Package evaluation of GaussianMixtures on Julia 1.13.0-DEV.811 (41570e9800*) started at 2025-07-03T17:45:15.216 ################################################################################ # Set-up # Installing PkgEval dependencies (TestEnv)... Set-up completed after 8.2s ################################################################################ # Installation # Installing GaussianMixtures... Resolving package versions... Updating `~/.julia/environments/v1.13/Project.toml` [cc18c42c] + GaussianMixtures v0.3.13 Updating `~/.julia/environments/v1.13/Manifest.toml` [66dad0bd] + AliasTables v1.1.3 [7d9fca2a] + Arpack v0.5.4 [aaaa29a8] + Clustering v0.15.8 [34da2185] + Compat v4.17.0 [9a962f9c] + DataAPI v1.16.0 [864edb3b] + DataStructures v0.18.22 [8bb1440f] + DelimitedFiles v1.9.1 [b4f34e82] + Distances v0.10.12 [31c24e10] + Distributions v0.25.120 [ffbed154] + DocStringExtensions v0.9.5 [5789e2e9] + FileIO v1.17.0 [1a297f60] + FillArrays v1.13.0 [cc18c42c] + GaussianMixtures v0.3.13 [076d061b] + HashArrayMappedTries v0.2.0 [34004b35] + HypergeometricFunctions v0.3.28 [92d709cd] + IrrationalConstants v0.2.4 [033835bb] + JLD2 v0.5.15 [692b3bcd] + JLLWrappers v1.7.0 [2ab3a3ac] + LogExpFunctions v0.3.29 [1914dd2f] + MacroTools v0.5.16 [e1d29d7a] + Missings v1.2.0 [b8a86587] + NearestNeighbors v0.4.21 [bac558e1] + OrderedCollections v1.8.1 [90014a1f] + PDMats v0.11.35 [aea7be01] + PrecompileTools v1.3.2 [21216c6a] + Preferences v1.4.3 [43287f4e] + PtrArrays v1.3.0 [1fd47b50] + QuadGK v2.11.2 [189a3867] + Reexport v1.2.2 [ae029012] + Requires v1.3.1 [79098fc4] + Rmath v0.8.0 [6e75b9c4] + ScikitLearnBase v0.5.0 [7e506255] + ScopedValues v1.3.0 [a2af1166] + SortingAlgorithms v1.2.1 [276daf66] + SpecialFunctions v2.5.1 [90137ffa] + StaticArrays v1.9.13 [1e83bf80] + StaticArraysCore v1.4.3 [10745b16] + Statistics v1.11.1 [82ae8749] + StatsAPI v1.7.1 [2913bbd2] + StatsBase v0.34.5 [4c63d2b9] + StatsFuns v1.5.0 [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 [b77e0a4c] + InteractiveUtils v1.11.0 [ac6e5ff7] + JuliaSyntaxHighlighting v1.12.0 [b27032c2] + LibCURL v0.6.4 [76f85450] + LibGit2 v1.11.0 [8f399da3] + Libdl v1.11.0 [37e2e46d] + LinearAlgebra v1.12.0 [56ddb016] + Logging v1.11.0 [d6f4376e] + Markdown v1.11.0 [a63ad114] + Mmap v1.11.0 [ca575930] + NetworkOptions v1.3.0 [44cfe95a] + Pkg v1.13.0 [de0858da] + Printf v1.11.0 [9a3f8284] + Random v1.11.0 [ea8e919c] + SHA v0.7.0 [9e88b42a] + Serialization v1.11.0 [6462fe0b] + Sockets v1.11.0 [2f01184e] + SparseArrays v1.12.0 [f489334b] + StyledStrings v1.11.0 [4607b0f0] + SuiteSparse [fa267f1f] + TOML v1.0.3 [a4e569a6] + Tar v1.10.0 [cf7118a7] + UUIDs v1.11.0 [4ec0a83e] + Unicode v1.11.0 [e66e0078] + CompilerSupportLibraries_jll v1.3.0+1 [deac9b47] + LibCURL_jll v8.14.1+1 [e37daf67] + LibGit2_jll v1.9.1+0 [29816b5a] + LibSSH2_jll v1.11.3+1 [14a3606d] + MozillaCACerts_jll v2025.5.20 [4536629a] + OpenBLAS_jll v0.3.29+0 [05823500] + OpenLibm_jll v0.8.5+0 [458c3c95] + OpenSSL_jll v3.5.1+0 [efcefdf7] + PCRE2_jll v10.45.0+0 [bea87d4a] + SuiteSparse_jll v7.10.1+0 [83775a58] + Zlib_jll v1.3.1+2 [8e850b90] + libblastrampoline_jll v5.13.1+0 [8e850ede] + nghttp2_jll v1.65.0+0 [3f19e933] + p7zip_jll v17.5.0+2 Info Packages marked with ⌅ have new versions available but compatibility constraints restrict them from upgrading. To see why use `status --outdated -m` Installation completed after 4.31s ################################################################################ # Precompilation # Precompiling PkgEval dependencies... Precompiling package dependencies... Precompilation completed after 45.03s ################################################################################ # Testing # Testing GaussianMixtures Status `/tmp/jl_ytYKts/Project.toml` [7d9fca2a] Arpack v0.5.4 [aaaa29a8] Clustering v0.15.8 [34da2185] Compat v4.17.0 [8bb1440f] DelimitedFiles v1.9.1 [31c24e10] Distributions v0.25.120 [5789e2e9] FileIO v1.17.0 [cc18c42c] GaussianMixtures v0.3.13 [033835bb] JLD2 v0.5.15 [90014a1f] PDMats v0.11.35 [ce6b1742] RDatasets v0.7.7 [6e75b9c4] ScikitLearnBase v0.5.0 [276daf66] SpecialFunctions v2.5.1 [10745b16] Statistics v1.11.1 [2913bbd2] StatsBase v0.34.5 [8ba89e20] Distributed v1.11.0 [37e2e46d] LinearAlgebra v1.12.0 [56ddb016] Logging v1.11.0 [de0858da] Printf v1.11.0 [9a3f8284] Random v1.11.0 [8dfed614] Test v1.11.0 Status `/tmp/jl_ytYKts/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 v4.17.0 [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 [b4f34e82] Distances v0.10.12 [31c24e10] Distributions v0.25.120 [ffbed154] DocStringExtensions v0.9.5 [e2ba6199] ExprTools v0.1.10 [5789e2e9] FileIO v1.17.0 [48062228] FilePathsBase v0.9.24 [1a297f60] FillArrays v1.13.0 [cc18c42c] GaussianMixtures v0.3.13 [076d061b] HashArrayMappedTries v0.2.0 [34004b35] HypergeometricFunctions v0.3.28 [842dd82b] InlineStrings v1.4.4 [41ab1584] InvertedIndices v1.3.1 [92d709cd] IrrationalConstants v0.2.4 [82899510] IteratorInterfaceExtensions v1.0.0 [033835bb] JLD2 v0.5.15 [692b3bcd] JLLWrappers v1.7.0 [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 v0.4.21 [bac558e1] OrderedCollections v1.8.1 [90014a1f] PDMats v0.11.35 [69de0a69] Parsers v2.8.3 [2dfb63ee] PooledArrays v1.4.3 [aea7be01] PrecompileTools v1.3.2 [21216c6a] Preferences v1.4.3 [08abe8d2] PrettyTables v2.4.0 [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 v0.8.0 [6e75b9c4] ScikitLearnBase v0.5.0 [7e506255] ScopedValues v1.3.0 [6c6a2e73] Scratch v1.3.0 [91c51154] SentinelArrays v1.4.8 [a2af1166] SortingAlgorithms v1.2.1 [276daf66] SpecialFunctions v2.5.1 [90137ffa] StaticArrays v1.9.13 [1e83bf80] StaticArraysCore v1.4.3 [10745b16] Statistics v1.11.1 [82ae8749] StatsAPI v1.7.1 [2913bbd2] StatsBase v0.34.5 [4c63d2b9] StatsFuns v1.5.0 [892a3eda] StringManipulation v0.4.1 [dc5dba14] TZJData v1.5.0+2025b [3783bdb8] TableTraits v1.0.1 [bd369af6] Tables v1.12.1 [f269a46b] TimeZones v1.21.3 [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 v0.6.4 [76f85450] LibGit2 v1.11.0 [8f399da3] Libdl v1.11.0 [37e2e46d] LinearAlgebra v1.12.0 [56ddb016] Logging v1.11.0 [d6f4376e] Markdown v1.11.0 [a63ad114] Mmap v1.11.0 [ca575930] NetworkOptions v1.3.0 [44cfe95a] Pkg v1.13.0 [de0858da] Printf v1.11.0 [9a3f8284] Random v1.11.0 [ea8e919c] SHA v0.7.0 [9e88b42a] Serialization v1.11.0 [6462fe0b] Sockets v1.11.0 [2f01184e] SparseArrays v1.12.0 [f489334b] StyledStrings v1.11.0 [4607b0f0] SuiteSparse [fa267f1f] TOML v1.0.3 [a4e569a6] Tar v1.10.0 [8dfed614] Test v1.11.0 [cf7118a7] UUIDs v1.11.0 [4ec0a83e] Unicode v1.11.0 [e66e0078] CompilerSupportLibraries_jll v1.3.0+1 [deac9b47] LibCURL_jll v8.14.1+1 [e37daf67] LibGit2_jll v1.9.1+0 [29816b5a] LibSSH2_jll v1.11.3+1 [14a3606d] MozillaCACerts_jll v2025.5.20 [4536629a] OpenBLAS_jll v0.3.29+0 [05823500] OpenLibm_jll v0.8.5+0 [458c3c95] OpenSSL_jll v3.5.1+0 [efcefdf7] PCRE2_jll v10.45.0+0 [bea87d4a] SuiteSparse_jll v7.10.1+0 [83775a58] Zlib_jll v1.3.1+2 [8e850b90] libblastrampoline_jll v5.13.1+0 [8e850ede] nghttp2_jll v1.65.0+0 [3f19e933] p7zip_jll v17.5.0+2 Info Packages marked with ⌅ have new versions available but compatibility constraints restrict them from upgrading. Testing Running tests... Precompiling packages... 62875.9 ms ✓ GaussianMixtures 1 dependency successfully precompiled in 65 seconds. 85 already precompiled. Precompiling packages... 27934.1 ms ✓ RData 26016.0 ms ✓ CSV 22023.5 ms ✓ RDatasets 3 dependencies successfully precompiled in 77 seconds. 70 already precompiled. (100000, -991828.8770850444, [20053.932163230813, 79946.06783676919], [-11196.273332530003 5541.693399583098 -12820.976021649138; 11422.588869486784 -5727.732344615967 12442.627474575835], [[12792.175660921546 -1483.241217595384 -1997.309555382892; -1483.241217595384 15884.444525945068 -7004.4165439604385; -1997.309555382892 -7004.4165439604385 29439.686780247237], [86861.15877411277 1402.6795151666556 1751.4732936298224; 1402.6795151666556 84411.18954254956 6925.209147982762; 1751.4732936298226 6925.209147982762 71203.65429347554]]) Test Summary: | Pass Total Time data.jl | 8 8 4m46.6s [ 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 7 iterations (objv = 900.511247316098) ┌ Info: K-means with 272 data points using 7 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:701 [inlined] └ @ Core ./broadcast.jl:701 ┌ 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:701 [inlined] └ @ Core ./broadcast.jl:701 ┌ Warning: `lgamma(x::Real)` is deprecated, use `(logabsgamma(x))[1]` instead. │ caller = _broadcast_getindex_evalf at broadcast.jl:701 [inlined] └ @ Core ./broadcast.jl:701 History[Thu Jul 3 17:55:52 2025: Initializing GMM, 8 Gaussians diag covariance 2 dimensions using 272 data points , Thu Jul 3 17:55:54 2025: K-means with 272 data points using 7 iterations 11.3 data points per parameter , Thu Jul 3 17:55:54 2025: EM with 272 data points 0 iterations avll -2.075865 5.8 data points per parameter , Thu Jul 3 17:56:01 2025: GMM converted to Variational GMM , Thu Jul 3 17:56:13 2025: iteration 1, lowerbound -3.794054 , Thu Jul 3 17:56:13 2025: iteration 2, lowerbound -3.645538 , Thu Jul 3 17:56:13 2025: iteration 3, lowerbound -3.484707 , Thu Jul 3 17:56:13 2025: iteration 4, lowerbound -3.300915 , Thu Jul 3 17:56:13 2025: iteration 5, lowerbound -3.118718 , Thu Jul 3 17:56:13 2025: iteration 6, lowerbound -2.970408 , Thu Jul 3 17:56:14 2025: dropping number of Gaussions to 7 , Thu Jul 3 17:56:14 2025: iteration 7, lowerbound -2.867358 , Thu Jul 3 17:56:14 2025: dropping number of Gaussions to 6 , Thu Jul 3 17:56:14 2025: iteration 8, lowerbound -2.810434 , Thu Jul 3 17:56:14 2025: dropping number of Gaussions to 5 , Thu Jul 3 17:56:14 2025: iteration 9, lowerbound -2.797870 , Thu Jul 3 17:56:14 2025: dropping number of Gaussions to 3 , Thu Jul 3 17:56:14 2025: iteration 10, lowerbound -2.779378 , Thu Jul 3 17:56:14 2025: iteration 11, lowerbound -2.763700 , Thu Jul 3 17:56:14 2025: iteration 12, lowerbound -2.750304 , Thu Jul 3 17:56:14 2025: iteration 13, lowerbound -2.729211 , Thu Jul 3 17:56:14 2025: iteration 14, lowerbound -2.697057 , Thu Jul 3 17:56:14 2025: iteration 15, lowerbound -2.650881 , Thu Jul 3 17:56:14 2025: iteration 16, lowerbound -2.590663 , Thu Jul 3 17:56:14 2025: iteration 17, lowerbound -2.522281 , Thu Jul 3 17:56:14 2025: iteration 18, lowerbound -2.456572 , Thu Jul 3 17:56:14 2025: iteration 19, lowerbound -2.402338 , Thu Jul 3 17:56:14 2025: iteration 20, lowerbound -2.361246 , Thu Jul 3 17:56:14 2025: iteration 21, lowerbound -2.331239 , Thu Jul 3 17:56:14 2025: iteration 22, lowerbound -2.312529 , Thu Jul 3 17:56:14 2025: iteration 23, lowerbound -2.307533 , Thu Jul 3 17:56:14 2025: dropping number of Gaussions to 2 , Thu Jul 3 17:56:14 2025: iteration 24, lowerbound -2.302923 , Thu Jul 3 17:56:14 2025: iteration 25, lowerbound -2.299260 , Thu Jul 3 17:56:14 2025: iteration 26, lowerbound -2.299256 , Thu Jul 3 17:56:14 2025: iteration 27, lowerbound -2.299254 , Thu Jul 3 17:56:14 2025: iteration 28, lowerbound -2.299254 , Thu Jul 3 17:56:14 2025: iteration 29, lowerbound -2.299253 , Thu Jul 3 17:56:14 2025: iteration 30, lowerbound -2.299253 , Thu Jul 3 17:56:14 2025: iteration 31, lowerbound -2.299253 , Thu Jul 3 17:56:14 2025: iteration 32, lowerbound -2.299253 , Thu Jul 3 17:56:14 2025: iteration 33, lowerbound -2.299253 , Thu Jul 3 17:56:14 2025: iteration 34, lowerbound -2.299253 , Thu Jul 3 17:56:14 2025: iteration 35, lowerbound -2.299253 , Thu Jul 3 17:56:14 2025: iteration 36, lowerbound -2.299253 , Thu Jul 3 17:56:14 2025: iteration 37, lowerbound -2.299253 , Thu Jul 3 17:56:14 2025: iteration 38, lowerbound -2.299253 , Thu Jul 3 17:56:14 2025: iteration 39, lowerbound -2.299253 , Thu Jul 3 17:56:14 2025: iteration 40, lowerbound -2.299253 , Thu Jul 3 17:56:14 2025: iteration 41, lowerbound -2.299253 , Thu Jul 3 17:56:14 2025: iteration 42, lowerbound -2.299253 , Thu Jul 3 17:56:14 2025: iteration 43, lowerbound -2.299253 , Thu Jul 3 17:56:14 2025: iteration 44, lowerbound -2.299253 , Thu Jul 3 17:56:14 2025: iteration 45, lowerbound -2.299253 , Thu Jul 3 17:56:14 2025: iteration 46, lowerbound -2.299253 , Thu Jul 3 17:56:14 2025: iteration 47, lowerbound -2.299253 , Thu Jul 3 17:56:14 2025: iteration 48, lowerbound -2.299253 , Thu Jul 3 17:56:14 2025: iteration 49, lowerbound -2.299253 , Thu Jul 3 17:56:14 2025: iteration 50, lowerbound -2.299253 , Thu Jul 3 17:56:14 2025: 50 variational Bayes EM-like iterations using 272 data points, final lowerbound -2.299253 ] α = [95.95490777397141, 178.04509222602857] β = [95.95490777397141, 178.04509222602857] m = [2.0002292577752465 53.851987172460625; 4.250300733269792 79.28686694436009] ν = [97.95490777397141, 180.04509222602857] W = LinearAlgebra.UpperTriangular{Float64, Matrix{Float64}}[[0.3758763611950516 -0.008953123827348534; 0.0 0.012748664777409702], [0.18404155547482814 -0.0076440490423284975; 0.0 0.008581705166331272]] Test Summary: | Pass Total Time bayes.jl | 3 3 2m02.8s Kind: diag, size256 nx: 100000 sum(zeroth order stats): 100000.0 avll from stats: -1.0024159774515997 avll from llpg: -1.0024159774516026 avll direct: -1.0024159774516024 sum posterior: 100000.0 Kind: full, size16 nx: 100000 sum(zeroth order stats): 100000.0 avll from stats: -0.9819057808242978 avll from llpg: -0.9819057808242978 avll direct: -0.9819057808242978 sum posterior: 100000.0 kind diag, method split ┌ Info: 0: avll = └ tll[1] = -1.428181406849861 ┌ Info: 1 │ avll = │ 50-element Vector{Float64}: │ -1.4282395486505013 │ -1.4281584119790411 │ -1.4276064037168643 │ -1.4232661826501285 │ ⋮ │ -1.397477019804122 │ -1.39747701008749 └ -1.397477003502805 ┌ Info: 2 │ avll = │ 50-element Vector{Float64}: │ -1.397568688767271 │ -1.3974735598578714 │ -1.3970192647701511 │ -1.3926178600311026 │ ⋮ │ -1.3596252490136758 │ -1.3596249284499458 └ -1.3596246444701099 ┌ Info: 3 │ avll = │ 50-element Vector{Float64}: │ -1.3597438078550559 │ -1.359611679291043 │ -1.3591001269587175 │ -1.3551984336094594 │ ⋮ │ -1.3056362031691884 │ -1.3056345752158784 └ -1.3056332230911107 ┌ Warning: Variances had to be floored │ ind = │ 1-element Vector{Int64}: │ 14 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 1-element Vector{Int64}: │ 14 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 2-element Vector{Int64}: │ 13 │ 14 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 1-element Vector{Int64}: │ 14 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 3-element Vector{Int64}: │ 12 │ 13 │ 14 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 3-element Vector{Int64}: │ 5 │ 10 │ 14 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 2-element Vector{Int64}: │ 13 │ 14 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 1-element Vector{Int64}: │ 14 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 3-element Vector{Int64}: │ 12 │ 13 │ 14 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 2-element Vector{Int64}: │ 10 │ 14 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 3-element Vector{Int64}: │ 5 │ 13 │ 14 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 1-element Vector{Int64}: │ 14 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 3-element Vector{Int64}: │ 12 │ 13 │ 14 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 2-element Vector{Int64}: │ 10 │ 14 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 2-element Vector{Int64}: │ 13 │ 14 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 2-element Vector{Int64}: │ 5 │ 14 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 3-element Vector{Int64}: │ 12 │ 13 │ 14 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 2-element Vector{Int64}: │ 10 │ 14 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 2-element Vector{Int64}: │ 13 │ 14 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 1-element Vector{Int64}: │ 14 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 4-element Vector{Int64}: │ 5 │ 12 │ 13 │ 14 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 2-element Vector{Int64}: │ 10 │ 14 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 2-element Vector{Int64}: │ 13 │ 14 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 1-element Vector{Int64}: │ 14 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 3-element Vector{Int64}: │ 12 │ 13 │ 14 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 3-element Vector{Int64}: │ 5 │ 10 │ 14 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 2-element Vector{Int64}: │ 13 │ 14 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 1-element Vector{Int64}: │ 14 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 3-element Vector{Int64}: │ 12 │ 13 │ 14 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 2-element Vector{Int64}: │ 10 │ 14 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 3-element Vector{Int64}: │ 5 │ 13 │ 14 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 1-element Vector{Int64}: │ 14 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 3-element Vector{Int64}: │ 12 │ 13 │ 14 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 2-element Vector{Int64}: │ 10 │ 14 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 2-element Vector{Int64}: │ 13 │ 14 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 2-element Vector{Int64}: │ 5 │ 14 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 3-element Vector{Int64}: │ 12 │ 13 │ 14 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 2-element Vector{Int64}: │ 10 │ 14 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 2-element Vector{Int64}: │ 13 │ 14 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 1-element Vector{Int64}: │ 14 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 4-element Vector{Int64}: │ 5 │ 12 │ 13 │ 14 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 2-element Vector{Int64}: │ 10 │ 14 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 2-element Vector{Int64}: │ 13 │ 14 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 1-element Vector{Int64}: │ 14 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 3-element Vector{Int64}: │ 12 │ 13 │ 14 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 3-element Vector{Int64}: │ 5 │ 10 │ 14 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 2-element Vector{Int64}: │ 13 │ 14 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 1-element Vector{Int64}: │ 14 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Info: 4 │ avll = │ 50-element Vector{Float64}: │ -1.3058022567983347 │ -1.3055687095805115 │ -1.3039728641245267 │ -1.2920579158123617 │ ⋮ │ -1.2273544599562232 │ -1.2364760161525974 └ -1.2282430795325785 ┌ Warning: Variances had to be floored │ ind = │ 6-element Vector{Int64}: │ 23 │ 24 │ 25 │ 26 │ 27 │ 28 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 8-element Vector{Int64}: │ 19 │ 20 │ 23 │ 24 │ 25 │ 26 │ 27 │ 28 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 8-element Vector{Int64}: │ 9 │ 10 │ 23 │ 24 │ 25 │ 26 │ 27 │ 28 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 9-element Vector{Int64}: │ 19 │ 20 │ 23 │ 24 │ ⋮ │ 27 │ 28 │ 30 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 8-element Vector{Int64}: │ 9 │ 10 │ 23 │ 24 │ 25 │ 26 │ 27 │ 28 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 11-element Vector{Int64}: │ 14 │ 19 │ 20 │ 23 │ ⋮ │ 28 │ 29 │ 30 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 8-element Vector{Int64}: │ 9 │ 10 │ 23 │ 24 │ 25 │ 26 │ 27 │ 28 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 9-element Vector{Int64}: │ 19 │ 20 │ 23 │ 24 │ ⋮ │ 27 │ 28 │ 30 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 11-element Vector{Int64}: │ 7 │ 9 │ 10 │ 14 │ ⋮ │ 27 │ 28 │ 29 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 9-element Vector{Int64}: │ 19 │ 20 │ 23 │ 24 │ ⋮ │ 27 │ 28 │ 30 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 9-element Vector{Int64}: │ 3 │ 9 │ 10 │ 23 │ ⋮ │ 26 │ 27 │ 28 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 11-element Vector{Int64}: │ 14 │ 19 │ 20 │ 23 │ ⋮ │ 28 │ 29 │ 30 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 8-element Vector{Int64}: │ 9 │ 10 │ 23 │ 24 │ 25 │ 26 │ 27 │ 28 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 10-element Vector{Int64}: │ 7 │ 19 │ 20 │ 23 │ ⋮ │ 27 │ 28 │ 30 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 10-element Vector{Int64}: │ 9 │ 10 │ 14 │ 23 │ ⋮ │ 27 │ 28 │ 29 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 9-element Vector{Int64}: │ 19 │ 20 │ 23 │ 24 │ ⋮ │ 27 │ 28 │ 30 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 8-element Vector{Int64}: │ 9 │ 10 │ 23 │ 24 │ 25 │ 26 │ 27 │ 28 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 12-element Vector{Int64}: │ 7 │ 14 │ 19 │ 20 │ ⋮ │ 28 │ 29 │ 30 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 8-element Vector{Int64}: │ 9 │ 10 │ 23 │ 24 │ 25 │ 26 │ 27 │ 28 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 9-element Vector{Int64}: │ 19 │ 20 │ 23 │ 24 │ ⋮ │ 27 │ 28 │ 30 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 10-element Vector{Int64}: │ 9 │ 10 │ 14 │ 23 │ ⋮ │ 27 │ 28 │ 29 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 9-element Vector{Int64}: │ 7 │ 19 │ 20 │ 23 │ ⋮ │ 27 │ 28 │ 30 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 10-element Vector{Int64}: │ 9 │ 10 │ 19 │ 20 │ ⋮ │ 27 │ 28 │ 29 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 10-element Vector{Int64}: │ 14 │ 19 │ 20 │ 22 │ ⋮ │ 27 │ 28 │ 30 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 7-element Vector{Int64}: │ 9 │ 10 │ 23 │ 24 │ 25 │ 27 │ 28 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 11-element Vector{Int64}: │ 7 │ 19 │ 20 │ 23 │ ⋮ │ 28 │ 29 │ 30 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 11-element Vector{Int64}: │ 9 │ 10 │ 14 │ 19 │ ⋮ │ 26 │ 27 │ 28 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 10-element Vector{Int64}: │ 19 │ 20 │ 22 │ 23 │ ⋮ │ 27 │ 28 │ 30 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 8-element Vector{Int64}: │ 9 │ 10 │ 23 │ 24 │ 26 │ 27 │ 28 │ 29 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 10-element Vector{Int64}: │ 7 │ 14 │ 19 │ 20 │ ⋮ │ 27 │ 28 │ 30 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 10-element Vector{Int64}: │ 9 │ 10 │ 19 │ 20 │ ⋮ │ 27 │ 28 │ 29 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 9-element Vector{Int64}: │ 19 │ 20 │ 22 │ 23 │ ⋮ │ 27 │ 28 │ 30 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 8-element Vector{Int64}: │ 9 │ 10 │ 14 │ 23 │ 24 │ 25 │ 27 │ 28 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 10-element Vector{Int64}: │ 7 │ 19 │ 20 │ 23 │ ⋮ │ 28 │ 29 │ 30 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 9-element Vector{Int64}: │ 9 │ 10 │ 19 │ 20 │ ⋮ │ 25 │ 27 │ 28 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 10-element Vector{Int64}: │ 14 │ 19 │ 20 │ 22 │ ⋮ │ 27 │ 28 │ 30 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 8-element Vector{Int64}: │ 9 │ 10 │ 23 │ 24 │ 25 │ 27 │ 28 │ 29 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 10-element Vector{Int64}: │ 7 │ 19 │ 20 │ 23 │ ⋮ │ 27 │ 28 │ 30 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 12-element Vector{Int64}: │ 9 │ 10 │ 14 │ 19 │ ⋮ │ 27 │ 28 │ 29 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 10-element Vector{Int64}: │ 19 │ 20 │ 22 │ 23 │ ⋮ │ 27 │ 28 │ 30 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 7-element Vector{Int64}: │ 9 │ 10 │ 23 │ 24 │ 26 │ 27 │ 28 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 11-element Vector{Int64}: │ 7 │ 14 │ 19 │ 20 │ ⋮ │ 28 │ 29 │ 30 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 10-element Vector{Int64}: │ 9 │ 10 │ 19 │ 20 │ ⋮ │ 26 │ 27 │ 28 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 10-element Vector{Int64}: │ 19 │ 20 │ 22 │ 23 │ ⋮ │ 27 │ 28 │ 30 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 10-element Vector{Int64}: │ 9 │ 10 │ 14 │ 23 │ ⋮ │ 27 │ 28 │ 29 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 10-element Vector{Int64}: │ 7 │ 19 │ 20 │ 23 │ ⋮ │ 27 │ 28 │ 30 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 11-element Vector{Int64}: │ 9 │ 10 │ 19 │ 20 │ ⋮ │ 27 │ 28 │ 29 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 11-element Vector{Int64}: │ 14 │ 19 │ 20 │ 22 │ ⋮ │ 27 │ 28 │ 30 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 8-element Vector{Int64}: │ 9 │ 10 │ 23 │ 24 │ 25 │ 26 │ 27 │ 28 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 11-element Vector{Int64}: │ 7 │ 19 │ 20 │ 23 │ ⋮ │ 28 │ 29 │ 30 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Info: 5 │ avll = │ 50-element Vector{Float64}: │ -1.2203841741850838 │ -1.2165998108021001 │ -1.2161123013994612 │ -1.2074601439833565 │ ⋮ │ -1.1314700758415444 │ -1.1411550827931505 └ -1.1281186564841013 ┌ Info: Total log likelihood: │ tll = │ 251-element Vector{Float64}: │ -1.428181406849861 │ -1.4282395486505013 │ -1.4281584119790411 │ -1.4276064037168643 │ ⋮ │ -1.1314700758415444 │ -1.1411550827931505 └ -1.1281186564841013 ┌ Warning: Variances had to be floored │ ind = │ 11-element Vector{Int64}: │ 9 │ 10 │ 14 │ 19 │ ⋮ │ 26 │ 27 │ 28 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 13-element Vector{Int64}: │ 9 │ 10 │ 14 │ 19 │ ⋮ │ 27 │ 28 │ 30 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 13-element Vector{Int64}: │ 9 │ 10 │ 14 │ 19 │ ⋮ │ 27 │ 28 │ 29 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 13-element Vector{Int64}: │ 7 │ 9 │ 10 │ 14 │ ⋮ │ 27 │ 28 │ 30 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 13-element Vector{Int64}: │ 9 │ 10 │ 14 │ 19 │ ⋮ │ 27 │ 28 │ 29 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 12-element Vector{Int64}: │ 9 │ 10 │ 14 │ 19 │ ⋮ │ 27 │ 28 │ 30 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 13-element Vector{Int64}: │ 9 │ 10 │ 14 │ 19 │ ⋮ │ 27 │ 28 │ 29 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 13-element Vector{Int64}: │ 7 │ 9 │ 10 │ 14 │ ⋮ │ 27 │ 28 │ 30 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 13-element Vector{Int64}: │ 9 │ 10 │ 14 │ 19 │ ⋮ │ 27 │ 28 │ 29 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 12-element Vector{Int64}: │ 9 │ 10 │ 14 │ 19 │ ⋮ │ 27 │ 28 │ 30 └ @ 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 = 629502.8131822308) ┌ Info: K-means with 32000 data points using 50 iterations └ 37.0 data points per parameter ┌ Warning: Variances had to be floored │ ind = │ 3-element Vector{Int64}: │ 4 │ 21 │ 32 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 4-element Vector{Int64}: │ 6 │ 15 │ 19 │ 25 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 5-element Vector{Int64}: │ 3 │ 8 │ 11 │ 13 │ 29 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 4-element Vector{Int64}: │ 4 │ 20 │ 21 │ 32 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 6-element Vector{Int64}: │ 6 │ 8 │ 11 │ 12 │ 15 │ 19 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 4-element Vector{Int64}: │ 13 │ 21 │ 30 │ 32 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 1-element Vector{Int64}: │ 4 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 2-element Vector{Int64}: │ 20 │ 25 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 6-element Vector{Int64}: │ 6 │ 8 │ 11 │ 12 │ 15 │ 19 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 5-element Vector{Int64}: │ 1 │ 4 │ 21 │ 29 │ 32 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 2-element Vector{Int64}: │ 13 │ 30 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 7-element Vector{Int64}: │ 4 │ 6 │ 8 │ 11 │ 12 │ 15 │ 20 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 4-element Vector{Int64}: │ 19 │ 21 │ 25 │ 32 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 8-element Vector{Int64}: │ 4 │ 11 │ 12 │ 13 │ 15 │ 21 │ 30 │ 32 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 5-element Vector{Int64}: │ 6 │ 8 │ 19 │ 20 │ 29 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 2-element Vector{Int64}: │ 1 │ 25 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 4-element Vector{Int64}: │ 4 │ 11 │ 21 │ 32 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 3-element Vector{Int64}: │ 12 │ 15 │ 30 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 5-element Vector{Int64}: │ 6 │ 8 │ 13 │ 19 │ 29 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 2-element Vector{Int64}: │ 20 │ 25 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 5-element Vector{Int64}: │ 1 │ 4 │ 11 │ 21 │ 32 └ @ 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 ┌ Warning: Variances had to be floored │ ind = │ 2-element Vector{Int64}: │ 15 │ 30 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 6-element Vector{Int64}: │ 6 │ 8 │ 13 │ 19 │ 21 │ 29 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 5-element Vector{Int64}: │ 4 │ 11 │ 20 │ 25 │ 32 └ @ 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 ┌ Warning: Variances had to be floored │ ind = │ 5-element Vector{Int64}: │ 1 │ 4 │ 15 │ 21 │ 30 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 8-element Vector{Int64}: │ 6 │ 8 │ 11 │ 13 │ 19 │ 20 │ 29 │ 32 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 2-element Vector{Int64}: │ 3 │ 25 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 2-element Vector{Int64}: │ 4 │ 21 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 4-element Vector{Int64}: │ 11 │ 12 │ 15 │ 32 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 6-element Vector{Int64}: │ 6 │ 8 │ 13 │ 19 │ 25 │ 29 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 4-element Vector{Int64}: │ 3 │ 5 │ 20 │ 21 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 1-element Vector{Int64}: │ 4 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 4-element Vector{Int64}: │ 1 │ 11 │ 12 │ 32 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 2-element Vector{Int64}: │ 15 │ 21 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 4-element Vector{Int64}: │ 4 │ 6 │ 8 │ 19 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 9-element Vector{Int64}: │ 3 │ 4 │ 5 │ 6 │ ⋮ │ 19 │ 20 │ 29 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 10-element Vector{Int64}: │ 4 │ 6 │ 8 │ 11 │ ⋮ │ 21 │ 25 │ 32 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 8-element Vector{Int64}: │ 1 │ 3 │ 4 │ 6 │ 8 │ 19 │ 20 │ 29 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 7-element Vector{Int64}: │ 4 │ 5 │ 6 │ 8 │ 12 │ 13 │ 19 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 13-element Vector{Int64}: │ 3 │ 4 │ 6 │ 8 │ ⋮ │ 25 │ 29 │ 32 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 6-element Vector{Int64}: │ 1 │ 3 │ 4 │ 6 │ 8 │ 19 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 9-element Vector{Int64}: │ 4 │ 5 │ 6 │ 8 │ ⋮ │ 19 │ 20 │ 29 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 12-element Vector{Int64}: │ 3 │ 4 │ 6 │ 8 │ ⋮ │ 25 │ 29 │ 32 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 7-element Vector{Int64}: │ 1 │ 3 │ 4 │ 6 │ 8 │ 19 │ 20 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 kind full, method split ┌ Info: 0: avll = └ tll[1] = -1.413202601164834 ┌ Info: 1 │ avll = │ 50-element Vector{Float64}: │ -1.413229838101559 │ -1.413176361267798 │ -1.4131346793857384 │ -1.4130585564445417 │ ⋮ │ -1.4073559105038893 │ -1.4073526627531436 └ -1.4073503903770148 ┌ Info: 2 │ avll = │ 50-element Vector{Float64}: │ -1.407373073762048 │ -1.407318890251622 │ -1.4072757859010139 │ -1.4072026321987456 │ ⋮ │ -1.3986082431144142 │ -1.3970242497323664 └ -1.3946698226246947 ┌ Info: 3 │ avll = │ 50-element Vector{Float64}: │ -1.3926937434312894 │ -1.392355504452035 │ -1.392233757456974 │ -1.3920171875106462 │ ⋮ │ -1.3636470271232386 │ -1.363592494419277 └ -1.363543698308345 ┌ Info: 4 │ avll = │ 50-element Vector{Float64}: │ -1.3635589720883414 │ -1.3633167960835821 │ -1.3630591266703391 │ -1.3622846273686107 │ ⋮ │ -1.316784112091984 │ -1.316763954815255 └ -1.3167429566764524 ┌ Info: 5 │ avll = │ 50-element Vector{Float64}: │ -1.3167971492503043 │ -1.316380317913105 │ -1.315340514970073 │ -1.309548609857295 │ ⋮ │ -1.2524580349508905 │ -1.2524511922588535 └ -1.2524444351723418 ┌ Info: Total log likelihood: │ tll = │ 251-element Vector{Float64}: │ -1.413202601164834 │ -1.413229838101559 │ -1.413176361267798 │ -1.4131346793857384 │ ⋮ │ -1.2524580349508905 │ -1.2524511922588535 └ -1.2524444351723418 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 = 672262.1528677322) ┌ Info: K-means with 32000 data points using 50 iterations └ 37.0 data points per parameter ┌ Warning: Too low occupancy count 2.9 for Gausian 15 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:266 ┌ Warning: Too low occupancy count 3.0 for Gausian 15 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:266 ┌ Warning: Too low occupancy count 3.0 for Gausian 15 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:266 ┌ Warning: Too low occupancy count 3.0 for Gausian 15 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:266 ┌ Warning: Too low occupancy count 3.0 for Gausian 15 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:266 ┌ Warning: Too low occupancy count 3.0 for Gausian 15 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:266 ┌ Warning: Too low occupancy count 2.9 for Gausian 15 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:266 ┌ Warning: Too low occupancy count 2.4 for Gausian 15 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:266 ┌ Warning: Too low occupancy count 2.0 for Gausian 15 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:266 ┌ Warning: Too low occupancy count 1.5 for Gausian 15 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:266 ┌ Warning: Too low occupancy count 0.9 for Gausian 15 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:266 ┌ Warning: Too low occupancy count 0.9 for Gausian 15 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:266 ┌ Warning: Too low occupancy count 1.0 for Gausian 15 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:266 ┌ Warning: Too low occupancy count 1.0 for Gausian 15 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:266 ┌ Warning: Too low occupancy count 1.0 for Gausian 15 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:266 ┌ Warning: Too low occupancy count 1.0 for Gausian 15 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:266 ┌ Warning: Too low occupancy count 1.0 for Gausian 15 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:266 ┌ Warning: Too low occupancy count 1.0 for Gausian 15 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:266 ┌ Warning: Too low occupancy count 1.0 for Gausian 15 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:266 ┌ Warning: Too low occupancy count 1.0 for Gausian 15 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:266 ┌ Warning: Too low occupancy count 1.0 for Gausian 15 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:266 ┌ Warning: Too low occupancy count 1.0 for Gausian 15 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:266 ┌ Warning: Too low occupancy count 1.0 for Gausian 15 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:266 ┌ Warning: Too low occupancy count 1.0 for Gausian 15 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:266 ┌ Warning: Too low occupancy count 1.0 for Gausian 15 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:266 ┌ Warning: Too low occupancy count 1.0 for Gausian 15 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:266 ┌ Warning: Too low occupancy count 1.0 for Gausian 15 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:266 ┌ Warning: Too low occupancy count 1.0 for Gausian 15 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:266 ┌ Warning: Too low occupancy count 1.0 for Gausian 15 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:266 ┌ Warning: Too low occupancy count 1.0 for Gausian 15 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:266 ┌ Warning: Too low occupancy count 1.0 for Gausian 15 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:266 ┌ Warning: Too low occupancy count 1.0 for Gausian 15 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:266 ┌ Warning: Too low occupancy count 1.0 for Gausian 15 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:266 ┌ Warning: Too low occupancy count 1.0 for Gausian 15 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:266 ┌ Warning: Too low occupancy count 1.0 for Gausian 15 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:266 ┌ Warning: Too low occupancy count 1.0 for Gausian 15 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:266 ┌ Warning: Too low occupancy count 1.0 for Gausian 15 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:266 ┌ Warning: Too low occupancy count 1.0 for Gausian 15 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:266 ┌ Warning: Too low occupancy count 1.0 for Gausian 15 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:266 ┌ Warning: Too low occupancy count 1.0 for Gausian 15 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:266 ┌ Warning: Too low occupancy count 1.0 for Gausian 15 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:266 ┌ Warning: Too low occupancy count 1.0 for Gausian 15 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:266 ┌ Warning: Too low occupancy count 1.0 for Gausian 15 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:266 ┌ Warning: Too low occupancy count 1.0 for Gausian 15 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:266 ┌ Warning: Too low occupancy count 1.0 for Gausian 15 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:266 ┌ Warning: Too low occupancy count 1.0 for Gausian 15 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:266 ┌ Warning: Too low occupancy count 1.0 for Gausian 15 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:266 ┌ Warning: Too low occupancy count 1.0 for Gausian 15 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:266 ┌ Warning: Too low occupancy count 1.0 for Gausian 15 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:266 ┌ Warning: Too low occupancy count 1.0 for Gausian 15 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:266 ┌ Warning: Too low occupancy count 1.0 for Gausian 15 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:266 ┌ Warning: Too low occupancy count 1.0 for Gausian 15 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:266 ┌ Warning: Too low occupancy count 1.0 for Gausian 15 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:266 ┌ Warning: Too low occupancy count 1.0 for Gausian 15 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:266 ┌ Warning: Too low occupancy count 1.0 for Gausian 15 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:266 ┌ Warning: Too low occupancy count 1.0 for Gausian 15 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:266 ┌ Warning: Too low occupancy count 1.0 for Gausian 15 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:266 ┌ Warning: Too low occupancy count 1.0 for Gausian 15 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:266 ┌ Warning: Too low occupancy count 1.0 for Gausian 15 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:266 ┌ Warning: Too low occupancy count 1.0 for Gausian 15 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:266 Test Summary: | Broken Total Time train.jl | 1 1 8m33.6s [ 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 2.8s Testing GaussianMixtures tests passed Testing completed after 1109.55s PkgEval succeeded after 1190.82s