36 [ce6b1742] RDatasets v0.7.7 [6e75b9c4] ScikitLearnBase v0.5.0 [276daf66] SpecialFunctions v2.6.1 [10745b16] Statistics v1.11.1 [2913bbd2] StatsBase v0.34.7 [8ba89e20] Distributed v1.11.0 [37e2e46d] LinearAlgebra v1.13.0 [56ddb016] Logging v1.11.0 [de0858da] Printf v1.11.0 [9a3f8284] Random v1.11.0 [8dfed614] Test v1.11.0 Status `/tmp/jl_WBQHca/Manifest.toml` [66dad0bd] AliasTables v1.1.3 [7d9fca2a] Arpack v0.5.4 [336ed68f] CSV v0.10.15 ⌅ [324d7699] CategoricalArrays v0.10.8 [aaaa29a8] Clustering v0.15.8 [944b1d66] CodecZlib v0.7.8 [34da2185] Compat v4.18.1 [a8cc5b0e] Crayons v4.1.1 [9a962f9c] DataAPI v1.16.0 [a93c6f00] DataFrames v1.8.1 [864edb3b] DataStructures v0.19.1 [e2d170a0] DataValueInterfaces v1.0.0 [8bb1440f] DelimitedFiles v1.9.1 [b4f34e82] Distances v0.10.12 [31c24e10] Distributions v0.25.122 [ffbed154] DocStringExtensions v0.9.5 [e2ba6199] ExprTools v0.1.10 [5789e2e9] FileIO v1.17.1 [48062228] FilePathsBase v0.9.24 [1a297f60] FillArrays v1.14.0 [cc18c42c] GaussianMixtures v0.3.13 [076d061b] HashArrayMappedTries v0.2.0 [34004b35] HypergeometricFunctions v0.3.28 [842dd82b] InlineStrings v1.4.5 [41ab1584] InvertedIndices v1.3.1 [92d709cd] IrrationalConstants v0.2.6 [82899510] IteratorInterfaceExtensions v1.0.0 ⌅ [033835bb] JLD2 v0.5.15 [692b3bcd] JLLWrappers v1.7.1 [b964fa9f] LaTeXStrings v1.4.0 [2ab3a3ac] LogExpFunctions v0.3.29 [1914dd2f] MacroTools v0.5.16 [e1d29d7a] Missings v1.2.0 [78c3b35d] Mocking v0.8.1 [b8a86587] NearestNeighbors v0.4.22 [bac558e1] OrderedCollections v1.8.1 [90014a1f] PDMats v0.11.36 [69de0a69] Parsers v2.8.3 [2dfb63ee] PooledArrays v1.4.3 [aea7be01] PrecompileTools v1.3.3 [21216c6a] Preferences v1.5.0 [08abe8d2] PrettyTables v3.1.0 [43287f4e] PtrArrays v1.3.0 [1fd47b50] QuadGK v2.11.2 ⌅ [df47a6cb] RData v0.8.3 [ce6b1742] RDatasets v0.7.7 [189a3867] Reexport v1.2.2 [ae029012] Requires v1.3.1 [79098fc4] Rmath v0.9.0 [6e75b9c4] ScikitLearnBase v0.5.0 [7e506255] ScopedValues v1.5.0 [6c6a2e73] Scratch v1.3.0 [91c51154] SentinelArrays v1.4.8 [a2af1166] SortingAlgorithms v1.2.2 [276daf66] SpecialFunctions v2.6.1 [90137ffa] StaticArrays v1.9.15 [1e83bf80] StaticArraysCore v1.4.4 [10745b16] Statistics v1.11.1 [82ae8749] StatsAPI v1.7.1 [2913bbd2] StatsBase v0.34.7 [4c63d2b9] StatsFuns v1.5.2 [892a3eda] StringManipulation v0.4.1 [dc5dba14] TZJData v1.5.0+2025b [3783bdb8] TableTraits v1.0.1 [bd369af6] Tables v1.12.1 [f269a46b] TimeZones v1.22.1 [3bb67fe8] TranscodingStreams v0.11.3 [ea10d353] WeakRefStrings v1.4.2 [76eceee3] WorkerUtilities v1.6.1 ⌅ [68821587] Arpack_jll v3.5.1+1 [efe28fd5] OpenSpecFun_jll v0.5.6+0 [f50d1b31] Rmath_jll v0.5.1+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 [b27032c2] LibCURL v1.0.0 [76f85450] LibGit2 v1.11.0 [8f399da3] Libdl v1.11.0 [37e2e46d] LinearAlgebra v1.13.0 [56ddb016] Logging v1.11.0 [d6f4376e] Markdown v1.11.0 [a63ad114] Mmap v1.11.0 [ca575930] NetworkOptions v1.3.0 [44cfe95a] Pkg v1.13.0 [de0858da] Printf v1.11.0 [3fa0cd96] REPL v1.11.0 [9a3f8284] Random v1.11.0 [ea8e919c] SHA v1.0.0 [9e88b42a] Serialization v1.11.0 [6462fe0b] Sockets v1.11.0 [2f01184e] SparseArrays v1.13.0 [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 v8.16.0+0 [e37daf67] LibGit2_jll v1.9.1+0 [29816b5a] LibSSH2_jll v1.11.3+1 [14a3606d] MozillaCACerts_jll v2025.9.9 [4536629a] OpenBLAS_jll v0.3.29+0 [05823500] OpenLibm_jll v0.8.7+0 [458c3c95] OpenSSL_jll v3.5.4+0 [efcefdf7] PCRE2_jll v10.47.0+0 [bea87d4a] SuiteSparse_jll v7.10.1+0 [83775a58] Zlib_jll v1.3.1+2 [3161d3a3] Zstd_jll v1.5.7+1 [8e850b90] libblastrampoline_jll v5.15.0+0 [8e850ede] nghttp2_jll v1.67.1+0 [3f19e933] p7zip_jll v17.6.0+0 Info Packages marked with ⌅ have new versions available but compatibility constraints restrict them from upgrading. Testing Running tests... (100000, -1.0788125574114774e6, [2633.9390579708343, 97366.06094202919], [1242.7649433614097 -2434.01847159257 4.056904709531772; -1182.5897119463352 2578.0326594394173 -318.89768881604357], [[1667.2304090222844 -602.4944046351723 -1083.171734056137; -602.4944046351723 4042.723200836219 -41.470436641480376; -1083.171734056137 -41.47043664148039 1274.2389310543554], [99262.76243790683 1048.261620743523 603.736044857543; 1048.261620743523 96204.87636997229 52.107150788179; 603.736044857543 52.107150788179055 98881.02130919984]]) Test Summary: | Pass Total Time data.jl | 8 8 4m56.6s [ Info: Initializing GMM, 2 Gaussians diag covariance 1 dimensions using 272 data points K-means converged with 4 iterations (objv = 8855.79069767458) ┌ Info: K-means with 272 data points using 4 iterations └ 68.0 data points per parameter [ Info: Initializing GMM, 8 Gaussians diag covariance 2 dimensions using 272 data points K-means converged with 4 iterations (objv = 790.6715829285909) ┌ Info: K-means with 272 data points using 4 iterations └ 11.3 data points per parameter ┌ Warning: `lgamma(x::Real)` is deprecated, use `(logabsgamma(x))[1]` instead. │ caller = lowerbound(vg::VGMM{Float64}, N::Vector{Float64}, mx::Matrix{Float64}, S::Vector{Matrix{Float64}}, Elogπ::Vector{Float64}, ElogdetΛ::Vector{Float64}, ElogpZπqZ::Float64) at bayes.jl:221 └ @ Core ~/.julia/packages/GaussianMixtures/RYvNa/src/bayes.jl:221 ┌ Warning: `lgamma(x::Real)` is deprecated, use `(logabsgamma(x))[1]` instead. │ caller = lowerbound(vg::VGMM{Float64}, N::Vector{Float64}, mx::Matrix{Float64}, S::Vector{Matrix{Float64}}, Elogπ::Vector{Float64}, ElogdetΛ::Vector{Float64}, ElogpZπqZ::Float64) at bayes.jl:221 └ @ Core ~/.julia/packages/GaussianMixtures/RYvNa/src/bayes.jl:221 ┌ Warning: `lgamma(x::Real)` is deprecated, use `(logabsgamma(x))[1]` instead. │ caller = _broadcast_getindex_evalf at broadcast.jl:698 [inlined] └ @ Core ./broadcast.jl:698 ┌ Warning: `lgamma(x::Real)` is deprecated, use `(logabsgamma(x))[1]` instead. │ caller = lowerbound(vg::VGMM{Float64}, N::Vector{Float64}, mx::Matrix{Float64}, S::Vector{Matrix{Float64}}, Elogπ::Vector{Float64}, ElogdetΛ::Vector{Float64}, ElogpZπqZ::Float64) at bayes.jl:230 └ @ Core ~/.julia/packages/GaussianMixtures/RYvNa/src/bayes.jl:230 ┌ Warning: `lgamma(x::Real)` is deprecated, use `(logabsgamma(x))[1]` instead. │ caller = _broadcast_getindex_evalf at broadcast.jl:698 [inlined] └ @ Core ./broadcast.jl:698 ┌ Warning: `lgamma(x::Real)` is deprecated, use `(logabsgamma(x))[1]` instead. │ caller = _broadcast_getindex_evalf at broadcast.jl:698 [inlined] └ @ Core ./broadcast.jl:698 History[Thu Oct 30 18:04:13 2025: Initializing GMM, 8 Gaussians diag covariance 2 dimensions using 272 data points , Thu Oct 30 18:04:15 2025: K-means with 272 data points using 4 iterations 11.3 data points per parameter , Thu Oct 30 18:04:15 2025: EM with 272 data points 0 iterations avll -2.056204 5.8 data points per parameter , Thu Oct 30 18:04:23 2025: GMM converted to Variational GMM , Thu Oct 30 18:04:33 2025: iteration 1, lowerbound -3.752668 , Thu Oct 30 18:04:33 2025: iteration 2, lowerbound -3.603036 , Thu Oct 30 18:04:33 2025: iteration 3, lowerbound -3.441827 , Thu Oct 30 18:04:33 2025: iteration 4, lowerbound -3.267864 , Thu Oct 30 18:04:33 2025: iteration 5, lowerbound -3.104874 , Thu Oct 30 18:04:33 2025: iteration 6, lowerbound -2.976184 , Thu Oct 30 18:04:34 2025: dropping number of Gaussions to 7 , Thu Oct 30 18:04:34 2025: iteration 7, lowerbound -2.889782 , Thu Oct 30 18:04:34 2025: dropping number of Gaussions to 5 , Thu Oct 30 18:04:34 2025: iteration 8, lowerbound -2.827725 , Thu Oct 30 18:04:34 2025: dropping number of Gaussions to 4 , Thu Oct 30 18:04:34 2025: iteration 9, lowerbound -2.779838 , Thu Oct 30 18:04:34 2025: iteration 10, lowerbound -2.757355 , Thu Oct 30 18:04:34 2025: dropping number of Gaussions to 3 , Thu Oct 30 18:04:34 2025: iteration 11, lowerbound -2.739795 , Thu Oct 30 18:04:34 2025: iteration 12, lowerbound -2.717546 , Thu Oct 30 18:04:34 2025: iteration 13, lowerbound -2.693256 , Thu Oct 30 18:04:34 2025: iteration 14, lowerbound -2.662882 , Thu Oct 30 18:04:34 2025: iteration 15, lowerbound -2.626749 , Thu Oct 30 18:04:34 2025: iteration 16, lowerbound -2.586063 , Thu Oct 30 18:04:34 2025: iteration 17, lowerbound -2.542877 , Thu Oct 30 18:04:34 2025: iteration 18, lowerbound -2.499736 , Thu Oct 30 18:04:34 2025: iteration 19, lowerbound -2.458893 , Thu Oct 30 18:04:34 2025: iteration 20, lowerbound -2.421482 , Thu Oct 30 18:04:34 2025: iteration 21, lowerbound -2.387366 , Thu Oct 30 18:04:34 2025: iteration 22, lowerbound -2.356192 , Thu Oct 30 18:04:34 2025: iteration 23, lowerbound -2.329489 , Thu Oct 30 18:04:34 2025: iteration 24, lowerbound -2.311862 , Thu Oct 30 18:04:34 2025: iteration 25, lowerbound -2.307688 , Thu Oct 30 18:04:34 2025: dropping number of Gaussions to 2 , Thu Oct 30 18:04:34 2025: iteration 26, lowerbound -2.302918 , Thu Oct 30 18:04:34 2025: iteration 27, lowerbound -2.299259 , Thu Oct 30 18:04:34 2025: iteration 28, lowerbound -2.299256 , Thu Oct 30 18:04:34 2025: iteration 29, lowerbound -2.299254 , Thu Oct 30 18:04:34 2025: iteration 30, lowerbound -2.299254 , Thu Oct 30 18:04:34 2025: iteration 31, lowerbound -2.299253 , Thu Oct 30 18:04:34 2025: iteration 32, lowerbound -2.299253 , Thu Oct 30 18:04:34 2025: iteration 33, lowerbound -2.299253 , Thu Oct 30 18:04:34 2025: iteration 34, lowerbound -2.299253 , Thu Oct 30 18:04:34 2025: iteration 35, lowerbound -2.299253 , Thu Oct 30 18:04:34 2025: iteration 36, lowerbound -2.299253 , Thu Oct 30 18:04:34 2025: iteration 37, lowerbound -2.299253 , Thu Oct 30 18:04:34 2025: iteration 38, lowerbound -2.299253 , Thu Oct 30 18:04:34 2025: iteration 39, lowerbound -2.299253 , Thu Oct 30 18:04:34 2025: iteration 40, lowerbound -2.299253 , Thu Oct 30 18:04:34 2025: iteration 41, lowerbound -2.299253 , Thu Oct 30 18:04:34 2025: iteration 42, lowerbound -2.299253 , Thu Oct 30 18:04:34 2025: iteration 43, lowerbound -2.299253 , Thu Oct 30 18:04:34 2025: iteration 44, lowerbound -2.299253 , Thu Oct 30 18:04:34 2025: iteration 45, lowerbound -2.299253 , Thu Oct 30 18:04:34 2025: iteration 46, lowerbound -2.299253 , Thu Oct 30 18:04:34 2025: iteration 47, lowerbound -2.299253 , Thu Oct 30 18:04:34 2025: iteration 48, lowerbound -2.299253 , Thu Oct 30 18:04:34 2025: iteration 49, lowerbound -2.299253 , Thu Oct 30 18:04:34 2025: iteration 50, lowerbound -2.299253 , Thu Oct 30 18:04:34 2025: 50 variational Bayes EM-like iterations using 272 data points, final lowerbound -2.299253 ] α = [178.04509222607825, 95.95490777392195] β = [178.04509222607825, 95.95490777392195] m = [4.250300733269386 79.2868669443541; 2.000229257774829 53.85198717245845] ν = [180.04509222607825, 97.95490777392195] W = LinearAlgebra.UpperTriangular{Float64, Matrix{Float64}}[[0.18404155547477893 -0.007644049042334548; 0.0 0.008581705166323608], [0.3758763611957352 -0.008953123827356848; 0.0 0.01274866477741185]] Test Summary: | Pass Total Time bayes.jl | 3 3 1m52.6s Kind: diag, size256 nx: 100000 sum(zeroth order stats): 100000.00000000007 avll from stats: -0.9972434872253133 avll from llpg: -0.9972434872254249 avll direct: -0.9972434872254249 sum posterior: 100000.0 Kind: full, size16 nx: 100000 sum(zeroth order stats): 100000.00000000001 avll from stats: -0.9930749967368915 avll from llpg: -0.9930749967368916 avll direct: -0.9930749967368916 sum posterior: 100000.0 kind diag, method split ┌ Info: 0: avll = └ tll[1] = -1.4524818948887939 ┌ Info: 1 │ avll = │ 50-element Vector{Float64}: │ -1.4525885203422815 │ -1.4525078018258681 │ -1.452200853901521 │ -1.4481422021477643 │ ⋮ │ -1.4144177481830562 │ -1.414410960717615 └ -1.4144041131169343 ┌ Info: 2 │ avll = │ 50-element Vector{Float64}: │ -1.4145598676894595 │ -1.4144066107918778 │ -1.4138502668226667 │ -1.4086208306701251 │ ⋮ │ -1.3666931394631086 │ -1.3665686126873209 └ -1.366456184820878 ┌ Info: 3 │ avll = │ 50-element Vector{Float64}: │ -1.366524136983991 │ -1.366230890497432 │ -1.3652170669390304 │ -1.3571991383142776 │ ⋮ │ -1.3017604395965576 │ -1.301754421875494 └ -1.301749638435638 ┌ Warning: Variances had to be floored │ ind = │ 1-element Vector{Int64}: │ 5 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 1-element Vector{Int64}: │ 5 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 1-element Vector{Int64}: │ 12 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Info: 4 │ avll = │ 50-element Vector{Float64}: │ -1.301956987518496 │ -1.3016867108152732 │ -1.2999806905045166 │ -1.2855941747025057 │ ⋮ │ -1.2086955404186868 │ -1.208375090947946 └ -1.208233848018479 ┌ Warning: Variances had to be floored │ ind = │ 3-element Vector{Int64}: │ 5 │ 23 │ 28 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 2-element Vector{Int64}: │ 10 │ 24 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 2-element Vector{Int64}: │ 5 │ 28 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 1-element Vector{Int64}: │ 10 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 3-element Vector{Int64}: │ 5 │ 24 │ 28 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 2-element Vector{Int64}: │ 10 │ 23 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 2-element Vector{Int64}: │ 5 │ 28 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 2-element Vector{Int64}: │ 10 │ 24 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 2-element Vector{Int64}: │ 5 │ 28 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 3-element Vector{Int64}: │ 10 │ 22 │ 24 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 3-element Vector{Int64}: │ 5 │ 14 │ 28 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 2-element Vector{Int64}: │ 10 │ 24 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 3-element Vector{Int64}: │ 5 │ 28 │ 31 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 2-element Vector{Int64}: │ 10 │ 24 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 3-element Vector{Int64}: │ 5 │ 22 │ 28 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 2-element Vector{Int64}: │ 10 │ 24 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 4-element Vector{Int64}: │ 5 │ 14 │ 28 │ 31 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 2-element Vector{Int64}: │ 10 │ 24 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 2-element Vector{Int64}: │ 5 │ 28 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 3-element Vector{Int64}: │ 10 │ 22 │ 24 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 3-element Vector{Int64}: │ 5 │ 28 │ 31 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 3-element Vector{Int64}: │ 10 │ 14 │ 24 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 2-element Vector{Int64}: │ 5 │ 28 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 2-element Vector{Int64}: │ 10 │ 24 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 4-element Vector{Int64}: │ 5 │ 22 │ 28 │ 31 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 2-element Vector{Int64}: │ 10 │ 24 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 3-element Vector{Int64}: │ 5 │ 14 │ 28 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 2-element Vector{Int64}: │ 10 │ 24 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 3-element Vector{Int64}: │ 5 │ 28 │ 31 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 2-element Vector{Int64}: │ 10 │ 24 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 3-element Vector{Int64}: │ 5 │ 22 │ 28 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 3-element Vector{Int64}: │ 10 │ 14 │ 24 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 3-element Vector{Int64}: │ 5 │ 28 │ 31 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 2-element Vector{Int64}: │ 10 │ 24 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 2-element Vector{Int64}: │ 5 │ 28 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 3-element Vector{Int64}: │ 10 │ 22 │ 24 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 4-element Vector{Int64}: │ 5 │ 14 │ 28 │ 31 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 2-element Vector{Int64}: │ 10 │ 24 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 2-element Vector{Int64}: │ 5 │ 28 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 2-element Vector{Int64}: │ 10 │ 24 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 4-element Vector{Int64}: │ 5 │ 22 │ 28 │ 31 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 3-element Vector{Int64}: │ 10 │ 14 │ 24 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 2-element Vector{Int64}: │ 5 │ 28 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 2-element Vector{Int64}: │ 10 │ 24 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 3-element Vector{Int64}: │ 5 │ 28 │ 31 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 2-element Vector{Int64}: │ 10 │ 24 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Info: 5 │ avll = │ 50-element Vector{Float64}: │ -1.2083379710728726 │ -1.2076156602784143 │ -1.2052552065909297 │ -1.1852952464842301 │ ⋮ │ -1.1012150426811926 │ -1.0948312168371797 └ -1.1079843382008443 ┌ Info: Total log likelihood: │ tll = │ 251-element Vector{Float64}: │ -1.4524818948887939 │ -1.4525885203422815 │ -1.4525078018258681 │ -1.452200853901521 │ ⋮ │ -1.1012150426811926 │ -1.0948312168371797 └ -1.1079843382008443 ┌ Warning: Variances had to be floored │ ind = │ 4-element Vector{Int64}: │ 5 │ 14 │ 22 │ 28 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 6-element Vector{Int64}: │ 5 │ 10 │ 14 │ 22 │ 24 │ 28 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 5-element Vector{Int64}: │ 5 │ 14 │ 22 │ 28 │ 31 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 6-element Vector{Int64}: │ 5 │ 10 │ 14 │ 22 │ 24 │ 28 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 4-element Vector{Int64}: │ 5 │ 14 │ 22 │ 28 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 7-element Vector{Int64}: │ 5 │ 10 │ 14 │ 22 │ 24 │ 28 │ 31 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 4-element Vector{Int64}: │ 5 │ 14 │ 22 │ 28 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 6-element Vector{Int64}: │ 5 │ 10 │ 14 │ 22 │ 24 │ 28 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 5-element Vector{Int64}: │ 5 │ 14 │ 22 │ 28 │ 31 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 6-element Vector{Int64}: │ 5 │ 10 │ 14 │ 22 │ 24 │ 28 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 kind diag, method kmeans [ Info: Initializing GMM, 32 Gaussians diag covariance 26 dimensions using 100000 data points K-means terminated without convergence after 50 iterations (objv = 655030.8599899174) ┌ Info: K-means with 32000 data points using 50 iterations └ 37.0 data points per parameter ┌ Warning: Variances had to be floored │ ind = │ 2-element Vector{Int64}: │ 5 │ 9 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 3-element Vector{Int64}: │ 13 │ 15 │ 19 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 1-element Vector{Int64}: │ 2 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 3-element Vector{Int64}: │ 7 │ 22 │ 23 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 4-element Vector{Int64}: │ 5 │ 9 │ 24 │ 32 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 2-element Vector{Int64}: │ 13 │ 15 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 1-element Vector{Int64}: │ 2 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 4-element Vector{Int64}: │ 5 │ 19 │ 22 │ 23 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 3-element Vector{Int64}: │ 7 │ 9 │ 15 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 2-element Vector{Int64}: │ 13 │ 24 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 2-element Vector{Int64}: │ 2 │ 29 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 4-element Vector{Int64}: │ 5 │ 9 │ 19 │ 22 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 2-element Vector{Int64}: │ 7 │ 15 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 1-element Vector{Int64}: │ 13 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 5-element Vector{Int64}: │ 2 │ 5 │ 9 │ 24 │ 29 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 2-element Vector{Int64}: │ 19 │ 22 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 2-element Vector{Int64}: │ 7 │ 15 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 1-element Vector{Int64}: │ 13 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 4-element Vector{Int64}: │ 2 │ 5 │ 9 │ 29 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 2-element Vector{Int64}: │ 19 │ 22 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 2-element Vector{Int64}: │ 7 │ 15 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 3-element Vector{Int64}: │ 13 │ 24 │ 29 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 3-element Vector{Int64}: │ 2 │ 5 │ 9 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 2-element Vector{Int64}: │ 19 │ 22 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 2-element Vector{Int64}: │ 7 │ 15 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 2-element Vector{Int64}: │ 13 │ 29 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 3-element Vector{Int64}: │ 2 │ 5 │ 9 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 3-element Vector{Int64}: │ 19 │ 22 │ 24 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 2-element Vector{Int64}: │ 7 │ 15 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 2-element Vector{Int64}: │ 13 │ 29 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 3-element Vector{Int64}: │ 2 │ 5 │ 9 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 2-element Vector{Int64}: │ 19 │ 22 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 2-element Vector{Int64}: │ 7 │ 15 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 3-element Vector{Int64}: │ 13 │ 24 │ 29 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 3-element Vector{Int64}: │ 2 │ 5 │ 9 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 2-element Vector{Int64}: │ 19 │ 22 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 2-element Vector{Int64}: │ 7 │ 15 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 2-element Vector{Int64}: │ 13 │ 29 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 3-element Vector{Int64}: │ 2 │ 5 │ 9 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 3-element Vector{Int64}: │ 19 │ 22 │ 24 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 2-element Vector{Int64}: │ 7 │ 15 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 2-element Vector{Int64}: │ 13 │ 29 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 3-element Vector{Int64}: │ 2 │ 5 │ 9 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 2-element Vector{Int64}: │ 19 │ 22 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 2-element Vector{Int64}: │ 7 │ 15 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 3-element Vector{Int64}: │ 13 │ 24 │ 29 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 8-element Vector{Int64}: │ 2 │ 5 │ 9 │ 13 │ 19 │ 22 │ 24 │ 29 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 8-element Vector{Int64}: │ 2 │ 5 │ 7 │ 9 │ 13 │ 15 │ 24 │ 29 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 6-element Vector{Int64}: │ 5 │ 13 │ 19 │ 22 │ 24 │ 29 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 6-element Vector{Int64}: │ 2 │ 5 │ 9 │ 13 │ 24 │ 29 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 10-element Vector{Int64}: │ 2 │ 5 │ 7 │ 9 │ ⋮ │ 22 │ 24 │ 29 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 3-element Vector{Int64}: │ 13 │ 24 │ 29 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 8-element Vector{Int64}: │ 2 │ 5 │ 9 │ 13 │ 19 │ 22 │ 24 │ 29 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 8-element Vector{Int64}: │ 2 │ 5 │ 7 │ 9 │ 13 │ 15 │ 24 │ 29 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 6-element Vector{Int64}: │ 5 │ 13 │ 19 │ 22 │ 24 │ 29 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 kind full, method split ┌ Info: 0: avll = └ tll[1] = -1.4082316651209061 ┌ Info: 1 │ avll = │ 50-element Vector{Float64}: │ -1.4082585477658314 │ -1.4082022602483018 │ -1.4081578509841068 │ -1.4080778499098183 │ ⋮ │ -1.402753986385491 │ -1.4027539396789355 └ -1.402753907362716 ┌ Info: 2 │ avll = │ 50-element Vector{Float64}: │ -1.402778049885917 │ -1.4027184969229856 │ -1.4026706718491284 │ -1.4025923383735859 │ ⋮ │ -1.3892397836307495 │ -1.3892281524609416 └ -1.3892156895186152 ┌ Info: 3 │ avll = │ 50-element Vector{Float64}: │ -1.38923658135866 │ -1.389128034434032 │ -1.3890364682612508 │ -1.3888994394635132 │ ⋮ │ -1.3690561316828065 │ -1.3679786313954199 └ -1.3660666706783424 ┌ Info: 4 │ avll = │ 50-element Vector{Float64}: │ -1.3634066784756347 │ -1.3607750516911843 │ -1.359201821726832 │ -1.358330045965375 │ ⋮ │ -1.321551375316749 │ -1.3215034116857807 └ -1.3214191993239492 ┌ Info: 5 │ avll = │ 50-element Vector{Float64}: │ -1.3213209953428762 │ -1.320668790186992 │ -1.319527658315374 │ -1.3171842912392473 │ ⋮ │ -1.288237895076608 │ -1.288135787237579 └ -1.2881236069359074 ┌ Info: Total log likelihood: │ tll = │ 251-element Vector{Float64}: │ -1.4082316651209061 │ -1.4082585477658314 │ -1.4082022602483018 │ -1.4081578509841068 │ ⋮ │ -1.288237895076608 │ -1.288135787237579 └ -1.2881236069359074 kind full, method kmeans [ Info: Initializing GMM, 32 Gaussians diag covariance 26 dimensions using 100000 data points K-means terminated without convergence after 50 iterations (objv = 664031.7107102253) ┌ Info: K-means with 32000 data points using 50 iterations └ 37.0 data points per parameter Test Summary: | Broken Total Time train.jl | 1 1 7m31.1s [ Info: Initializing GMM, 2 Gaussians diag covariance 2 dimensions using 900 data points K-means converged with 2 iterations (objv = 7869.867369234178) ┌ Info: K-means with 900 data points using 2 iterations └ 150.0 data points per parameter Test Summary: | Pass Total Time ScikitLearnBase | 1 1 2.5s Testing GaussianMixtures tests passed Testing completed after 993.86s PkgEval succeeded after 1150.0s