Package evaluation to test GaussianMixtures on Julia 1.14.0-DEV.30 (073666df8b*) started at 2025-11-04T18:48:35.584 ################################################################################ # Set-up # Installing PkgEval dependencies (TestEnv)... Set-up completed after 8.96s ################################################################################ # 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 v0.19.2 [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 5.04s ################################################################################ # 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... 3971.4 ms ✓ Clustering 9974.6 ms ✓ Distributions 9460.1 ms ✓ GaussianMixtures 3 dependencies successfully precompiled in 26 seconds. 84 already precompiled. Precompilation completed after 37.62s ################################################################################ # Testing # Testing GaussianMixtures Status `/tmp/jl_BoYR0l/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_BoYR0l/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 v0.19.2 [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, -1.4757509691875135e6, [51291.84336720041, 48708.1566327996], [-5771.613591293281 20206.36424144674 -33947.96096299157; 5309.969098664582 -20582.646765732923 33574.143942217495], [[50272.89248526266 930.1580036023985 683.0619814393599; 930.1580036023984 50219.3158418228 422.8676027273696; 683.0619814393599 422.8676027273697 50413.21213782743], [50250.62893523267 -444.2217019380625 -325.1184006256789; -444.2217019380624 49343.75391655473 -327.2585955340643; -325.118400625679 -327.2585955340644 49777.43766447863]]) Test Summary: | Pass Total Time data.jl | 8 8 4m31.0s [ Info: Initializing GMM, 2 Gaussians diag covariance 1 dimensions using 272 data points K-means converged with 3 iterations (objv = 8855.79069767458) ┌ Info: K-means with 272 data points using 3 iterations └ 68.0 data points per parameter [ Info: Initializing GMM, 8 Gaussians diag covariance 2 dimensions using 272 data points K-means converged with 5 iterations (objv = 852.3248142738703) ┌ Info: K-means with 272 data points using 5 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[Tue Nov 4 18:56:38 2025: Initializing GMM, 8 Gaussians diag covariance 2 dimensions using 272 data points , Tue Nov 4 18:56:39 2025: K-means with 272 data points using 5 iterations 11.3 data points per parameter , Tue Nov 4 18:56:39 2025: EM with 272 data points 0 iterations avll -2.084727 5.8 data points per parameter , Tue Nov 4 18:56:47 2025: GMM converted to Variational GMM , Tue Nov 4 18:56:57 2025: iteration 1, lowerbound -3.888208 , Tue Nov 4 18:56:57 2025: iteration 2, lowerbound -3.785269 , Tue Nov 4 18:56:57 2025: iteration 3, lowerbound -3.665615 , Tue Nov 4 18:56:57 2025: iteration 4, lowerbound -3.510426 , Tue Nov 4 18:56:57 2025: iteration 5, lowerbound -3.336048 , Tue Nov 4 18:56:57 2025: iteration 6, lowerbound -3.172449 , Tue Nov 4 18:56:57 2025: iteration 7, lowerbound -3.048009 , Tue Nov 4 18:56:58 2025: dropping number of Gaussions to 6 , Tue Nov 4 18:56:58 2025: iteration 8, lowerbound -2.960626 , Tue Nov 4 18:56:58 2025: dropping number of Gaussions to 5 , Tue Nov 4 18:56:58 2025: iteration 9, lowerbound -2.877252 , Tue Nov 4 18:56:58 2025: dropping number of Gaussions to 4 , Tue Nov 4 18:56:58 2025: iteration 10, lowerbound -2.790067 , Tue Nov 4 18:56:58 2025: iteration 11, lowerbound -2.699932 , Tue Nov 4 18:56:58 2025: iteration 12, lowerbound -2.612621 , Tue Nov 4 18:56:58 2025: iteration 13, lowerbound -2.532324 , Tue Nov 4 18:56:58 2025: iteration 14, lowerbound -2.467326 , Tue Nov 4 18:56:58 2025: iteration 15, lowerbound -2.422344 , Tue Nov 4 18:56:58 2025: dropping number of Gaussions to 3 , Tue Nov 4 18:56:58 2025: iteration 16, lowerbound -2.382794 , Tue Nov 4 18:56:58 2025: iteration 17, lowerbound -2.348251 , Tue Nov 4 18:56:58 2025: iteration 18, lowerbound -2.323444 , Tue Nov 4 18:56:58 2025: iteration 19, lowerbound -2.309283 , Tue Nov 4 18:56:58 2025: iteration 20, lowerbound -2.308778 , Tue Nov 4 18:56:58 2025: dropping number of Gaussions to 2 , Tue Nov 4 18:56:58 2025: iteration 21, lowerbound -2.302914 , Tue Nov 4 18:56:58 2025: iteration 22, lowerbound -2.299258 , Tue Nov 4 18:56:58 2025: iteration 23, lowerbound -2.299255 , Tue Nov 4 18:56:58 2025: iteration 24, lowerbound -2.299254 , Tue Nov 4 18:56:58 2025: iteration 25, lowerbound -2.299253 , Tue Nov 4 18:56:58 2025: iteration 26, lowerbound -2.299253 , Tue Nov 4 18:56:58 2025: iteration 27, lowerbound -2.299253 , Tue Nov 4 18:56:58 2025: iteration 28, lowerbound -2.299253 , Tue Nov 4 18:56:58 2025: iteration 29, lowerbound -2.299253 , Tue Nov 4 18:56:58 2025: iteration 30, lowerbound -2.299253 , Tue Nov 4 18:56:58 2025: iteration 31, lowerbound -2.299253 , Tue Nov 4 18:56:58 2025: iteration 32, lowerbound -2.299253 , Tue Nov 4 18:56:58 2025: iteration 33, lowerbound -2.299253 , Tue Nov 4 18:56:58 2025: iteration 34, lowerbound -2.299253 , Tue Nov 4 18:56:58 2025: iteration 35, lowerbound -2.299253 , Tue Nov 4 18:56:58 2025: iteration 36, lowerbound -2.299253 , Tue Nov 4 18:56:58 2025: iteration 37, lowerbound -2.299253 , Tue Nov 4 18:56:58 2025: iteration 38, lowerbound -2.299253 , Tue Nov 4 18:56:58 2025: iteration 39, lowerbound -2.299253 , Tue Nov 4 18:56:58 2025: iteration 40, lowerbound -2.299253 , Tue Nov 4 18:56:58 2025: iteration 41, lowerbound -2.299253 , Tue Nov 4 18:56:58 2025: iteration 42, lowerbound -2.299253 , Tue Nov 4 18:56:58 2025: iteration 43, lowerbound -2.299253 , Tue Nov 4 18:56:58 2025: iteration 44, lowerbound -2.299253 , Tue Nov 4 18:56:58 2025: iteration 45, lowerbound -2.299253 , Tue Nov 4 18:56:58 2025: iteration 46, lowerbound -2.299253 , Tue Nov 4 18:56:58 2025: iteration 47, lowerbound -2.299253 , Tue Nov 4 18:56:58 2025: iteration 48, lowerbound -2.299253 , Tue Nov 4 18:56:58 2025: iteration 49, lowerbound -2.299253 , Tue Nov 4 18:56:58 2025: iteration 50, lowerbound -2.299253 , Tue Nov 4 18:56:58 2025: 50 variational Bayes EM-like iterations using 272 data points, final lowerbound -2.299253 ] α = [95.95490777398535, 178.0450922260147] β = [95.95490777398535, 178.0450922260147] m = [2.0002292577753633 53.85198717246125; 4.250300733269902 79.28686694436172] ν = [97.95490777398535, 180.0450922260147] W = LinearAlgebra.UpperTriangular{Float64, Matrix{Float64}}[[0.3758763611948478 -0.008953123827346103; 0.0 0.012748664777409283], [0.18404155547484088 -0.00764404904232748; 0.0 0.008581705166333251]] Test Summary: | Pass Total Time bayes.jl | 3 3 1m57.4s Kind: diag, size256 nx: 100000 sum(zeroth order stats): 99999.99999999996 avll from stats: -1.0068008194108546 avll from llpg: -1.0068008194108553 avll direct: -1.0068008194108553 sum posterior: 100000.0 Kind: full, size16 nx: 100000 sum(zeroth order stats): 100000.0 avll from stats: -0.9647303529090855 avll from llpg: -0.9647303529090855 avll direct: -0.9647303529090856 sum posterior: 100000.0 kind diag, method split ┌ Info: 0: avll = └ tll[1] = -1.4240516056486376 ┌ Info: 1 │ avll = │ 50-element Vector{Float64}: │ -1.4241233931964672 │ -1.4240490791476568 │ -1.4233570264312638 │ -1.4161422179325103 │ ⋮ │ -1.3867475080025824 │ -1.3867474769255765 └ -1.3867474509011528 ┌ Info: 2 │ avll = │ 50-element Vector{Float64}: │ -1.38685985623271 │ -1.3867586629066397 │ -1.3862615427672567 │ -1.381099557189932 │ ⋮ │ -1.3406998810179032 │ -1.3406630744884438 └ -1.340632112275153 ┌ Info: 3 │ avll = │ 50-element Vector{Float64}: │ -1.3407578496416133 │ -1.3405839006237654 │ -1.3400686852770876 │ -1.3354340183303255 │ ⋮ │ -1.2799341621748541 │ -1.2799333471925547 └ -1.2799324758373527 ┌ 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}: │ 2 └ @ 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}: │ 5 └ @ 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 = │ 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}: │ 2 └ @ 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}: │ 5 └ @ 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 = │ 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}: │ 2 └ @ 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}: │ 5 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 2-element Vector{Int64}: │ 2 │ 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 = │ 2-element Vector{Int64}: │ 2 │ 5 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Info: 4 │ avll = │ 50-element Vector{Float64}: │ -1.2801071500895944 │ -1.2798650607816642 │ -1.2783746386790702 │ -1.2666771654197058 │ ⋮ │ -1.1766325621944551 │ -1.200481876096649 └ -1.1883005225430285 ┌ Warning: Variances had to be floored │ ind = │ 2-element Vector{Int64}: │ 9 │ 10 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 2-element Vector{Int64}: │ 9 │ 10 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 2-element Vector{Int64}: │ 9 │ 10 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 4-element Vector{Int64}: │ 4 │ 9 │ 10 │ 31 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 5-element Vector{Int64}: │ 3 │ 5 │ 6 │ 9 │ 10 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 4-element Vector{Int64}: │ 9 │ 10 │ 25 │ 31 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 4-element Vector{Int64}: │ 3 │ 9 │ 10 │ 30 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 8-element Vector{Int64}: │ 2 │ 5 │ 6 │ 9 │ 10 │ 18 │ 25 │ 31 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 3-element Vector{Int64}: │ 3 │ 9 │ 10 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 5-element Vector{Int64}: │ 9 │ 10 │ 25 │ 30 │ 31 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 7-element Vector{Int64}: │ 2 │ 3 │ 5 │ 6 │ 9 │ 10 │ 18 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 4-element Vector{Int64}: │ 9 │ 10 │ 25 │ 31 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 4-element Vector{Int64}: │ 3 │ 9 │ 10 │ 30 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 8-element Vector{Int64}: │ 2 │ 5 │ 6 │ 9 │ 10 │ 18 │ 25 │ 31 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 4-element Vector{Int64}: │ 3 │ 9 │ 10 │ 27 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 5-element Vector{Int64}: │ 9 │ 10 │ 25 │ 30 │ 31 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 5-element Vector{Int64}: │ 2 │ 5 │ 6 │ 9 │ 10 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 6-element Vector{Int64}: │ 3 │ 9 │ 10 │ 18 │ 25 │ 31 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 3-element Vector{Int64}: │ 9 │ 10 │ 30 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 9-element Vector{Int64}: │ 2 │ 3 │ 5 │ 6 │ ⋮ │ 25 │ 27 │ 31 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 2-element Vector{Int64}: │ 9 │ 10 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 7-element Vector{Int64}: │ 3 │ 9 │ 10 │ 18 │ 25 │ 30 │ 31 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 4-element Vector{Int64}: │ 5 │ 6 │ 9 │ 10 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 5-element Vector{Int64}: │ 3 │ 9 │ 10 │ 25 │ 31 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 5-element Vector{Int64}: │ 2 │ 9 │ 10 │ 18 │ 30 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 8-element Vector{Int64}: │ 3 │ 5 │ 6 │ 9 │ 10 │ 25 │ 27 │ 31 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 2-element Vector{Int64}: │ 9 │ 10 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 7-element Vector{Int64}: │ 2 │ 9 │ 10 │ 18 │ 25 │ 30 │ 31 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 5-element Vector{Int64}: │ 3 │ 5 │ 6 │ 9 │ 10 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 4-element Vector{Int64}: │ 9 │ 10 │ 25 │ 31 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 7-element Vector{Int64}: │ 2 │ 3 │ 9 │ 10 │ 18 │ 27 │ 30 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 6-element Vector{Int64}: │ 5 │ 6 │ 9 │ 10 │ 25 │ 31 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 3-element Vector{Int64}: │ 3 │ 9 │ 10 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 4-element Vector{Int64}: │ 9 │ 10 │ 25 │ 31 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 7-element Vector{Int64}: │ 3 │ 5 │ 6 │ 9 │ 10 │ 18 │ 30 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 5-element Vector{Int64}: │ 2 │ 9 │ 10 │ 25 │ 31 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 4-element Vector{Int64}: │ 3 │ 9 │ 10 │ 27 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 7-element Vector{Int64}: │ 5 │ 6 │ 9 │ 10 │ 25 │ 30 │ 31 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 4-element Vector{Int64}: │ 2 │ 9 │ 10 │ 18 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 5-element Vector{Int64}: │ 3 │ 9 │ 10 │ 25 │ 31 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 5-element Vector{Int64}: │ 5 │ 6 │ 9 │ 10 │ 30 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 8-element Vector{Int64}: │ 2 │ 3 │ 9 │ 10 │ 18 │ 25 │ 27 │ 31 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 2-element Vector{Int64}: │ 9 │ 10 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 8-element Vector{Int64}: │ 3 │ 5 │ 6 │ 9 │ 10 │ 25 │ 30 │ 31 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 2-element Vector{Int64}: │ 9 │ 10 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 6-element Vector{Int64}: │ 3 │ 9 │ 10 │ 18 │ 25 │ 31 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 6-element Vector{Int64}: │ 2 │ 5 │ 6 │ 9 │ 10 │ 30 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 6-element Vector{Int64}: │ 3 │ 9 │ 10 │ 25 │ 27 │ 31 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 2-element Vector{Int64}: │ 9 │ 10 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 9-element Vector{Int64}: │ 2 │ 5 │ 6 │ 9 │ ⋮ │ 25 │ 30 │ 31 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Info: 5 │ avll = │ 50-element Vector{Float64}: │ -1.1801557216906127 │ -1.1789533490588557 │ -1.1749041872383235 │ -1.150652021650555 │ ⋮ │ -1.059956166724086 │ -1.073957601737888 └ -1.036590659928713 ┌ Info: Total log likelihood: │ tll = │ 251-element Vector{Float64}: │ -1.4240516056486376 │ -1.4241233931964672 │ -1.4240490791476568 │ -1.4233570264312638 │ ⋮ │ -1.059956166724086 │ -1.073957601737888 └ -1.036590659928713 ┌ Warning: Variances had to be floored │ ind = │ 3-element Vector{Int64}: │ 3 │ 9 │ 10 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 5-element Vector{Int64}: │ 3 │ 9 │ 10 │ 25 │ 31 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 9-element Vector{Int64}: │ 2 │ 3 │ 5 │ 6 │ ⋮ │ 18 │ 27 │ 30 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 5-element Vector{Int64}: │ 3 │ 9 │ 10 │ 25 │ 31 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 3-element Vector{Int64}: │ 3 │ 9 │ 10 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 11-element Vector{Int64}: │ 2 │ 3 │ 5 │ 6 │ ⋮ │ 27 │ 30 │ 31 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 3-element Vector{Int64}: │ 3 │ 9 │ 10 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 5-element Vector{Int64}: │ 3 │ 9 │ 10 │ 25 │ 31 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 9-element Vector{Int64}: │ 2 │ 3 │ 5 │ 6 │ ⋮ │ 18 │ 27 │ 30 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 5-element Vector{Int64}: │ 3 │ 9 │ 10 │ 25 │ 31 └ @ 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 = 624470.6349268309) ┌ 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}: │ 7 │ 23 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 1-element Vector{Int64}: │ 16 └ @ 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}: │ 4 │ 6 │ 27 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 6-element Vector{Int64}: │ 5 │ 7 │ 11 │ 23 │ 28 │ 30 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 2-element Vector{Int64}: │ 16 │ 20 └ @ 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}: │ 6 │ 24 │ 27 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 4-element Vector{Int64}: │ 11 │ 23 │ 28 │ 30 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 3-element Vector{Int64}: │ 7 │ 8 │ 16 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 3-element Vector{Int64}: │ 2 │ 4 │ 20 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 1-element Vector{Int64}: │ 6 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 5-element Vector{Int64}: │ 11 │ 23 │ 27 │ 28 │ 30 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 3-element Vector{Int64}: │ 2 │ 7 │ 16 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 1-element Vector{Int64}: │ 8 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 4-element Vector{Int64}: │ 6 │ 20 │ 21 │ 30 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 3-element Vector{Int64}: │ 4 │ 23 │ 28 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 4-element Vector{Int64}: │ 2 │ 7 │ 11 │ 16 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 1-element Vector{Int64}: │ 8 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 3-element Vector{Int64}: │ 6 │ 21 │ 30 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 4-element Vector{Int64}: │ 4 │ 20 │ 23 │ 27 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 3-element Vector{Int64}: │ 2 │ 7 │ 16 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 1-element Vector{Int64}: │ 28 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 5-element Vector{Int64}: │ 8 │ 11 │ 21 │ 23 │ 30 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 3-element Vector{Int64}: │ 4 │ 6 │ 27 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 4-element Vector{Int64}: │ 2 │ 7 │ 16 │ 20 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 5-element Vector{Int64}: │ 21 │ 23 │ 27 │ 28 │ 30 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 3-element Vector{Int64}: │ 6 │ 8 │ 11 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 2-element Vector{Int64}: │ 2 │ 7 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 3-element Vector{Int64}: │ 4 │ 16 │ 20 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 3-element Vector{Int64}: │ 21 │ 23 │ 30 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 3-element Vector{Int64}: │ 2 │ 6 │ 28 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 4-element Vector{Int64}: │ 7 │ 8 │ 11 │ 16 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 2-element Vector{Int64}: │ 21 │ 27 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 3-element Vector{Int64}: │ 20 │ 23 │ 30 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 3-element Vector{Int64}: │ 2 │ 4 │ 6 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 3-element Vector{Int64}: │ 16 │ 21 │ 28 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 2-element Vector{Int64}: │ 8 │ 11 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 5-element Vector{Int64}: │ 7 │ 20 │ 23 │ 27 │ 30 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 3-element Vector{Int64}: │ 2 │ 4 │ 6 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 2-element Vector{Int64}: │ 21 │ 28 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 3-element Vector{Int64}: │ 8 │ 11 │ 16 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 3-element Vector{Int64}: │ 20 │ 23 │ 27 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 4-element Vector{Int64}: │ 2 │ 6 │ 7 │ 30 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 3-element Vector{Int64}: │ 16 │ 21 │ 28 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 7-element Vector{Int64}: │ 4 │ 8 │ 11 │ 16 │ 21 │ 23 │ 28 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 3-element Vector{Int64}: │ 16 │ 21 │ 28 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 11-element Vector{Int64}: │ 2 │ 6 │ 7 │ 8 │ ⋮ │ 23 │ 27 │ 28 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 5-element Vector{Int64}: │ 4 │ 16 │ 21 │ 28 │ 30 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 6-element Vector{Int64}: │ 8 │ 11 │ 16 │ 21 │ 23 │ 28 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 8-element Vector{Int64}: │ 2 │ 4 │ 6 │ 16 │ 20 │ 21 │ 27 │ 28 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 7-element Vector{Int64}: │ 8 │ 11 │ 16 │ 21 │ 23 │ 28 │ 30 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 3-element Vector{Int64}: │ 16 │ 21 │ 28 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 11-element Vector{Int64}: │ 2 │ 4 │ 6 │ 8 │ ⋮ │ 23 │ 27 │ 28 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 kind full, method split ┌ Info: 0: avll = └ tll[1] = -1.415803556642471 ┌ Info: 1 │ avll = │ 50-element Vector{Float64}: │ -1.4158301613964104 │ -1.4157758828806328 │ -1.4157375734679467 │ -1.4156764678556013 │ ⋮ │ -1.4101890410824383 │ -1.4101876754728986 └ -1.410186643928518 ┌ Info: 2 │ avll = │ 50-element Vector{Float64}: │ -1.4102094776908143 │ -1.4101538693405091 │ -1.4101128540108274 │ -1.4100518009528407 │ ⋮ │ -1.4030104592435724 │ -1.402938224618748 └ -1.4028565864239586 ┌ Info: 3 │ avll = │ 50-element Vector{Float64}: │ -1.402805448176174 │ -1.4025715161117476 │ -1.4022749551619031 │ -1.4014128374715733 │ ⋮ │ -1.3487674061609232 │ -1.3486943060755294 └ -1.3486262018262505 ┌ Info: 4 │ avll = │ 50-element Vector{Float64}: │ -1.3486211405678357 │ -1.3483503015131482 │ -1.3480743392646464 │ -1.3472975062657095 │ ⋮ │ -1.3207927384004046 │ -1.3206076283329995 └ -1.3204135214760977 ┌ Info: 5 │ avll = │ 50-element Vector{Float64}: │ -1.320317428263949 │ -1.3198687473593724 │ -1.3192308559127026 │ -1.3159086949275864 │ ⋮ │ -1.2508721919791155 │ -1.2508631675062383 └ -1.250854211592687 ┌ Info: Total log likelihood: │ tll = │ 251-element Vector{Float64}: │ -1.415803556642471 │ -1.4158301613964104 │ -1.4157758828806328 │ -1.4157375734679467 │ ⋮ │ -1.2508721919791155 │ -1.2508631675062383 └ -1.250854211592687 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 = 674903.9231995612) ┌ 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 8m22.6s [ 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 2.7s Testing GaussianMixtures tests passed Testing completed after 956.14s PkgEval succeeded after 1021.4s