Package evaluation of GaussianMixtures on Julia 1.10.9 (96dc2d8c45*) started at 2025-06-06T16:55:11.372 ################################################################################ # Set-up # Installing PkgEval dependencies (TestEnv)... Set-up completed after 4.83s ################################################################################ # Installation # Installing GaussianMixtures... Resolving package versions... Updating `~/.julia/environments/v1.10/Project.toml` [cc18c42c] + GaussianMixtures v0.3.13 Updating `~/.julia/environments/v1.10/Manifest.toml` [66dad0bd] + AliasTables v1.1.3 [7d9fca2a] + Arpack v0.5.4 [aaaa29a8] + Clustering v0.15.8 [34da2185] + Compat v4.16.0 [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 v0.9.4 [5789e2e9] + FileIO v1.17.0 [1a297f60] + FillArrays v1.13.0 [cc18c42c] + GaussianMixtures v0.3.13 [34004b35] + HypergeometricFunctions v0.3.28 [92d709cd] + IrrationalConstants v0.2.4 [033835bb] + JLD2 v0.5.13 [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 v1.2.1 [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 [a2af1166] + SortingAlgorithms v1.2.1 [276daf66] + SpecialFunctions v2.5.1 [90137ffa] + StaticArrays v1.9.13 [1e83bf80] + StaticArraysCore v1.4.3 [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 v1.1.1 [56f22d72] + Artifacts [2a0f44e3] + Base64 [ade2ca70] + Dates [8ba89e20] + Distributed [f43a241f] + Downloads v1.6.0 [7b1f6079] + FileWatching [b77e0a4c] + InteractiveUtils [b27032c2] + LibCURL v0.6.4 [76f85450] + LibGit2 [8f399da3] + Libdl [37e2e46d] + LinearAlgebra [56ddb016] + Logging [d6f4376e] + Markdown [a63ad114] + Mmap [ca575930] + NetworkOptions v1.2.0 [44cfe95a] + Pkg v1.10.0 [de0858da] + Printf [3fa0cd96] + REPL [9a3f8284] + Random [ea8e919c] + SHA v0.7.0 [9e88b42a] + Serialization [6462fe0b] + Sockets [2f01184e] + SparseArrays v1.10.0 [10745b16] + Statistics v1.10.0 [4607b0f0] + SuiteSparse [fa267f1f] + TOML v1.0.3 [a4e569a6] + Tar v1.10.0 [cf7118a7] + UUIDs [4ec0a83e] + Unicode [e66e0078] + CompilerSupportLibraries_jll v1.1.1+0 [deac9b47] + LibCURL_jll v8.4.0+0 [e37daf67] + LibGit2_jll v1.6.4+0 [29816b5a] + LibSSH2_jll v1.11.0+1 [c8ffd9c3] + MbedTLS_jll v2.28.2+1 [14a3606d] + MozillaCACerts_jll v2023.1.10 [4536629a] + OpenBLAS_jll v0.3.23+4 [05823500] + OpenLibm_jll v0.8.5+0 [bea87d4a] + SuiteSparse_jll v7.2.1+1 [83775a58] + Zlib_jll v1.2.13+1 [8e850b90] + libblastrampoline_jll v5.11.0+0 [8e850ede] + nghttp2_jll v1.52.0+1 [3f19e933] + p7zip_jll v17.4.0+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 8.02s ################################################################################ # Precompilation # Precompiling PkgEval dependencies... Precompiling package dependencies... Precompilation completed after 22.98s ################################################################################ # Testing # Testing GaussianMixtures Status `/tmp/jl_uc9wCi/Project.toml` [7d9fca2a] Arpack v0.5.4 [aaaa29a8] Clustering v0.15.8 [34da2185] Compat v4.16.0 [8bb1440f] DelimitedFiles v1.9.1 [31c24e10] Distributions v0.25.120 [5789e2e9] FileIO v1.17.0 [cc18c42c] GaussianMixtures v0.3.13 [033835bb] JLD2 v0.5.13 [90014a1f] PDMats v0.11.35 [ce6b1742] RDatasets v0.7.7 [6e75b9c4] ScikitLearnBase v0.5.0 [276daf66] SpecialFunctions v2.5.1 [2913bbd2] StatsBase v0.34.5 [8ba89e20] Distributed [37e2e46d] LinearAlgebra [56ddb016] Logging [de0858da] Printf [9a3f8284] Random [10745b16] Statistics v1.10.0 [8dfed614] Test Status `/tmp/jl_uc9wCi/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 v4.16.0 [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 v0.9.4 [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 [34004b35] HypergeometricFunctions v0.3.28 [842dd82b] InlineStrings v1.4.3 [41ab1584] InvertedIndices v1.3.1 [92d709cd] IrrationalConstants v0.2.4 [82899510] IteratorInterfaceExtensions v1.0.0 [033835bb] JLD2 v0.5.13 [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 v1.2.1 [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 [6c6a2e73] Scratch v1.2.1 [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 [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 v1.1.1 [56f22d72] Artifacts [2a0f44e3] Base64 [ade2ca70] Dates [8ba89e20] Distributed [f43a241f] Downloads v1.6.0 [7b1f6079] FileWatching [9fa8497b] Future [b77e0a4c] InteractiveUtils [b27032c2] LibCURL v0.6.4 [76f85450] LibGit2 [8f399da3] Libdl [37e2e46d] LinearAlgebra [56ddb016] Logging [d6f4376e] Markdown [a63ad114] Mmap [ca575930] NetworkOptions v1.2.0 [44cfe95a] Pkg v1.10.0 [de0858da] Printf [3fa0cd96] REPL [9a3f8284] Random [ea8e919c] SHA v0.7.0 [9e88b42a] Serialization [6462fe0b] Sockets [2f01184e] SparseArrays v1.10.0 [10745b16] Statistics v1.10.0 [4607b0f0] SuiteSparse [fa267f1f] TOML v1.0.3 [a4e569a6] Tar v1.10.0 [8dfed614] Test [cf7118a7] UUIDs [4ec0a83e] Unicode [e66e0078] CompilerSupportLibraries_jll v1.1.1+0 [deac9b47] LibCURL_jll v8.4.0+0 [e37daf67] LibGit2_jll v1.6.4+0 [29816b5a] LibSSH2_jll v1.11.0+1 [c8ffd9c3] MbedTLS_jll v2.28.2+1 [14a3606d] MozillaCACerts_jll v2023.1.10 [4536629a] OpenBLAS_jll v0.3.23+4 [05823500] OpenLibm_jll v0.8.5+0 [bea87d4a] SuiteSparse_jll v7.2.1+1 [83775a58] Zlib_jll v1.2.13+1 [8e850b90] libblastrampoline_jll v5.11.0+0 [8e850ede] nghttp2_jll v1.52.0+1 [3f19e933] p7zip_jll v17.4.0+2 Info Packages marked with ⌅ have new versions available but compatibility constraints restrict them from upgrading. Testing Running tests... (100000, -2.6998013941320237e6, [99952.0130293376, 47.98697066238633], [90.72125745302053 -404.3011322934577 -9.175613525056924; -51.7751988976601 80.08663195971181 -139.84282630296843], [[99555.20586322849 452.2556844252475 408.9753789784485; 452.2556844252475 99830.11028297771 -58.76821303675064; 408.9753789784485 -58.76821303675064 100404.01853379233], [126.31452579480191 -75.72106540353195 131.51833660325846; -75.72106540353195 171.29714263665434 -218.92625589085796; 131.51833660325846 -218.92625589085796 424.74454046746615]]) Test Summary: | Pass Total Time data.jl | 8 8 2m52.4s [ Info: Initializing GMM, 2 Gaussians diag covariance 1 dimensions using 272 data points K-means converged with 4 iterations (objv = 8855.79069767458) ┌ Info: K-means with 272 data points using 4 iterations └ 68.0 data points per parameter [ Info: Initializing GMM, 8 Gaussians diag covariance 2 dimensions using 272 data points K-means converged with 6 iterations (objv = 817.0860114658858) ┌ Info: K-means with 272 data points using 6 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 └ @ GaussianMixtures ~/.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 └ @ GaussianMixtures ~/.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:709 [inlined] └ @ Core ./broadcast.jl:709 ┌ 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 └ @ GaussianMixtures ~/.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:709 [inlined] └ @ Core ./broadcast.jl:709 ┌ Warning: `lgamma(x::Real)` is deprecated, use `(logabsgamma(x))[1]` instead. │ caller = _broadcast_getindex_evalf at broadcast.jl:709 [inlined] └ @ Core ./broadcast.jl:709 History[Fri Jun 6 17:02:38 2025: Initializing GMM, 8 Gaussians diag covariance 2 dimensions using 272 data points , Fri Jun 6 17:02:39 2025: K-means with 272 data points using 6 iterations 11.3 data points per parameter , Fri Jun 6 17:02:43 2025: EM with 272 data points 0 iterations avll -2.057876 5.8 data points per parameter , Fri Jun 6 17:02:46 2025: GMM converted to Variational GMM , Fri Jun 6 17:02:55 2025: iteration 1, lowerbound -3.807806 , Fri Jun 6 17:02:55 2025: iteration 2, lowerbound -3.674720 , Fri Jun 6 17:02:56 2025: iteration 3, lowerbound -3.533319 , Fri Jun 6 17:02:57 2025: iteration 4, lowerbound -3.380274 , Fri Jun 6 17:02:57 2025: iteration 5, lowerbound -3.241064 , Fri Jun 6 17:02:58 2025: iteration 6, lowerbound -3.139123 , Fri Jun 6 17:02:59 2025: dropping number of Gaussions to 7 , Fri Jun 6 17:02:59 2025: iteration 7, lowerbound -3.078445 , Fri Jun 6 17:02:59 2025: dropping number of Gaussions to 5 , Fri Jun 6 17:03:00 2025: iteration 8, lowerbound -3.027851 , Fri Jun 6 17:03:00 2025: iteration 9, lowerbound -2.981597 , Fri Jun 6 17:03:00 2025: dropping number of Gaussions to 4 , Fri Jun 6 17:03:01 2025: iteration 10, lowerbound -2.925360 , Fri Jun 6 17:03:01 2025: iteration 11, lowerbound -2.855323 , Fri Jun 6 17:03:01 2025: iteration 12, lowerbound -2.782435 , Fri Jun 6 17:03:02 2025: iteration 13, lowerbound -2.713668 , Fri Jun 6 17:03:02 2025: iteration 14, lowerbound -2.653923 , Fri Jun 6 17:03:03 2025: iteration 15, lowerbound -2.600106 , Fri Jun 6 17:03:03 2025: iteration 16, lowerbound -2.547811 , Fri Jun 6 17:03:03 2025: iteration 17, lowerbound -2.497043 , Fri Jun 6 17:03:03 2025: dropping number of Gaussions to 3 , Fri Jun 6 17:03:04 2025: iteration 18, lowerbound -2.445631 , Fri Jun 6 17:03:04 2025: iteration 19, lowerbound -2.394124 , Fri Jun 6 17:03:04 2025: iteration 20, lowerbound -2.353891 , Fri Jun 6 17:03:05 2025: iteration 21, lowerbound -2.324840 , Fri Jun 6 17:03:05 2025: iteration 22, lowerbound -2.309436 , Fri Jun 6 17:03:05 2025: iteration 23, lowerbound -2.308905 , Fri Jun 6 17:03:05 2025: dropping number of Gaussions to 2 , Fri Jun 6 17:03:06 2025: iteration 24, lowerbound -2.302915 , Fri Jun 6 17:03:06 2025: iteration 25, lowerbound -2.299259 , Fri Jun 6 17:03:06 2025: iteration 26, lowerbound -2.299256 , Fri Jun 6 17:03:06 2025: iteration 27, lowerbound -2.299254 , Fri Jun 6 17:03:07 2025: iteration 28, lowerbound -2.299254 , Fri Jun 6 17:03:07 2025: iteration 29, lowerbound -2.299253 , Fri Jun 6 17:03:07 2025: iteration 30, lowerbound -2.299253 , Fri Jun 6 17:03:07 2025: iteration 31, lowerbound -2.299253 , Fri Jun 6 17:03:08 2025: iteration 32, lowerbound -2.299253 , Fri Jun 6 17:03:08 2025: iteration 33, lowerbound -2.299253 , Fri Jun 6 17:03:08 2025: iteration 34, lowerbound -2.299253 , Fri Jun 6 17:03:08 2025: iteration 35, lowerbound -2.299253 , Fri Jun 6 17:03:09 2025: iteration 36, lowerbound -2.299253 , Fri Jun 6 17:03:09 2025: iteration 37, lowerbound -2.299253 , Fri Jun 6 17:03:09 2025: iteration 38, lowerbound -2.299253 , Fri Jun 6 17:03:09 2025: iteration 39, lowerbound -2.299253 , Fri Jun 6 17:03:10 2025: iteration 40, lowerbound -2.299253 , Fri Jun 6 17:03:10 2025: iteration 41, lowerbound -2.299253 , Fri Jun 6 17:03:10 2025: iteration 42, lowerbound -2.299253 , Fri Jun 6 17:03:11 2025: iteration 43, lowerbound -2.299253 , Fri Jun 6 17:03:11 2025: iteration 44, lowerbound -2.299253 , Fri Jun 6 17:03:11 2025: iteration 45, lowerbound -2.299253 , Fri Jun 6 17:03:11 2025: iteration 46, lowerbound -2.299253 , Fri Jun 6 17:03:12 2025: iteration 47, lowerbound -2.299253 , Fri Jun 6 17:03:12 2025: iteration 48, lowerbound -2.299253 , Fri Jun 6 17:03:12 2025: iteration 49, lowerbound -2.299253 , Fri Jun 6 17:03:12 2025: iteration 50, lowerbound -2.299253 , Fri Jun 6 17:03:12 2025: 50 variational Bayes EM-like iterations using 272 data points, final lowerbound -2.299253 ] α = [178.04509222602496, 95.95490777397497] β = [178.04509222602496, 95.95490777397497] m = [4.250300733269821 79.28686694436053; 2.000229257775277 53.85198717246082] ν = [180.04509222602496, 97.95490777397497] W = LinearAlgebra.UpperTriangular{Float64, Matrix{Float64}}[[0.18404155547483225 -0.007644049042328204; 0.0 0.008581705166331855], [0.3758763611949976 -0.008953123827347918; 0.0 0.012748664777409916]] Test Summary: | Pass Total Time bayes.jl | 3 3 1m58.8s Kind: diag, size256 nx: 100000 sum(zeroth order stats): 100000.00000000009 avll from stats: -0.9709188917532355 avll from llpg: -0.9709188917532355 avll direct: -0.9709188917532356 sum posterior: 100000.0 Kind: full, size16 nx: 100000 sum(zeroth order stats): 100000.00000000001 avll from stats: -1.015962903827696 avll from llpg: -1.015962903827696 avll direct: -1.015962903827696 sum posterior: 100000.0 kind diag, method split ┌ Info: 0: avll = └ tll[1] = -1.4059778103802443 ┌ Info: 1 │ avll = │ 50-element Vector{Float64}: │ -1.4060539203297724 │ -1.4059822674533542 │ -1.4056006326156547 │ -1.4011655926033517 │ ⋮ │ -1.372616320177802 │ -1.37261631607574 └ -1.3726163128133286 ┌ Info: 2 │ avll = │ 50-element Vector{Float64}: │ -1.3727315020367217 │ -1.3726382330977491 │ -1.3724694558406585 │ -1.3709066577811293 │ ⋮ │ -1.330969262057192 │ -1.3309006978829014 └ -1.33084621363111 ┌ Info: 3 │ avll = │ 50-element Vector{Float64}: │ -1.330935588030123 │ -1.330738096006686 │ -1.3301950183628486 │ -1.3259789990711814 │ ⋮ │ -1.274264807970446 │ -1.2742648064737623 └ -1.2742648054628967 ┌ 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}: │ 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 = │ 2-element Vector{Int64}: │ 2 │ 3 └ @ 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 = │ 2-element Vector{Int64}: │ 2 │ 5 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 2-element Vector{Int64}: │ 2 │ 3 └ @ 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}: │ 2 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 2-element Vector{Int64}: │ 2 │ 3 └ @ 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}: │ 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 = │ 2-element Vector{Int64}: │ 2 │ 3 └ @ 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 = │ 2-element Vector{Int64}: │ 2 │ 5 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 2-element Vector{Int64}: │ 2 │ 3 └ @ 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}: │ 2 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Info: 4 │ avll = │ 50-element Vector{Float64}: │ -1.2744837031362701 │ -1.274225651557602 │ -1.2732115871431127 │ -1.2635095877066187 │ ⋮ │ -1.193631400263985 │ -1.1877284129447006 └ -1.1909892036142509 ┌ Warning: Variances had to be floored │ ind = │ 4-element Vector{Int64}: │ 3 │ 4 │ 5 │ 6 └ @ 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}: │ 3 │ 4 │ 5 │ 6 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 2-element Vector{Int64}: │ 3 │ 4 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 8-element Vector{Int64}: │ 3 │ 4 │ 5 │ 6 │ 9 │ 10 │ 12 │ 31 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 3-element Vector{Int64}: │ 4 │ 5 │ 6 └ @ 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 │ 12 │ 31 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 3-element Vector{Int64}: │ 3 │ 5 │ 6 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 8-element Vector{Int64}: │ 4 │ 5 │ 6 │ 9 │ 10 │ 12 │ 25 │ 31 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 4-element Vector{Int64}: │ 3 │ 5 │ 6 │ 27 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 7-element Vector{Int64}: │ 4 │ 5 │ 6 │ 9 │ 10 │ 12 │ 31 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 4-element Vector{Int64}: │ 3 │ 5 │ 6 │ 22 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 7-element Vector{Int64}: │ 4 │ 5 │ 6 │ 9 │ 10 │ 12 │ 31 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 5-element Vector{Int64}: │ 3 │ 5 │ 6 │ 25 │ 27 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 7-element Vector{Int64}: │ 4 │ 5 │ 6 │ 9 │ 10 │ 12 │ 31 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 3-element Vector{Int64}: │ 3 │ 5 │ 6 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 8-element Vector{Int64}: │ 4 │ 5 │ 6 │ 9 │ 10 │ 12 │ 22 │ 31 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 4-element Vector{Int64}: │ 3 │ 5 │ 6 │ 27 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 8-element Vector{Int64}: │ 4 │ 5 │ 6 │ 9 │ 10 │ 12 │ 25 │ 31 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 4-element Vector{Int64}: │ 3 │ 4 │ 5 │ 6 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 9-element Vector{Int64}: │ 3 │ 4 │ 5 │ 6 │ ⋮ │ 12 │ 22 │ 31 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 5-element Vector{Int64}: │ 3 │ 4 │ 5 │ 6 │ 27 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 8-element Vector{Int64}: │ 3 │ 4 │ 5 │ 6 │ 9 │ 10 │ 12 │ 31 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 5-element Vector{Int64}: │ 3 │ 4 │ 5 │ 6 │ 25 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 8-element Vector{Int64}: │ 3 │ 4 │ 5 │ 6 │ 9 │ 10 │ 12 │ 31 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 6-element Vector{Int64}: │ 3 │ 4 │ 5 │ 6 │ 22 │ 27 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 8-element Vector{Int64}: │ 3 │ 4 │ 5 │ 6 │ 9 │ 10 │ 12 │ 31 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 4-element Vector{Int64}: │ 3 │ 4 │ 5 │ 6 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 9-element Vector{Int64}: │ 3 │ 4 │ 5 │ 6 │ ⋮ │ 12 │ 25 │ 31 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 5-element Vector{Int64}: │ 3 │ 4 │ 5 │ 6 │ 27 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 9-element Vector{Int64}: │ 3 │ 4 │ 5 │ 6 │ ⋮ │ 12 │ 22 │ 31 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 4-element Vector{Int64}: │ 3 │ 4 │ 5 │ 6 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 8-element Vector{Int64}: │ 3 │ 4 │ 5 │ 6 │ 9 │ 10 │ 12 │ 31 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 6-element Vector{Int64}: │ 3 │ 4 │ 5 │ 6 │ 25 │ 27 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 9-element Vector{Int64}: │ 3 │ 4 │ 5 │ 6 │ ⋮ │ 12 │ 22 │ 31 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 4-element Vector{Int64}: │ 3 │ 4 │ 5 │ 6 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 8-element Vector{Int64}: │ 3 │ 4 │ 5 │ 6 │ 9 │ 10 │ 12 │ 31 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 5-element Vector{Int64}: │ 3 │ 4 │ 5 │ 6 │ 27 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 9-element Vector{Int64}: │ 3 │ 4 │ 5 │ 6 │ ⋮ │ 12 │ 25 │ 31 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 5-element Vector{Int64}: │ 3 │ 4 │ 5 │ 6 │ 22 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 8-element Vector{Int64}: │ 3 │ 4 │ 5 │ 6 │ 9 │ 10 │ 12 │ 31 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 5-element Vector{Int64}: │ 3 │ 4 │ 5 │ 6 │ 27 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 8-element Vector{Int64}: │ 3 │ 4 │ 5 │ 6 │ 9 │ 10 │ 12 │ 31 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 6-element Vector{Int64}: │ 3 │ 4 │ 5 │ 6 │ 22 │ 25 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 8-element Vector{Int64}: │ 3 │ 4 │ 5 │ 6 │ 9 │ 10 │ 12 │ 31 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 5-element Vector{Int64}: │ 3 │ 4 │ 5 │ 6 │ 27 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 8-element Vector{Int64}: │ 3 │ 4 │ 5 │ 6 │ 9 │ 10 │ 12 │ 31 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 4-element Vector{Int64}: │ 3 │ 4 │ 5 │ 6 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 10-element Vector{Int64}: │ 3 │ 4 │ 5 │ 6 │ ⋮ │ 22 │ 25 │ 31 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Info: 5 │ avll = │ 50-element Vector{Float64}: │ -1.1843854865002508 │ -1.1797105961952756 │ -1.1820278560340196 │ -1.1722818015153356 │ ⋮ │ -1.1038832313876557 │ -1.1082262503131035 └ -1.0835859513950061 ┌ Info: Total log likelihood: │ tll = │ 251-element Vector{Float64}: │ -1.4059778103802443 │ -1.4060539203297724 │ -1.4059822674533542 │ -1.4056006326156547 │ ⋮ │ -1.1038832313876557 │ -1.1082262503131035 └ -1.0835859513950061 ┌ Warning: Variances had to be floored │ ind = │ 5-element Vector{Int64}: │ 3 │ 4 │ 5 │ 6 │ 27 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 9-element Vector{Int64}: │ 3 │ 4 │ 5 │ 6 │ ⋮ │ 12 │ 27 │ 31 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 5-element Vector{Int64}: │ 3 │ 4 │ 5 │ 6 │ 27 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 10-element Vector{Int64}: │ 3 │ 4 │ 5 │ 6 │ ⋮ │ 22 │ 27 │ 31 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 6-element Vector{Int64}: │ 3 │ 4 │ 5 │ 6 │ 25 │ 27 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 9-element Vector{Int64}: │ 3 │ 4 │ 5 │ 6 │ ⋮ │ 12 │ 27 │ 31 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 5-element Vector{Int64}: │ 3 │ 4 │ 5 │ 6 │ 27 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 9-element Vector{Int64}: │ 3 │ 4 │ 5 │ 6 │ ⋮ │ 12 │ 27 │ 31 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 6-element Vector{Int64}: │ 3 │ 4 │ 5 │ 6 │ 22 │ 27 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 10-element Vector{Int64}: │ 3 │ 4 │ 5 │ 6 │ ⋮ │ 25 │ 27 │ 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 = 598463.0370247217) ┌ Info: K-means with 32000 data points using 50 iterations └ 37.0 data points per parameter ┌ Warning: Variances had to be floored │ ind = │ 1-element Vector{Int64}: │ 11 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 4-element Vector{Int64}: │ 7 │ 8 │ 15 │ 32 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 2-element Vector{Int64}: │ 5 │ 13 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 5-element Vector{Int64}: │ 8 │ 11 │ 15 │ 19 │ 32 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 2-element Vector{Int64}: │ 5 │ 7 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 1-element Vector{Int64}: │ 13 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 4-element Vector{Int64}: │ 8 │ 11 │ 15 │ 32 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 3-element Vector{Int64}: │ 5 │ 7 │ 19 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 1-element Vector{Int64}: │ 13 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 4-element Vector{Int64}: │ 8 │ 11 │ 15 │ 32 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 2-element Vector{Int64}: │ 5 │ 7 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 2-element Vector{Int64}: │ 13 │ 19 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 4-element Vector{Int64}: │ 8 │ 11 │ 15 │ 32 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 2-element Vector{Int64}: │ 5 │ 7 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 1-element Vector{Int64}: │ 13 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 3-element Vector{Int64}: │ 8 │ 12 │ 19 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 2-element Vector{Int64}: │ 15 │ 32 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 3-element Vector{Int64}: │ 5 │ 7 │ 13 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 1-element Vector{Int64}: │ 24 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 3-element Vector{Int64}: │ 8 │ 12 │ 32 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 3-element Vector{Int64}: │ 13 │ 15 │ 19 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 3-element Vector{Int64}: │ 5 │ 7 │ 24 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 4-element Vector{Int64}: │ 8 │ 12 │ 13 │ 32 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 1-element Vector{Int64}: │ 24 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 4-element Vector{Int64}: │ 5 │ 7 │ 15 │ 19 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 2-element Vector{Int64}: │ 8 │ 13 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 3-element Vector{Int64}: │ 2 │ 12 │ 32 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 5-element Vector{Int64}: │ 5 │ 7 │ 8 │ 13 │ 24 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 4-element Vector{Int64}: │ 2 │ 15 │ 19 │ 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 = │ 1-element Vector{Int64}: │ 13 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 5-element Vector{Int64}: │ 5 │ 7 │ 8 │ 24 │ 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 = │ 4-element Vector{Int64}: │ 2 │ 13 │ 15 │ 19 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 3-element Vector{Int64}: │ 8 │ 24 │ 32 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 2-element Vector{Int64}: │ 5 │ 7 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 1-element Vector{Int64}: │ 13 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 6-element Vector{Int64}: │ 2 │ 8 │ 12 │ 19 │ 24 │ 32 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 8-element Vector{Int64}: │ 2 │ 5 │ 8 │ 13 │ 15 │ 19 │ 24 │ 32 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 6-element Vector{Int64}: │ 2 │ 8 │ 12 │ 19 │ 24 │ 32 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 8-element Vector{Int64}: │ 2 │ 5 │ 8 │ 13 │ 15 │ 19 │ 24 │ 32 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 7-element Vector{Int64}: │ 2 │ 7 │ 8 │ 12 │ 19 │ 24 │ 32 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 8-element Vector{Int64}: │ 2 │ 5 │ 8 │ 13 │ 15 │ 19 │ 24 │ 32 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 6-element Vector{Int64}: │ 2 │ 8 │ 12 │ 19 │ 24 │ 32 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 8-element Vector{Int64}: │ 2 │ 5 │ 8 │ 13 │ 15 │ 19 │ 24 │ 32 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 6-element Vector{Int64}: │ 2 │ 8 │ 12 │ 19 │ 24 │ 32 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 ┌ Warning: Variances had to be floored │ ind = │ 9-element Vector{Int64}: │ 2 │ 5 │ 7 │ 8 │ ⋮ │ 19 │ 24 │ 32 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:260 kind full, method split ┌ Info: 0: avll = └ tll[1] = -1.4187108241711108 ┌ Info: 1 │ avll = │ 50-element Vector{Float64}: │ -1.4187392070042708 │ -1.4186689919763396 │ -1.418598665350221 │ -1.4184588275621517 │ ⋮ │ -1.4127693945120985 │ -1.4127679763190466 └ -1.4127668710223604 ┌ Info: 2 │ avll = │ 50-element Vector{Float64}: │ -1.4127920194824106 │ -1.4127228531089369 │ -1.412657434876751 │ -1.4125381697250445 │ ⋮ │ -1.4026208991085056 │ -1.4013439461514439 └ -1.4007626577356516 ┌ Info: 3 │ avll = │ 50-element Vector{Float64}: │ -1.4007377226198905 │ -1.4005871681653206 │ -1.4004399559683811 │ -1.4001857932855895 │ ⋮ │ -1.371702682499579 │ -1.371697699110957 └ -1.3716927712869533 ┌ Info: 4 │ avll = │ 50-element Vector{Float64}: │ -1.3717452449611998 │ -1.3715159016162022 │ -1.3711505954432832 │ -1.3689077658608526 │ ⋮ │ -1.3088883827190245 │ -1.3088574378663163 └ -1.3088191734986974 ┌ Info: 5 │ avll = │ 50-element Vector{Float64}: │ -1.30884940088563 │ -1.3084446880948382 │ -1.30793028523217 │ -1.3068210810728929 │ ⋮ │ -1.2873953976718806 │ -1.2872737967769183 └ -1.287055049129961 ┌ Info: Total log likelihood: │ tll = │ 251-element Vector{Float64}: │ -1.4187108241711108 │ -1.4187392070042708 │ -1.4186689919763396 │ -1.418598665350221 │ ⋮ │ -1.2873953976718806 │ -1.2872737967769183 └ -1.287055049129961 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 = 678546.3055510401) ┌ Info: K-means with 32000 data points using 50 iterations └ 37.0 data points per parameter ┌ Warning: Too low occupancy count 17.5 for Gausian 3 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:266 ┌ Warning: Too low occupancy count 14.9 for Gausian 3 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:266 ┌ Warning: Too low occupancy count 12.3 for Gausian 3 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:266 ┌ Warning: Too low occupancy count 10.7 for Gausian 3 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:266 ┌ Warning: Too low occupancy count 10.3 for Gausian 3 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:266 ┌ Warning: Too low occupancy count 10.1 for Gausian 3 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:266 ┌ Warning: Too low occupancy count 10.0 for Gausian 3 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:266 ┌ Warning: Too low occupancy count 9.9 for Gausian 3 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:266 ┌ Warning: Too low occupancy count 9.9 for Gausian 3 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:266 ┌ Warning: Too low occupancy count 9.9 for Gausian 3 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:266 ┌ Warning: Too low occupancy count 9.9 for Gausian 3 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:266 ┌ Warning: Too low occupancy count 9.9 for Gausian 3 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:266 ┌ Warning: Too low occupancy count 9.9 for Gausian 3 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:266 ┌ Warning: Too low occupancy count 9.9 for Gausian 3 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:266 ┌ Warning: Too low occupancy count 9.9 for Gausian 3 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:266 ┌ Warning: Too low occupancy count 9.9 for Gausian 3 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:266 ┌ Warning: Too low occupancy count 9.9 for Gausian 3 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:266 ┌ Warning: Too low occupancy count 9.9 for Gausian 3 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:266 ┌ Warning: Too low occupancy count 9.9 for Gausian 3 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:266 ┌ Warning: Too low occupancy count 9.9 for Gausian 3 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:266 ┌ Warning: Too low occupancy count 9.9 for Gausian 3 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:266 ┌ Warning: Too low occupancy count 9.9 for Gausian 3 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:266 ┌ Warning: Too low occupancy count 9.9 for Gausian 3 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:266 ┌ Warning: Too low occupancy count 9.9 for Gausian 3 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:266 ┌ Warning: Too low occupancy count 9.9 for Gausian 3 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:266 ┌ Warning: Too low occupancy count 9.9 for Gausian 3 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:266 ┌ Warning: Too low occupancy count 9.9 for Gausian 3 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:266 ┌ Warning: Too low occupancy count 9.9 for Gausian 3 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:266 ┌ Warning: Too low occupancy count 9.9 for Gausian 3 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:266 ┌ Warning: Too low occupancy count 9.9 for Gausian 3 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:266 ┌ Warning: Too low occupancy count 9.9 for Gausian 3 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:266 ┌ Warning: Too low occupancy count 9.9 for Gausian 3 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:266 ┌ Warning: Too low occupancy count 9.9 for Gausian 3 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:266 ┌ Warning: Too low occupancy count 9.9 for Gausian 3 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:266 ┌ Warning: Too low occupancy count 9.9 for Gausian 3 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:266 ┌ Warning: Too low occupancy count 9.9 for Gausian 3 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:266 ┌ Warning: Too low occupancy count 9.9 for Gausian 3 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:266 ┌ Warning: Too low occupancy count 9.9 for Gausian 3 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:266 ┌ Warning: Too low occupancy count 9.9 for Gausian 3 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:266 ┌ Warning: Too low occupancy count 9.9 for Gausian 3 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:266 ┌ Warning: Too low occupancy count 9.9 for Gausian 3 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:266 ┌ Warning: Too low occupancy count 9.9 for Gausian 3 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:266 ┌ Warning: Too low occupancy count 9.9 for Gausian 3 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:266 ┌ Warning: Too low occupancy count 9.9 for Gausian 3 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:266 ┌ Warning: Too low occupancy count 9.9 for Gausian 3 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:266 ┌ Warning: Too low occupancy count 9.9 for Gausian 3 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:266 ┌ Warning: Too low occupancy count 9.9 for Gausian 3 └ @ GaussianMixtures ~/.julia/packages/GaussianMixtures/RYvNa/src/train.jl:266 Test Summary: | Broken Total Time train.jl | 1 1 6m09.8s [ 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 2.3s Testing GaussianMixtures tests passed Testing completed after 814.37s PkgEval succeeded after 861.99s