Package evaluation to test JWAS on Julia 1.14.0-DEV.3055 (7e75a8061a*) started at 2026-08-28T07:24:04.886 ################################################################################ # Set-up # Installing PkgEval dependencies (TestEnv)... Activating project at `~/.julia/environments/v1.14` Set-up completed after 13.7s ################################################################################ # Installation # Installing JWAS... Resolving package versions... Installed libaom_jll ─────────────────── v3.14.1+0 Installed Libtiff_jll ────────────────── v4.7.3+0 Installed Libuuid_jll ────────────────── v2.42.0+0 Installed Qt6Base_jll ────────────────── v6.10.2+2 Installed libass_jll ─────────────────── v0.17.4+0 Installed InlineStrings ──────────────── v1.4.5 Installed HarfBuzz_jll ───────────────── v8.5.1+0 Installed Bzip2_jll ──────────────────── v1.0.9+0 Installed Cairo_jll ──────────────────── v1.18.7+0 Installed OrderedCollections ─────────── v1.8.2 Installed PlotThemes ─────────────────── v3.3.0 Installed Graphite2_jll ──────────────── v1.3.16+0 Installed SentinelArrays ─────────────── v1.4.10 Installed Revise ─────────────────────── v3.16.5 Installed Xorg_libXinerama_jll ───────── v1.1.7+0 Installed libinput_jll ───────────────── v1.28.1+0 Installed NaNMath ────────────────────── v1.1.4 Installed Xorg_libpciaccess_jll ──────── v0.19.0+0 Installed Fontconfig_jll ─────────────── v2.17.1+0 Installed fzf_jll ────────────────────── v0.61.1+0 Installed Compiler ───────────────────── v0.1.1 Installed LoweredCodeUtils ───────────── v3.8.0 Installed QuadGK ─────────────────────── v2.11.3 Installed Tables ─────────────────────── v1.14.0 Installed OpenSpecFun_jll ────────────── v0.5.6+0 Installed Opus_jll ───────────────────── v1.6.1+0 Installed libva_jll ──────────────────── v2.23.0+0 Installed Xorg_libxcb_jll ────────────── v1.17.1+0 Installed Ogg_jll ────────────────────── v1.3.6+0 Installed GSL_jll ────────────────────── v2.8.1+0 Installed Unzip ──────────────────────── v0.2.0 Installed Xorg_xcb_util_wm_jll ───────── v0.4.2+0 Installed Reexport ───────────────────── v1.2.2 Installed Missings ───────────────────── v1.2.0 Installed InverseFunctions ───────────── v0.1.17 Installed FFMPEG ─────────────────────── v0.4.5 Installed LERC_jll ───────────────────── v4.1.0+0 Installed Preferences ────────────────── v1.5.2 Installed LaTeXStrings ───────────────── v1.4.1 Installed LLVMOpenMP_jll ─────────────── v22.1.7+0 Installed libdrm_jll ─────────────────── v2.4.134+0 Installed Crayons ────────────────────── v4.2.0 Installed SortingAlgorithms ──────────── v1.2.3 Installed TableTraits ────────────────── v1.0.1 Installed Xorg_libICE_jll ────────────── v1.1.2+0 Installed eudev_jll ──────────────────── v3.2.14+0 Installed URIs ───────────────────────── v1.7.0 Installed FillArrays ─────────────────── v1.17.0 Installed Grisu ──────────────────────── v1.0.2 Installed EpollShim_jll ──────────────── v0.0.20230411+1 (no artifacts on this platform) Installed Format ─────────────────────── v1.3.7 Installed MacroTools ─────────────────── v0.5.16 Installed DataStructures ─────────────── v0.18.22 Installed DelimitedFiles ─────────────── v1.9.1 Installed Xorg_xcb_util_jll ──────────── v0.4.1+0 Installed UnicodeFun ─────────────────── v0.4.1 Installed CodecZlib ──────────────────── v0.7.9 Installed StatsBase ──────────────────── v0.33.10 Installed x264_jll ───────────────────── v10164.0.1+0 Installed Xorg_libXau_jll ────────────── v1.0.13+0 Installed StructUtils ────────────────── v2.8.5 Installed Xorg_libXfixes_jll ─────────── v6.0.2+0 Installed mtdev_jll ──────────────────── v1.1.7+0 Installed Libffi_jll ─────────────────── v3.4.7+0 Installed Qt6ShaderTools_jll ─────────── v6.10.2+1 Installed LoggingExtras ──────────────── v1.2.0 Installed DataValueInterfaces ────────── v1.0.0 Installed Pixman_jll ─────────────────── v0.46.4+0 Installed NamedDims ──────────────────── v1.2.3 Installed Expat_jll ──────────────────── v2.8.3+0 Installed IrrationalConstants ────────── v0.2.6 Installed libdecor_jll ───────────────── v0.2.2+0 Installed Roots ──────────────────────── v3.0.7 Installed Xorg_libXcursor_jll ────────── v1.2.4+0 Installed libpng_jll ─────────────────── v1.6.58+0 Installed Contour ────────────────────── v0.6.3 Installed ColorVectorSpace ───────────── v0.11.0 Installed BitFlags ───────────────────── v0.1.10 Installed HTTP ───────────────────────── v1.11.0 Installed FFMPEG_jll ─────────────────── v8.1.2+0 Installed Xorg_xcb_util_keysyms_jll ──── v0.4.1+0 Installed StableRNGs ─────────────────── v1.0.4 Installed libfdk_aac_jll ─────────────── v2.0.4+0 Installed Scratch ────────────────────── v1.3.0 Installed SimpleBufferStream ─────────── v1.2.0 Installed Qt6Svg_jll ─────────────────── v6.10.2+0 Installed PooledArrays ───────────────── v1.4.3 Installed Qt6Declarative_jll ─────────── v6.10.2+2 Installed PDMats ─────────────────────── v0.11.35 Installed WorkerUtilities ────────────── v1.6.1 Installed DocStringExtensions ────────── v0.9.5 Installed Plots ──────────────────────── v1.41.7 Installed ColorSchemes ───────────────── v3.31.0 Installed Rmath_jll ──────────────────── v0.5.2+0 Installed CompositionsBase ───────────── v0.1.2 Installed CommonSolve ────────────────── v0.2.14 Installed RelocatableFolders ─────────── v1.0.1 Installed GSL ────────────────────────── v1.0.1 Installed JWAS ───────────────────────── v2.4.0 Installed Ghostscript_jll ────────────── v9.55.1+0 Installed JLFzf ──────────────────────── v0.1.11 Installed ConcurrentUtilities ────────── v2.6.0 Installed AliasTables ────────────────── v1.1.3 Installed CSV ────────────────────────── v0.10.17 Installed IteratorInterfaceExtensions ── v1.0.0 Installed DataAPI ────────────────────── v1.16.0 Installed RecipesBase ────────────────── v1.3.4 Installed libevdev_jll ───────────────── v1.13.4+0 Installed Wayland_jll ────────────────── v1.24.0+0 Installed Xorg_libxkbfile_jll ────────── v1.2.0+0 Installed Xorg_libXi_jll ─────────────── v1.8.4+0 Installed InvertedIndices ────────────── v1.3.1 Installed Measures ───────────────────── v0.3.3 Installed CodeTracking ───────────────── v3.0.2 Installed Glib_jll ───────────────────── v2.88.3+0 Installed Xorg_xkbcomp_jll ───────────── v1.4.7+0 Installed Libglvnd_jll ───────────────── v1.7.1+1 Installed ColorTypes ─────────────────── v0.12.1 Installed Requires ───────────────────── v1.3.1 Installed StringManipulation ─────────── v0.5.0 Installed Latexify ───────────────────── v0.16.12 Installed Colors ─────────────────────── v0.13.1 Installed LogExpFunctions ────────────── v1.0.1 Installed Parsers ────────────────────── v2.8.7 Installed JuliaInterpreter ───────────── v0.11.4 Installed Vulkan_Loader_jll ──────────── v1.3.243+0 Installed Xorg_xcb_util_cursor_jll ───── v0.1.6+0 Installed JSON ───────────────────────── v1.7.1 Installed Gamma ──────────────────────── v1.2.0 Installed Rmath ──────────────────────── v0.9.0 Installed Distributions ──────────────── v0.25.131 Installed Xorg_xcb_util_renderutil_jll ─ v0.3.10+0 Installed StatsFuns ──────────────────── v2.2.1 Installed PrettyTables ───────────────── v3.4.8 Installed Xorg_libXdmcp_jll ──────────── v1.1.6+0 Installed DataFrames ─────────────────── v1.8.2 Installed Xorg_xkeyboard_config_jll ──── v2.47.0+2 Installed Xorg_libSM_jll ─────────────── v1.2.6+0 Installed Pango_jll ──────────────────── v1.58.0+0 Installed GR_jll ─────────────────────── v0.73.27+0 Installed Accessors ──────────────────── v0.1.45 Installed WeakRefStrings ─────────────── v1.4.3 Installed XZ_jll ─────────────────────── v5.8.3+0 Installed JLLWrappers ────────────────── v1.8.0 Installed x265_jll ───────────────────── v4.1.0+0 Installed JpegTurbo_jll ──────────────── v3.2.0+1 Installed RecipesPipeline ────────────── v0.6.12 Installed Xorg_xtrans_jll ────────────── v1.6.0+0 Installed HypergeometricFunctions ────── v0.3.30 Installed FilePathsBase ──────────────── v0.9.24 Installed Dbus_jll ───────────────────── v1.16.2+0 Installed Libmount_jll ───────────────── v2.42.0+0 Installed ConstructionBase ───────────── v1.6.0 Installed Xorg_libX11_jll ────────────── v1.8.13+0 Installed ExceptionUnwrapping ────────── v0.1.11 Installed Compat ─────────────────────── v4.18.1 Installed PlotUtils ──────────────────── v1.4.4 Installed TensorCore ─────────────────── v0.1.1 Installed TranscodingStreams ─────────── v0.11.3 Installed GR ─────────────────────────── v0.73.27 Installed MbedTLS ────────────────────── v1.1.10 Installed Xorg_xcb_util_image_jll ────── v0.4.1+0 Installed StatsAPI ───────────────────── v1.8.0 Installed Statistics ─────────────────── v1.11.1 Installed xkbcommon_jll ──────────────── v1.13.0+0 Installed ProgressMeter ──────────────── v1.11.0 Installed OpenSSL ────────────────────── v1.6.1 Installed PrecompileTools ────────────── v1.3.4 Installed GLFW_jll ───────────────────── v3.5.1+0 Installed FixedPointNumbers ──────────── v0.8.6 Installed GettextRuntime_jll ─────────── v0.22.4+0 Installed FriBidi_jll ────────────────── v1.0.17+0 Installed LAME_jll ───────────────────── v3.100.3+0 Installed libvorbis_jll ──────────────── v1.3.8+0 Installed PtrArrays ──────────────────── v1.4.0 Installed Xorg_libXrender_jll ────────── v0.9.12+0 Installed SpecialFunctions ───────────── v2.9.0 Installed Showoff ────────────────────── v1.0.3 Installed FreeType2_jll ──────────────── v2.14.3+1 Installed Libiconv_jll ───────────────── v1.18.0+0 Installed MbedTLS_jll ────────────────── v2.28.1010+0 Installed Xorg_libXrandr_jll ─────────── v1.5.6+0 Installed Xorg_libXext_jll ───────────── v1.3.8+0 Installed Qt6Wayland_jll ─────────────── v6.10.2+1 Installed Kronecker ──────────────────── v0.5.5 Installing 81 artifacts Installed artifact Xorg_xcb_util_keysyms 14.3 KiB Installed artifact Xorg_xcb_util_cursor 24.2 KiB Installed artifact LERC 220.3 KiB Installed artifact Xorg_xkbcomp 230.5 KiB Installed artifact LAME 243.9 KiB Installed artifact GettextRuntime 345.6 KiB Installed artifact Xorg_libxcb 1.3 MiB Installed artifact Xorg_libXcursor 137.4 KiB Installed artifact MbedTLS 1.0 MiB Installed artifact eudev 2.3 MiB Installed artifact Ogg 213.4 KiB Installed artifact Rmath 111.3 KiB Installed artifact Xorg_xtrans 39.5 KiB Installed artifact FriBidi 67.6 KiB Installed artifact Xorg_libX11 2.3 MiB Installed artifact Wayland 266.5 KiB Installed artifact libfdk_aac 2.4 MiB Installed artifact libdrm 304.7 KiB Installed artifact Xorg_libpciaccess 23.4 KiB Installed artifact Libmount 3.4 MiB Installed artifact libvorbis 226.3 KiB Installed artifact JpegTurbo 713.4 KiB Installed artifact xkbcommon 252.5 KiB Installed artifact Pango 1.3 MiB Installed artifact Fontconfig 443.8 KiB Installed artifact GLFW 162.5 KiB Installed artifact Xorg_libXi 499.8 KiB Installed artifact Xorg_libSM 104.8 KiB Installed artifact Libglvnd 482.2 KiB Installed artifact libinput 555.0 KiB Installed artifact mtdev 55.5 KiB Installed artifact Vulkan_Loader 146.2 KiB Installed artifact GR 15.8 MiB Installed artifact Libiconv 1022.9 KiB Installed artifact Expat 255.9 KiB Installed artifact Pixman 343.0 KiB Installed artifact Xorg_libXau 25.8 KiB Installed artifact HarfBuzz 1.2 MiB Installed artifact Libtiff 1.7 MiB Installed artifact Opus 792.2 KiB Installed artifact x264 908.7 KiB Installed artifact libass 361.1 KiB Installed artifact Libffi 39.2 KiB Installed artifact Qt6ShaderTools 1.7 MiB Installed artifact Xorg_libxkbfile 81.0 KiB Installed artifact x265 1.1 MiB Installed artifact Bzip2 152.8 KiB Installed artifact Dbus 398.5 KiB Installed artifact FreeType2 1.2 MiB Installed artifact libaom 3.9 MiB Installed artifact Xorg_libXrender 174.0 KiB Installed artifact Xorg_xcb_util_renderutil 22.4 KiB Installed artifact Xorg_libXfixes 41.4 KiB Installed artifact Xorg_xkeyboard_config 375.9 KiB Installed artifact libva 187.1 KiB Installed artifact libpng 234.7 KiB Installed artifact GSL 3.6 MiB Installed artifact OpenSpecFun 105.4 KiB Installed artifact fzf 3.0 MiB Installed artifact Xorg_libXdmcp 49.9 KiB Installed artifact Xorg_libXinerama 21.7 KiB Installed artifact libevdev 91.2 KiB Installed artifact XZ 1018.2 KiB Installed artifact Glib 4.2 MiB Installed artifact Xorg_xcb_util 26.3 KiB Installed artifact FFMPEG 10.2 MiB Installed artifact Xorg_libXext 187.3 KiB Installed artifact Xorg_xcb_util_image 33.8 KiB Installed artifact Graphite2 109.8 KiB Installed artifact Cairo 1.5 MiB Installed artifact LLVMOpenMP 573.2 KiB Installed artifact Xorg_libXrandr 69.9 KiB Installed artifact Ghostscript 30.0 MiB Installed artifact Xorg_libICE 254.5 KiB Installed artifact libdecor 36.5 KiB Installed artifact Qt6Base 17.1 MiB Installed artifact Xorg_xcb_util_wm 95.5 KiB Installed artifact Qt6Svg 303.6 KiB Installed artifact Qt6Wayland 930.6 KiB Installed artifact Libuuid 1.9 MiB Installed artifact Qt6Declarative 15.7 MiB Updating `~/.julia/environments/v1.14/Project.toml` [c9a035f4] + JWAS v2.4.0 Updating `~/.julia/environments/v1.14/Manifest.toml` [7d9f7c33] + Accessors v0.1.45 [66dad0bd] + AliasTables v1.1.3 [d1d4a3ce] + BitFlags v0.1.10 [336ed68f] + CSV v0.10.17 [da1fd8a2] + CodeTracking v3.0.2 [944b1d66] + CodecZlib v0.7.9 [35d6a980] + ColorSchemes v3.31.0 [3da002f7] + ColorTypes v0.12.1 [c3611d14] + ColorVectorSpace v0.11.0 [5ae59095] + Colors v0.13.1 [38540f10] + CommonSolve v0.2.14 [34da2185] + Compat v4.18.1 [807dbc54] + Compiler v0.1.1 [a33af91c] + CompositionsBase v0.1.2 [f0e56b4a] + ConcurrentUtilities v2.6.0 [187b0558] + ConstructionBase v1.6.0 [d38c429a] + Contour v0.6.3 [a8cc5b0e] + Crayons v4.2.0 [9a962f9c] + DataAPI v1.16.0 [a93c6f00] + DataFrames v1.8.2 ⌅ [864edb3b] + DataStructures v0.18.22 [e2d170a0] + DataValueInterfaces v1.0.0 [8bb1440f] + DelimitedFiles v1.9.1 [31c24e10] + Distributions v0.25.131 [ffbed154] + DocStringExtensions v0.9.5 [460bff9d] + ExceptionUnwrapping v0.1.11 [c87230d0] + FFMPEG v0.4.5 [48062228] + FilePathsBase v0.9.24 [1a297f60] + FillArrays v1.17.0 ⌅ [53c48c17] + FixedPointNumbers v0.8.6 [1fa38f19] + Format v1.3.7 [28b8d3ca] + GR v0.73.27 [92c85e6c] + GSL v1.0.1 [a0844989] + Gamma v1.2.0 [42e2da0e] + Grisu v1.0.2 ⌅ [cd3eb016] + HTTP v1.11.0 [34004b35] + HypergeometricFunctions v0.3.30 [842dd82b] + InlineStrings v1.4.5 [3587e190] + InverseFunctions v0.1.17 [41ab1584] + InvertedIndices v1.3.1 [92d709cd] + IrrationalConstants v0.2.6 [82899510] + IteratorInterfaceExtensions v1.0.0 [1019f520] + JLFzf v0.1.11 [692b3bcd] + JLLWrappers v1.8.0 [682c06a0] + JSON v1.7.1 [c9a035f4] + JWAS v2.4.0 [aa1ae85d] + JuliaInterpreter v0.11.4 [2c470bb0] + Kronecker v0.5.5 [b964fa9f] + LaTeXStrings v1.4.1 [23fbe1c1] + Latexify v0.16.12 [2ab3a3ac] + LogExpFunctions v1.0.1 [e6f89c97] + LoggingExtras v1.2.0 [6f1432cf] + LoweredCodeUtils v3.8.0 [1914dd2f] + MacroTools v0.5.16 [739be429] + MbedTLS v1.1.10 [442fdcdd] + Measures v0.3.3 [e1d29d7a] + Missings v1.2.0 [77ba4419] + NaNMath v1.1.4 [356022a1] + NamedDims v1.2.3 [4d8831e6] + OpenSSL v1.6.1 ⌅ [bac558e1] + OrderedCollections v1.8.2 ⌃ [90014a1f] + PDMats v0.11.35 ⌅ [69de0a69] + Parsers v2.8.7 [ccf2f8ad] + PlotThemes v3.3.0 [995b91a9] + PlotUtils v1.4.4 [91a5bcdd] + Plots v1.41.7 [2dfb63ee] + PooledArrays v1.4.3 [aea7be01] + PrecompileTools v1.3.4 [21216c6a] + Preferences v1.5.2 [08abe8d2] + PrettyTables v3.4.8 [92933f4c] + ProgressMeter v1.11.0 [43287f4e] + PtrArrays v1.4.0 [1fd47b50] + QuadGK v2.11.3 [3cdcf5f2] + RecipesBase v1.3.4 [01d81517] + RecipesPipeline v0.6.12 [189a3867] + Reexport v1.2.2 [05181044] + RelocatableFolders v1.0.1 [ae029012] + Requires v1.3.1 [295af30f] + Revise v3.16.5 [79098fc4] + Rmath v0.9.0 [f2b01f46] + Roots v3.0.7 [6c6a2e73] + Scratch v1.3.0 [91c51154] + SentinelArrays v1.4.10 [992d4aef] + Showoff v1.0.3 [777ac1f9] + SimpleBufferStream v1.2.0 [a2af1166] + SortingAlgorithms v1.2.3 [276daf66] + SpecialFunctions v2.9.0 [860ef19b] + StableRNGs v1.0.4 [10745b16] + Statistics v1.11.1 [82ae8749] + StatsAPI v1.8.0 ⌅ [2913bbd2] + StatsBase v0.33.10 [4c63d2b9] + StatsFuns v2.2.1 [892a3eda] + StringManipulation v0.5.0 [ec057cc2] + StructUtils v2.8.5 [3783bdb8] + TableTraits v1.0.1 [bd369af6] + Tables v1.14.0 [62fd8b95] + TensorCore v0.1.1 [3bb67fe8] + TranscodingStreams v0.11.3 [5c2747f8] + URIs v1.7.0 [1cfade01] + UnicodeFun v0.4.1 [41fe7b60] + Unzip v0.2.0 [ea10d353] + WeakRefStrings v1.4.3 [76eceee3] + WorkerUtilities v1.6.1 [6e34b625] + Bzip2_jll v1.0.9+0 [83423d85] + Cairo_jll v1.18.7+0 [ee1fde0b] + Dbus_jll v1.16.2+0 [2702e6a9] + EpollShim_jll v0.0.20230411+1 [2e619515] + Expat_jll v2.8.3+0 ⌅ [b22a6f82] + FFMPEG_jll v8.1.2+0 [a3f928ae] + Fontconfig_jll v2.17.1+0 [d7e528f0] + FreeType2_jll v2.14.3+1 [559328eb] + FriBidi_jll v1.0.17+0 [0656b61e] + GLFW_jll v3.5.1+0 [d2c73de3] + GR_jll v0.73.27+0 [1b77fbbe] + GSL_jll v2.8.1+0 ⌅ [b0724c58] + GettextRuntime_jll v0.22.4+0 [61579ee1] + Ghostscript_jll v9.55.1+0 [7746bdde] + Glib_jll v2.88.3+0 [3b182d85] + Graphite2_jll v1.3.16+0 ⌅ [2e76f6c2] + HarfBuzz_jll v8.5.1+0 [aacddb02] + JpegTurbo_jll v3.2.0+1 [c1c5ebd0] + LAME_jll v3.100.3+0 [88015f11] + LERC_jll v4.1.0+0 [1d63c593] + LLVMOpenMP_jll v22.1.7+0 ⌅ [e9f186c6] + Libffi_jll v3.4.7+0 [7e76a0d4] + Libglvnd_jll v1.7.1+1 [94ce4f54] + Libiconv_jll v1.18.0+0 [4b2f31a3] + Libmount_jll v2.42.0+0 [89763e89] + Libtiff_jll v4.7.3+0 [38a345b3] + Libuuid_jll v2.42.0+0 [c8ffd9c3] + MbedTLS_jll v2.28.1010+0 [e7412a2a] + Ogg_jll v1.3.6+0 [efe28fd5] + OpenSpecFun_jll v0.5.6+0 [91d4177d] + Opus_jll v1.6.1+0 [36c8627f] + Pango_jll v1.58.0+0 [30392449] + Pixman_jll v0.46.4+0 [c0090381] + Qt6Base_jll v6.10.2+2 [629bc702] + Qt6Declarative_jll v6.10.2+2 [ce943373] + Qt6ShaderTools_jll v6.10.2+1 [6de9746b] + Qt6Svg_jll v6.10.2+0 [e99dba38] + Qt6Wayland_jll v6.10.2+1 [f50d1b31] + Rmath_jll v0.5.2+0 [a44049a8] + Vulkan_Loader_jll v1.3.243+0 [a2964d1f] + Wayland_jll v1.24.0+0 [ffd25f8a] + XZ_jll v5.8.3+0 [f67eecfb] + Xorg_libICE_jll v1.1.2+0 [c834827a] + Xorg_libSM_jll v1.2.6+0 [4f6342f7] + Xorg_libX11_jll v1.8.13+0 [0c0b7dd1] + Xorg_libXau_jll v1.0.13+0 [935fb764] + Xorg_libXcursor_jll v1.2.4+0 [a3789734] + Xorg_libXdmcp_jll v1.1.6+0 [1082639a] + Xorg_libXext_jll v1.3.8+0 [d091e8ba] + Xorg_libXfixes_jll v6.0.2+0 [a51aa0fd] + Xorg_libXi_jll v1.8.4+0 [d1454406] + Xorg_libXinerama_jll v1.1.7+0 [ec84b674] + Xorg_libXrandr_jll v1.5.6+0 [ea2f1a96] + Xorg_libXrender_jll v0.9.12+0 [a65dc6b1] + Xorg_libpciaccess_jll v0.19.0+0 [c7cfdc94] + Xorg_libxcb_jll v1.17.1+0 [cc61e674] + Xorg_libxkbfile_jll v1.2.0+0 [e920d4aa] + Xorg_xcb_util_cursor_jll v0.1.6+0 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v8.21.0+0 [e37daf67] + LibGit2_jll v1.9.7+0 [29816b5a] + LibSSH2_jll v1.11.104+0 [14a3606d] + MozillaCACerts_jll v2026.8.13 [4536629a] + OpenBLAS_jll v0.3.34+0 [05823500] + OpenLibm_jll v0.8.7+0 [458c3c95] + OpenSSL_jll v3.5.8+0 [efcefdf7] + PCRE2_jll v10.47.0+0 [bea87d4a] + SuiteSparse_jll v7.10.1+0 [83775a58] + Zlib_jll v1.3.2+0 [3161d3a3] + Zstd_jll v1.5.7+1 [8e850b90] + libblastrampoline_jll v5.15.0+0 [8e850ede] + nghttp2_jll v1.70.0+0 [3f19e933] + p7zip_jll v17.8.2+0 Info Packages marked with ⌃ and ⌅ have new versions available. Those with ⌃ may be upgradable, but those with ⌅ are restricted by compatibility constraints from upgrading. To see why use `status --outdated -m` Installation completed after 32.2s ################################################################################ # Precompilation # Precompiling PkgEval dependencies... Precompiling project... 4.4 s ✓ TestEnv 1 dependency successfully precompiled in 5 seconds. 27 already precompiled. Precompiling package dependencies... Precompiling project... 3.2 s ✓ MacroTools 1.3 s ✓ InlineStrings 0.6 s ✓ Reexport 0.6 s ✓ TensorCore 0.7 s ✓ ConstructionBase 1.8 s ✓ IrrationalConstants 0.6 s ✓ Measures 0.4 s ✓ DataValueInterfaces 0.5 s ✓ StatsAPI 1.6 s ✓ Format 0.6 s ✓ Contour 0.8 s ✓ TranscodingStreams 0.5 s ✓ LaTeXStrings 0.8 s ✓ Statistics 0.6 s ✓ StableRNGs 0.5 s ✓ PtrArrays 0.5 s ✓ SimpleBufferStream 0.9 s ✓ Grisu 0.6 s ✓ DataAPI 0.9 s ✓ URIs 0.6 s ✓ InvertedIndices 0.6 s ✓ InverseFunctions 0.6 s ✓ BitFlags 0.5 s ✓ CompositionsBase 0.8 s ✓ WorkerUtilities 2.1 s ✓ FillArrays 1.5 s ✓ OrderedCollections 1.0 s ✓ DocStringExtensions 0.7 s ✓ Unzip 1.4 s ✓ Compiler 0.5 s ✓ IteratorInterfaceExtensions 2.0 s ✓ Crayons 0.7 s ✓ NaNMath 0.7 s ✓ Requires 1.2 s ✓ ConcurrentUtilities 2.2 s ✓ ProgressMeter 0.6 s ✓ DelimitedFiles 1.2 s ✓ Scratch 1.8 s ✓ SentinelArrays 1.2 s ✓ LoggingExtras 1.6 s ✓ StructUtils 2.0 s ✓ PDMats 0.8 s ✓ Compat 1.4 s ✓ Preferences 1.6 s ✓ ExceptionUnwrapping 4.1 s ✓ UnicodeFun 2.8 s ✓ CodeTracking 0.7 s ✓ ConstructionBase → ConstructionBaseLinearAlgebraExt 0.7 s ✓ CodecZlib 1.6 s ✓ Statistics → SparseArraysExt 2.3 s ✓ FixedPointNumbers 1.8 s ✓ NamedDims 0.8 s ✓ AliasTables 0.9 s ✓ Showoff 0.6 s ✓ Missings 1.0 s ✓ PooledArrays 0.9 s ✓ InverseFunctions → InverseFunctionsDatesExt 1.6 s ✓ InverseFunctions → InverseFunctionsTestExt 3.7 s ✓ OpenSSL 0.5 s ✓ CompositionsBase → CompositionsBaseInverseFunctionsExt 2.0 s ✓ FillArrays → FillArraysSparseArraysExt 0.9 s ✓ FillArrays → FillArraysStatisticsExt 1.0 s ✓ LogExpFunctions 0.5 s ✓ TableTraits 1.8 s ✓ RelocatableFolders 1.8 s ✓ FillArrays → FillArraysPDMatsExt 0.6 s ✓ Compat → CompatLinearAlgebraExt 1.4 s ✓ PrecompileTools 1.1 s ✓ JLLWrappers 10.6 s ✓ JuliaInterpreter 2.2 s ✓ ColorTypes 3.9 s ✓ Accessors 0.6 s ✓ LogExpFunctions → LogExpFunctionsInverseFunctionsExt 1.4 s ✓ Gamma 1.6 s ✓ Tables 2.0 s ✓ FilePathsBase 3.9 s ✓ DataStructures 5.6 s ✓ StringManipulation 3.1 s ✓ CommonSolve 2.8 s ✓ RecipesBase 10.0 s ✓ Parsers 2.4 s ✓ GSL_jll 2.2 s ✓ Libffi_jll 1.1 s ✓ Xorg_libICE_jll 1.1 s ✓ eudev_jll 1.2 s ✓ mtdev_jll 1.2 s ✓ Bzip2_jll 1.3 s ✓ XZ_jll 1.1 s ✓ Rmath_jll 1.1 s ✓ OpenSpecFun_jll 1.0 s ✓ Xorg_xtrans_jll 1.1 s ✓ Opus_jll 1.2 s ✓ x265_jll 1.0 s ✓ fzf_jll 1.1 s ✓ libpng_jll 0.8 s ✓ EpollShim_jll 1.0 s ✓ Libmount_jll 1.1 s ✓ libfdk_aac_jll 1.1 s ✓ Libuuid_jll 1.3 s ✓ FriBidi_jll 1.3 s ✓ LERC_jll 1.0 s ✓ Xorg_libXau_jll 1.1 s ✓ Ogg_jll 1.2 s ✓ libevdev_jll 1.6 s ✓ LAME_jll 1.0 s ✓ Graphite2_jll 1.4 s ✓ x264_jll 1.3 s ✓ Xorg_libpciaccess_jll 1.3 s ✓ LLVMOpenMP_jll 1.1 s ✓ Libiconv_jll 1.0 s ✓ MbedTLS_jll 1.9 s ✓ libaom_jll 1.0 s ✓ Xorg_libXdmcp_jll 1.1 s ✓ Expat_jll 1.2 s ✓ JpegTurbo_jll 19.4 s ✓ LoweredCodeUtils 1.0 s ✓ ColorTypes → StyledStringsExt 4.7 s ✓ Colors 1.4 s ✓ ColorVectorSpace 2.5 s ✓ Accessors → TestExt 2.1 s ✓ Accessors → LinearAlgebraExt 1.7 s ✓ HypergeometricFunctions 0.8 s ✓ StructUtils → StructUtilsTablesExt 2.5 s ✓ FilePathsBase → FilePathsBaseTestExt 0.9 s ✓ FilePathsBase → FilePathsBaseMmapExt 1.3 s ✓ SortingAlgorithms 2.4 s ✓ QuadGK 39.3 s ✓ PrettyTables 8.4 s ✓ JSON 0.8 s ✓ InlineStrings → ParsersExt 15.2 s ✓ GSL 1.2 s ✓ Xorg_libSM_jll 1.1 s ✓ FreeType2_jll 1.6 s ✓ Rmath 4.6 s ✓ SpecialFunctions 2.4 s ✓ JLFzf 1.1 s ✓ libvorbis_jll 1.1 s ✓ libinput_jll 1.7 s ✓ libdrm_jll 1.2 s ✓ Pixman_jll 1.2 s ✓ GettextRuntime_jll 1.6 s ✓ MbedTLS 1.3 s ✓ Xorg_libxcb_jll 1.4 s ✓ Dbus_jll 1.3 s ✓ Wayland_jll 1.5 s ✓ Ghostscript_jll 1.4 s ✓ Libtiff_jll 7.5 s ✓ Revise 9.6 s ✓ ColorSchemes 5.2 s ✓ Roots 4.7 s ✓ StatsBase 76.6 s ✓ DataFrames 2.3 s ✓ WeakRefStrings 1.5 s ✓ Fontconfig_jll 1.4 s ✓ ColorVectorSpace → SpecialFunctionsExt 2.0 s ✓ StatsFuns 1.1 s ✓ Glib_jll 26.5 s ✓ HTTP 1.1 s ✓ Xorg_xcb_util_jll 1.0 s ✓ Xorg_libX11_jll 5.6 s ✓ Latexify 8.3 s ✓ Revise → DistributedExt 15.8 s ✓ PlotUtils 3.5 s ✓ Kronecker 27.0 s ✓ CSV 1.2 s ✓ StatsFuns → StatsFunsInverseFunctionsExt 1.1 s ✓ Xorg_xcb_util_renderutil_jll 1.3 s ✓ Xorg_xcb_util_wm_jll 1.5 s ✓ Xorg_xcb_util_image_jll 1.1 s ✓ Xorg_xcb_util_keysyms_jll 2.4 s ✓ Xorg_libXfixes_jll 1.2 s ✓ Xorg_libXrender_jll 1.2 s ✓ Xorg_libXext_jll 1.6 s ✓ Xorg_libxkbfile_jll 2.5 s ✓ Latexify → SparseArraysExt 6.7 s ✓ Latexify → DataFramesExt 9.1 s ✓ PlotThemes 7.7 s ✓ RecipesPipeline 11.7 s ✓ Distributions 1.3 s ✓ Xorg_xcb_util_cursor_jll 1.2 s ✓ Xorg_libXcursor_jll 1.1 s ✓ Xorg_libXrandr_jll 1.4 s ✓ Xorg_libXinerama_jll 1.4 s ✓ Xorg_libXi_jll 1.3 s ✓ Cairo_jll 1.2 s ✓ libva_jll 1.2 s ✓ Libglvnd_jll 1.5 s ✓ Xorg_xkbcomp_jll 4.5 s ✓ Distributions → DistributionsTestExt 1.4 s ✓ HarfBuzz_jll 0.9 s ✓ Xorg_xkeyboard_config_jll 1.4 s ✓ libass_jll 1.3 s ✓ Pango_jll 1.2 s ✓ xkbcommon_jll 2.2 s ✓ FFMPEG_jll 2.7 s ✓ Vulkan_Loader_jll 1.7 s ✓ libdecor_jll 0.9 s ✓ FFMPEG 1.4 s ✓ Qt6Base_jll 1.1 s ✓ GLFW_jll 1.3 s ✓ Qt6ShaderTools_jll 2.0 s ✓ Qt6Svg_jll 1.4 s ✓ GR_jll 1.4 s ✓ Qt6Declarative_jll 1.7 s ✓ Qt6Wayland_jll 5.5 s ✓ GR ERROR: LoadError: MethodError: no method matching floatrange(::Float64, ::Float64, ::Int64, ::Float64) The function `floatrange` exists, but no method is defined for this combination of argument types. Closest candidates are: floatrange(!Matched::Type{T}, !Matched::Integer, ::Integer, !Matched::Integer, !Matched::Integer) where T @ Base twiceprecision.jl:380 Stacktrace: [1] histrange(lo::Float64, hi::Float64, n::Int64, closed::Symbol) @ StatsBase ~/.julia/packages/StatsBase/PGTj8/src/hist.jl:99 [2] histrange(v::Vector{Float64}, n::Int64, closed::Symbol) @ StatsBase ~/.julia/packages/StatsBase/PGTj8/src/hist.jl:39 [3] _hist_edge(vs::Tuple{Vector{Float64}, Vector{Float64}}, dim::Int64, binning::Int64) @ Plots ~/.julia/packages/Plots/h49MV/src/recipes.jl:761 [inlined] [4] (::Plots.var"#_hist_edges##2#_hist_edges##3"{Tuple{Vector{Float64}, Vector{Float64}}, Int64})(dim::Int64) @ Plots ~/.julia/packages/Plots/h49MV/src/recipes.jl:774 [inlined] [5] map(f::Plots.var"#_hist_edges##2#_hist_edges##3"{Tuple{Vector{Float64}, Vector{Float64}}, Int64}, t::Tuple{Int64, Int64}) @ Base tuple.jl:360 [6] _hist_edges(vs::Tuple{Vector{Float64}, Vector{Float64}}, binning::Int64) @ Plots ~/.julia/packages/Plots/h49MV/src/recipes.jl:771 [7] _make_hist(vs::Tuple{Vector{Float64}, Vector{Float64}}, binning::Int64; normed::Bool, weights::Nothing) @ Plots ~/.julia/packages/Plots/h49MV/src/recipes.jl:794 [8] macro expansion @ ~/.julia/packages/Plots/h49MV/src/recipes.jl:914 [inlined] [9] apply_recipe(plotattributes::AbstractDict{Symbol, Any}, ::Type{Val{:histogram2d}}, x::Any, y::Any, z::Any) @ Plots ~/.julia/packages/RecipesBase/BRe07/src/RecipesBase.jl:300 [10] _process_seriesrecipe(plt::Any, plotattributes::Any) @ RecipesPipeline ~/.julia/packages/RecipesPipeline/BGM3l/src/series_recipe.jl:50 [11] _process_seriesrecipes!(plt::Any, kw_list::Any) @ RecipesPipeline ~/.julia/packages/RecipesPipeline/BGM3l/src/series_recipe.jl:27 [12] recipe_pipeline!(plt::Any, plotattributes::Any, args::Any) @ RecipesPipeline ~/.julia/packages/RecipesPipeline/BGM3l/src/RecipesPipeline.jl:99 [13] _plot!(plt::Plots.Plot, plotattributes::Any, args::Any) @ Plots ~/.julia/packages/Plots/h49MV/src/plot.jl:223 [14] plot(::Vector{Float64}, ::Vector{Float64}; kw::@Kwargs{nbins::Int64, seriestype::Symbol}) @ Plots ~/.julia/packages/Plots/h49MV/src/plot.jl:102 [inlined] [15] histogram2d(::Vector{Float64}, ::Vector{Float64}; kw::@Kwargs{nbins::Int64}) @ Plots ~/.julia/packages/RecipesBase/BRe07/src/RecipesBase.jl:427 [inlined] [16] var"##10#156"() @ Plots ~/.julia/packages/Plots/h49MV/src/init.jl:111 [17] top-level scope @ ~/.julia/packages/Plots/h49MV/src/init.jl:123 [18] eval(m::Module, e::Any) @ Core boot.jl:618 [19] _broadcast_getindex_evalf(f::Core.EvalInto, args::Expr) @ Base.Broadcast broadcast.jl:703 [inlined] [20] _broadcast_getindex(bc::Base.Broadcast.Broadcasted{Base.Broadcast.DefaultArrayStyle{1}, Tuple{Base.OneTo{Int64}}, Core.EvalInto, Tuple{Base.Broadcast.Extruded{Vector{Expr}, Tuple{Bool}, Tuple{Int64}}}}, I::Int64) @ Base.Broadcast broadcast.jl:676 [inlined] [21] _getindex(::IndexLinear, bc::Base.Broadcast.Broadcasted{Base.Broadcast.DefaultArrayStyle{1}, Tuple{Base.OneTo{Int64}}, Core.EvalInto, Tuple{Base.Broadcast.Extruded{Vector{Expr}, Tuple{Bool}, Tuple{Int64}}}}, I::Int64) @ Base.Broadcast broadcast.jl:620 [inlined] [22] getindex(bc::Base.Broadcast.Broadcasted{Base.Broadcast.DefaultArrayStyle{1}, Tuple{Base.OneTo{Int64}}, Core.EvalInto, Tuple{Base.Broadcast.Extruded{Vector{Expr}, Tuple{Bool}, Tuple{Int64}}}}, Is::Int64) @ Base.Broadcast broadcast.jl:616 [inlined] [23] copyto_nonleaf!(dest::Vector{Nothing}, bc::Base.Broadcast.Broadcasted{Base.Broadcast.DefaultArrayStyle{1}, Tuple{Base.OneTo{Int64}}, Core.EvalInto, Tuple{Base.Broadcast.Extruded{Vector{Expr}, Tuple{Bool}, Tuple{Int64}}}}, iter::Base.OneTo{Int64}, state::Int64, count::Int64) @ Base.Broadcast broadcast.jl:1136 [24] copy(bc::Base.Broadcast.Broadcasted{Base.Broadcast.DefaultArrayStyle{1}, Tuple{Base.OneTo{Int64}}, Core.EvalInto, Tuple{Vector{Expr}}}) @ Base.Broadcast broadcast.jl:973 [inlined] [25] materialize(bc::Base.Broadcast.Broadcasted{Base.Broadcast.DefaultArrayStyle{1}, Nothing, Core.EvalInto, Tuple{Vector{Expr}}}) @ Base.Broadcast broadcast.jl:920 [inlined] [26] (::Plots.var"#491#492"{Vector{Expr}, Vector{Expr}})() @ Plots ~/.julia/packages/Plots/h49MV/src/init.jl:131 [27] withenv(::Plots.var"#491#492"{Vector{Expr}, Vector{Expr}}, ::Pair{String, String}, ::Vararg{Pair{String, String}}) @ Base env.jl:283 [28] macro expansion @ ~/.julia/packages/Plots/h49MV/src/init.jl:128 [inlined] [29] macro expansion @ ~/.julia/packages/PrecompileTools/QUxvR/src/workloads.jl:70 [inlined] [30] macro expansion @ ~/.julia/packages/Plots/h49MV/src/init.jl:127 [inlined] [31] macro expansion @ ~/.julia/packages/PrecompileTools/QUxvR/src/workloads.jl:118 [inlined] [32] top-level scope @ ~/.julia/packages/Plots/h49MV/src/init.jl:115 [33] include(mapexpr::Function, mod::Module, _path::String) @ Base Base.jl:335 [34] top-level scope @ ~/.julia/packages/Plots/h49MV/src/Plots.jl:176 [35] include(mod::Module, _path::String) @ Base Base.jl:334 [36] top-level scope @ stdin:5 in expression starting at /home/pkgeval/.julia/packages/Plots/h49MV/src/init.jl:97 in expression starting at /home/pkgeval/.julia/packages/Plots/h49MV/src/Plots.jl:1 in expression starting at stdin:5 ✗ Plots 13.9 s ✓ JWAS 207 dependencies successfully precompiled in 674 seconds. 40 already precompiled. 1 dependency had output during precompilation: ┌ Plots │ ERROR: LoadError: MethodError: no method matching floatrange(::Float64, ::Float64, ::Int64, ::Float64) │ The function `floatrange` exists, but no method is defined for this combination of argument types. │ │ Closest candidates are: │ floatrange(!Matched::Type{T}, !Matched::Integer, ::Integer, !Matched::Integer, !Matched::Integer) where T │ @ Base twiceprecision.jl:380 │ │ Stacktrace: │ [1] histrange(lo::Float64, hi::Float64, n::Int64, closed::Symbol) │ @ StatsBase ~/.julia/packages/StatsBase/PGTj8/src/hist.jl:99 │ [2] histrange(v::Vector{Float64}, n::Int64, closed::Symbol) │ @ StatsBase ~/.julia/packages/StatsBase/PGTj8/src/hist.jl:39 │ [3] _hist_edge(vs::Tuple{Vector{Float64}, Vector{Float64}}, dim::Int64, binning::Int64) │ @ Plots ~/.julia/packages/Plots/h49MV/src/recipes.jl:761 [inlined] │ [4] (::Plots.var"#_hist_edges##2#_hist_edges##3"{Tuple{Vector{Float64}, Vector{Float64}}, Int64})(dim::Int64) │ @ Plots ~/.julia/packages/Plots/h49MV/src/recipes.jl:774 [inlined] │ [5] map(f::Plots.var"#_hist_edges##2#_hist_edges##3"{Tuple{Vector{Float64}, Vector{Float64}}, Int64}, t::Tuple{Int64, Int64}) │ @ Base tuple.jl:360 │ [6] _hist_edges(vs::Tuple{Vector{Float64}, Vector{Float64}}, binning::Int64) │ @ Plots ~/.julia/packages/Plots/h49MV/src/recipes.jl:771 │ [7] _make_hist(vs::Tuple{Vector{Float64}, Vector{Float64}}, binning::Int64; normed::Bool, weights::Nothing) │ @ Plots ~/.julia/packages/Plots/h49MV/src/recipes.jl:794 │ [8] macro expansion │ @ ~/.julia/packages/Plots/h49MV/src/recipes.jl:914 [inlined] │ [9] apply_recipe(plotattributes::AbstractDict{Symbol, Any}, ::Type{Val{:histogram2d}}, x::Any, y::Any, z::Any) │ @ Plots ~/.julia/packages/RecipesBase/BRe07/src/RecipesBase.jl:300 │ [10] _process_seriesrecipe(plt::Any, plotattributes::Any) │ @ RecipesPipeline ~/.julia/packages/RecipesPipeline/BGM3l/src/series_recipe.jl:50 │ [11] _process_seriesrecipes!(plt::Any, kw_list::Any) │ @ RecipesPipeline ~/.julia/packages/RecipesPipeline/BGM3l/src/series_recipe.jl:27 │ [12] recipe_pipeline!(plt::Any, plotattributes::Any, args::Any) │ @ RecipesPipeline ~/.julia/packages/RecipesPipeline/BGM3l/src/RecipesPipeline.jl:99 │ [13] _plot!(plt::Plots.Plot, plotattributes::Any, args::Any) │ @ Plots ~/.julia/packages/Plots/h49MV/src/plot.jl:223 │ [14] plot(::Vector{Float64}, ::Vector{Float64}; kw::@Kwargs{nbins::Int64, seriestype::Symbol}) │ @ Plots ~/.julia/packages/Plots/h49MV/src/plot.jl:102 [inlined] │ [15] histogram2d(::Vector{Float64}, ::Vector{Float64}; kw::@Kwargs{nbins::Int64}) │ @ Plots ~/.julia/packages/RecipesBase/BRe07/src/RecipesBase.jl:427 [inlined] │ [16] var"##10#156"() │ @ Plots ~/.julia/packages/Plots/h49MV/src/init.jl:111 │ [17] top-level scope │ @ ~/.julia/packages/Plots/h49MV/src/init.jl:123 │ [18] eval(m::Module, e::Any) │ @ Core boot.jl:618 │ [19] _broadcast_getindex_evalf(f::Core.EvalInto, args::Expr) │ @ Base.Broadcast broadcast.jl:703 [inlined] │ [20] _broadcast_getindex(bc::Base.Broadcast.Broadcasted{Base.Broadcast.DefaultArrayStyle{1}, Tuple{Base.OneTo{Int64}}, Core.EvalInto, Tuple{Base.Broadcast.Extruded{Vector{Expr}, Tuple{Bool}, Tuple{Int64}}}}, I::Int64) │ @ Base.Broadcast broadcast.jl:676 [inlined] │ [21] _getindex(::IndexLinear, bc::Base.Broadcast.Broadcasted{Base.Broadcast.DefaultArrayStyle{1}, Tuple{Base.OneTo{Int64}}, Core.EvalInto, Tuple{Base.Broadcast.Extruded{Vector{Expr}, Tuple{Bool}, Tuple{Int64}}}}, I::Int64) │ @ Base.Broadcast broadcast.jl:620 [inlined] │ [22] getindex(bc::Base.Broadcast.Broadcasted{Base.Broadcast.DefaultArrayStyle{1}, Tuple{Base.OneTo{Int64}}, Core.EvalInto, Tuple{Base.Broadcast.Extruded{Vector{Expr}, Tuple{Bool}, Tuple{Int64}}}}, Is::Int64) │ @ Base.Broadcast broadcast.jl:616 [inlined] │ [23] copyto_nonleaf!(dest::Vector{Nothing}, bc::Base.Broadcast.Broadcasted{Base.Broadcast.DefaultArrayStyle{1}, Tuple{Base.OneTo{Int64}}, Core.EvalInto, Tuple{Base.Broadcast.Extruded{Vector{Expr}, Tuple{Bool}, Tuple{Int64}}}}, iter::Base.OneTo{Int64}, state::Int64, count::Int64) │ @ Base.Broadcast broadcast.jl:1136 │ [24] copy(bc::Base.Broadcast.Broadcasted{Base.Broadcast.DefaultArrayStyle{1}, Tuple{Base.OneTo{Int64}}, Core.EvalInto, Tuple{Vector{Expr}}}) │ @ Base.Broadcast broadcast.jl:973 [inlined] │ [25] materialize(bc::Base.Broadcast.Broadcasted{Base.Broadcast.DefaultArrayStyle{1}, Nothing, Core.EvalInto, Tuple{Vector{Expr}}}) │ @ Base.Broadcast broadcast.jl:920 [inlined] │ [26] (::Plots.var"#491#492"{Vector{Expr}, Vector{Expr}})() │ @ Plots ~/.julia/packages/Plots/h49MV/src/init.jl:131 │ [27] withenv(::Plots.var"#491#492"{Vector{Expr}, Vector{Expr}}, ::Pair{String, String}, ::Vararg{Pair{String, String}}) │ @ Base env.jl:283 │ [28] macro expansion │ @ ~/.julia/packages/Plots/h49MV/src/init.jl:128 [inlined] │ [29] macro expansion │ @ ~/.julia/packages/PrecompileTools/QUxvR/src/workloads.jl:70 [inlined] │ [30] macro expansion │ @ ~/.julia/packages/Plots/h49MV/src/init.jl:127 [inlined] │ [31] macro expansion │ @ ~/.julia/packages/PrecompileTools/QUxvR/src/workloads.jl:118 [inlined] │ [32] top-level scope │ @ ~/.julia/packages/Plots/h49MV/src/init.jl:115 │ [33] include(mapexpr::Function, mod::Module, _path::String) │ @ Base Base.jl:335 │ [34] top-level scope │ @ ~/.julia/packages/Plots/h49MV/src/Plots.jl:176 │ [35] include(mod::Module, _path::String) │ @ Base Base.jl:334 │ [36] top-level scope │ @ stdin:5 │ in expression starting at /home/pkgeval/.julia/packages/Plots/h49MV/src/init.jl:97 │ in expression starting at /home/pkgeval/.julia/packages/Plots/h49MV/src/Plots.jl:1 │ in expression starting at stdin:5 └ ERROR: LoadError: The following 1 package failed to precompile: Plots Failed to precompile Plots [91a5bcdd-55d7-5caf-9e0b-520d859cae80] to "/home/pkgeval/.julia/compiled/v1.14/Plots/jl_KbgrGu" (ProcessExited(1)). in expression starting at /PkgEval.jl/scripts/precompile.jl:34 Precompilation failed after 657.79s ################################################################################ # Testing # Testing JWAS Status `/tmp/jl_g0vHag/Project.toml` [336ed68f] CSV v0.10.17 [a93c6f00] DataFrames v1.8.2 [8bb1440f] DelimitedFiles v1.9.1 [31c24e10] Distributions v0.25.131 [92c85e6c] GSL v1.0.1 ⌅ [cd3eb016] HTTP v1.11.0 [c9a035f4] JWAS v2.4.0 [2c470bb0] Kronecker v0.5.5 [91a5bcdd] Plots v1.41.7 [92933f4c] ProgressMeter v1.11.0 [295af30f] Revise v3.16.5 [10745b16] Statistics v1.11.1 ⌅ [2913bbd2] StatsBase v0.33.10 [b77e0a4c] InteractiveUtils v1.11.0 [37e2e46d] LinearAlgebra v1.14.0 [de0858da] Printf v1.11.0 [9a3f8284] Random v1.11.0 [2f01184e] SparseArrays v1.13.0 [8dfed614] Test v1.11.0 Status `/tmp/jl_g0vHag/Manifest.toml` [7d9f7c33] Accessors v0.1.45 [66dad0bd] AliasTables v1.1.3 [d1d4a3ce] BitFlags v0.1.10 [336ed68f] CSV v0.10.17 [da1fd8a2] CodeTracking v3.0.2 [944b1d66] CodecZlib v0.7.9 [35d6a980] ColorSchemes v3.31.0 [3da002f7] ColorTypes v0.12.1 [c3611d14] ColorVectorSpace v0.11.0 [5ae59095] Colors v0.13.1 [38540f10] CommonSolve v0.2.14 [34da2185] Compat v4.18.1 [807dbc54] Compiler v0.1.1 [a33af91c] CompositionsBase v0.1.2 [f0e56b4a] ConcurrentUtilities v2.6.0 [187b0558] ConstructionBase v1.6.0 [d38c429a] Contour v0.6.3 [a8cc5b0e] Crayons v4.2.0 [9a962f9c] DataAPI v1.16.0 [a93c6f00] DataFrames v1.8.2 ⌅ [864edb3b] DataStructures v0.18.22 [e2d170a0] DataValueInterfaces v1.0.0 [8bb1440f] DelimitedFiles v1.9.1 [31c24e10] Distributions v0.25.131 [ffbed154] DocStringExtensions v0.9.5 [460bff9d] ExceptionUnwrapping v0.1.11 [c87230d0] FFMPEG v0.4.5 [48062228] FilePathsBase v0.9.24 [1a297f60] FillArrays v1.17.0 ⌅ [53c48c17] FixedPointNumbers v0.8.6 [1fa38f19] Format v1.3.7 [28b8d3ca] GR v0.73.27 [92c85e6c] GSL v1.0.1 [a0844989] Gamma v1.2.0 [42e2da0e] Grisu v1.0.2 ⌅ [cd3eb016] HTTP v1.11.0 [34004b35] HypergeometricFunctions v0.3.30 [842dd82b] InlineStrings v1.4.5 [3587e190] InverseFunctions v0.1.17 [41ab1584] InvertedIndices v1.3.1 [92d709cd] IrrationalConstants v0.2.6 [82899510] IteratorInterfaceExtensions v1.0.0 [1019f520] JLFzf v0.1.11 [692b3bcd] JLLWrappers v1.8.0 [682c06a0] JSON v1.7.1 [c9a035f4] JWAS v2.4.0 [aa1ae85d] JuliaInterpreter v0.11.4 [2c470bb0] Kronecker v0.5.5 [b964fa9f] LaTeXStrings v1.4.1 [23fbe1c1] Latexify v0.16.12 [2ab3a3ac] LogExpFunctions v1.0.1 [e6f89c97] LoggingExtras v1.2.0 [6f1432cf] LoweredCodeUtils v3.8.0 [1914dd2f] MacroTools v0.5.16 [739be429] MbedTLS v1.1.10 [442fdcdd] Measures v0.3.3 [e1d29d7a] Missings v1.2.0 [77ba4419] NaNMath v1.1.4 [356022a1] NamedDims v1.2.3 [4d8831e6] OpenSSL v1.6.1 ⌅ [bac558e1] OrderedCollections v1.8.2 ⌃ [90014a1f] PDMats v0.11.35 ⌅ [69de0a69] Parsers v2.8.7 [ccf2f8ad] PlotThemes v3.3.0 [995b91a9] PlotUtils v1.4.4 [91a5bcdd] Plots v1.41.7 [2dfb63ee] PooledArrays v1.4.3 [aea7be01] PrecompileTools v1.3.4 [21216c6a] Preferences v1.5.2 [08abe8d2] PrettyTables v3.4.8 [92933f4c] ProgressMeter v1.11.0 [43287f4e] PtrArrays v1.4.0 [1fd47b50] QuadGK v2.11.3 [3cdcf5f2] RecipesBase v1.3.4 [01d81517] RecipesPipeline v0.6.12 [189a3867] Reexport v1.2.2 [05181044] RelocatableFolders v1.0.1 [ae029012] Requires v1.3.1 [295af30f] Revise v3.16.5 [79098fc4] Rmath v0.9.0 [f2b01f46] Roots v3.0.7 [6c6a2e73] Scratch v1.3.0 [91c51154] SentinelArrays v1.4.10 [992d4aef] Showoff v1.0.3 [777ac1f9] SimpleBufferStream v1.2.0 [a2af1166] SortingAlgorithms v1.2.3 [276daf66] SpecialFunctions v2.9.0 [860ef19b] StableRNGs v1.0.4 [10745b16] Statistics v1.11.1 [82ae8749] StatsAPI v1.8.0 ⌅ [2913bbd2] StatsBase v0.33.10 [4c63d2b9] StatsFuns v2.2.1 [892a3eda] StringManipulation v0.5.0 [ec057cc2] StructUtils v2.8.5 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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 v1.5.7+0 [deac9b47] LibCURL_jll v8.21.0+0 [e37daf67] LibGit2_jll v1.9.7+0 [29816b5a] LibSSH2_jll v1.11.104+0 [14a3606d] MozillaCACerts_jll v2026.8.13 [4536629a] OpenBLAS_jll v0.3.34+0 [05823500] OpenLibm_jll v0.8.7+0 [458c3c95] OpenSSL_jll v3.5.8+0 [efcefdf7] PCRE2_jll v10.47.0+0 [bea87d4a] SuiteSparse_jll v7.10.1+0 [83775a58] Zlib_jll v1.3.2+0 [3161d3a3] Zstd_jll v1.5.7+1 [8e850b90] libblastrampoline_jll v5.15.0+0 [8e850ede] nghttp2_jll v1.70.0+0 [3f19e933] p7zip_jll v17.8.2+0 Info Packages marked with ⌃ and ⌅ have new versions available. Those with ⌃ may be upgradable, but those with ⌅ are restricted by compatibility constraints from upgrading. Testing Running tests... ====================================================================== JWAS.jl Comprehensive Test Suite ====================================================================== Cleaning up old test artifacts... Cleanup complete. ====================================================================== Running tests in: test_run_40086 ====================================================================== Test Configuration: Unit Tests: Always run ✓ Integration Tests: Disabled (set RUN_INTEGRATION_TESTS=true) ====================================================================== ┌ Warning: Estimated marker memory usage exceeds configured guard threshold. │ context: test │ estimated: 600.00 B │ threshold (50.0% of RAM): 500.00 B │ system RAM: 1000.00 B │ Set memory_guard=:warn or :off to override, or reduce model/data size. └ @ JWAS ~/.julia/packages/JWAS/AxFc6/src/1.JWAS/src/markers/tools4genotypes.jl:231 The delimiter in genotypes.txt is ','. The header (marker IDs) is provided in genotypes.txt. Missing values (9.0) are replaced by column means. runMCMC throws early in :error mode when guard threshold is tiny: Error During Test at /home/pkgeval/.julia/packages/JWAS/AxFc6/test/unit/test_memory_guardrails.jl:123 Got exception outside of a @test MethodError: no method matching reducedim1(::Matrix{Float32}, ::Matrix{Float32}) The function `reducedim1` exists, but no method is defined for this combination of argument types. Closest candidates are: reducedim1(::Any) @ Base reducedim.jl:1229 Stacktrace: [1] centralize_sumabs2!(R::Matrix{Float32}, A::Matrix{Float32}, means::Matrix{Float32}) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:282 [2] varm!(R::Matrix{Float32}, A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:309 [3] _varm(A::Matrix{Float32}, m::Matrix{Float32}, corrected::Bool, region::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:341 [4] varm(A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:339 [inlined] [5] _var(A::Matrix{Float32}, corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:386 [inlined] [6] var(A::Matrix{Float32}; corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:380 [inlined] [7] get_genotypes(file::String, G::Float64; method::String, Pi::Float64, estimatePi::Bool, G_is_marker_variance::Bool, df::Float64, estimate_variance::Bool, estimate_scale::Bool, constraint::Bool, separator::Char, header::Bool, double_precision::Bool, quality_control::Bool, MAF::Float64, missing_value::Float64, center::Bool, starting_value::Bool, annotations::Bool, multi_trait_sampler::Symbol, storage::Symbol) @ JWAS ~/.julia/packages/JWAS/AxFc6/src/1.JWAS/src/markers/readgenotypes.jl:390 [8] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_memory_guardrails.jl:124 [inlined] [9] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [10] (::var"#5#6"{DataFrame, String})() @ Main ~/.julia/packages/JWAS/AxFc6/test/unit/test_memory_guardrails.jl:124 The delimiter in genotypes.txt is ','. The header (marker IDs) is provided in genotypes.txt. Missing values (9.0) are replaced by column means. runMCMC proceeds in :off mode with same threshold: Error During Test at /home/pkgeval/.julia/packages/JWAS/AxFc6/test/unit/test_memory_guardrails.jl:136 Got exception outside of a @test MethodError: no method matching reducedim1(::Matrix{Float32}, ::Matrix{Float32}) The function `reducedim1` exists, but no method is defined for this combination of argument types. Closest candidates are: reducedim1(::Any) @ Base reducedim.jl:1229 Stacktrace: [1] centralize_sumabs2!(R::Matrix{Float32}, A::Matrix{Float32}, means::Matrix{Float32}) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:282 [2] varm!(R::Matrix{Float32}, A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:309 [3] _varm(A::Matrix{Float32}, m::Matrix{Float32}, corrected::Bool, region::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:341 [4] varm(A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:339 [inlined] [5] _var(A::Matrix{Float32}, corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:386 [inlined] [6] var(A::Matrix{Float32}; corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:380 [inlined] [7] get_genotypes(file::String, G::Float64; method::String, Pi::Float64, estimatePi::Bool, G_is_marker_variance::Bool, df::Float64, estimate_variance::Bool, estimate_scale::Bool, constraint::Bool, separator::Char, header::Bool, double_precision::Bool, quality_control::Bool, MAF::Float64, missing_value::Float64, center::Bool, starting_value::Bool, annotations::Bool, multi_trait_sampler::Symbol, storage::Symbol) @ JWAS ~/.julia/packages/JWAS/AxFc6/src/1.JWAS/src/markers/readgenotypes.jl:390 [8] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_memory_guardrails.jl:137 [inlined] [9] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [10] (::var"#5#6"{DataFrame, String})() @ Main ~/.julia/packages/JWAS/AxFc6/test/unit/test_memory_guardrails.jl:137 Memory guardrails: runMCMC integration: Test Failed at /home/pkgeval/.julia/packages/JWAS/AxFc6/test/unit/test_memory_guardrails.jl:153 Expression: isfile(joinpath("guardrail_off_mode", "IDs_for_individuals_with_genotypes.txt")) Evaluated: isfile("guardrail_off_mode/IDs_for_individuals_with_genotypes.txt") Stacktrace: [1] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:784 [inlined] [2] (::var"#5#6"{DataFrame, String})() @ Main ~/.julia/packages/JWAS/AxFc6/test/unit/test_memory_guardrails.jl:153 [3] cd(f::var"#5#6"{DataFrame, String}, dir::String) @ Base.Filesystem file.jl:113 [4] (::var"#3#4"{DataFrame, String})(tmpdir::String) @ Main ~/.julia/packages/JWAS/AxFc6/test/unit/test_memory_guardrails.jl:122 [inlined] [5] mktempdir(fn::var"#3#4"{DataFrame, String}, parent::String; prefix::String) @ Base.Filesystem file.jl:949 [6] mktempdir(fn::Function, parent::String) @ Base.Filesystem file.jl:945 [7] top-level scope @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_memory_guardrails.jl:118 [8] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [9] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_memory_guardrails.jl:121 [inlined] Memory guardrails: runMCMC integration: Test Failed at /home/pkgeval/.julia/packages/JWAS/AxFc6/test/unit/test_memory_guardrails.jl:154 Expression: isfile(joinpath("guardrail_off_mode", "IDs_for_individuals_with_phenotypes.txt")) Evaluated: isfile("guardrail_off_mode/IDs_for_individuals_with_phenotypes.txt") Stacktrace: [1] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:784 [inlined] [2] (::var"#5#6"{DataFrame, String})() @ Main ~/.julia/packages/JWAS/AxFc6/test/unit/test_memory_guardrails.jl:154 [3] cd(f::var"#5#6"{DataFrame, String}, dir::String) @ Base.Filesystem file.jl:113 [4] (::var"#3#4"{DataFrame, String})(tmpdir::String) @ Main ~/.julia/packages/JWAS/AxFc6/test/unit/test_memory_guardrails.jl:122 [inlined] [5] mktempdir(fn::var"#3#4"{DataFrame, String}, parent::String; prefix::String) @ Base.Filesystem file.jl:949 [6] mktempdir(fn::Function, parent::String) @ Base.Filesystem file.jl:945 [7] top-level scope @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_memory_guardrails.jl:118 [8] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [9] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_memory_guardrails.jl:121 [inlined] 0 loci which are fixed or have minor allele frequency < 0.01 are removed. Streaming genotype files are created with prefix /tmp/jl_aXolfl/geno_missing_stream. The delimiter in geno_missing.csv is ','. The header (marker IDs) is provided in geno_missing.csv. Missing values (9.0) are replaced by column means. prepare + load + decode: Error During Test at /home/pkgeval/.julia/packages/JWAS/AxFc6/test/unit/test_streaming_codec.jl:21 Got exception outside of a @test MethodError: no method matching reducedim1(::Matrix{Float32}, ::Matrix{Float32}) The function `reducedim1` exists, but no method is defined for this combination of argument types. Closest candidates are: reducedim1(::Any) @ Base reducedim.jl:1229 Stacktrace: [1] centralize_sumabs2!(R::Matrix{Float32}, A::Matrix{Float32}, means::Matrix{Float32}) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:282 [2] varm!(R::Matrix{Float32}, A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:309 [3] _varm(A::Matrix{Float32}, m::Matrix{Float32}, corrected::Bool, region::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:341 [4] varm(A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:339 [inlined] [5] _var(A::Matrix{Float32}, corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:386 [inlined] [6] var(A::Matrix{Float32}; corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:380 [inlined] [7] get_genotypes(file::String, G::Float64; method::String, Pi::Float64, estimatePi::Bool, G_is_marker_variance::Bool, df::Float64, estimate_variance::Bool, estimate_scale::Bool, constraint::Bool, separator::Char, header::Bool, double_precision::Bool, quality_control::Bool, MAF::Float64, missing_value::Float64, center::Bool, starting_value::Bool, annotations::Bool, multi_trait_sampler::Symbol, storage::Symbol) @ JWAS ~/.julia/packages/JWAS/AxFc6/src/1.JWAS/src/markers/readgenotypes.jl:390 [8] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_streaming_codec.jl:32 [inlined] [9] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [10] (::var"#19#20")() @ Main ~/.julia/packages/JWAS/AxFc6/test/unit/test_streaming_codec.jl:22 Streaming genotype files are created with prefix /tmp/jl_aXolfl/geno_nomissing_stream. The delimiter in geno_nomissing.csv is ','. The header (marker IDs) is provided in geno_nomissing.csv. Genotype informatin: #markers: 4; #individuals: 6 The folder dense_results is created to save results. Checking genotypes... Checking phenotypes... Individual IDs (strings) are provided in the first column of the phenotypic data. Predicted values for individuals of interest will be obtained as the summation of Any[] (Note that genomic data is always included for now).Phenotypes for 6 observations are used in the analysis.These individual IDs are saved in the file dense_results/IDs_for_individuals_with_phenotypes.txt. The prior for marker effects variance is calculated from the genetic variance and π. The mean of the prior for the marker effects variance is: 0.503496 A Linear Mixed Model was build using model equations: y1 = intercept + geno Model Information: Term C/F F/R nLevels intercept factor fixed 1 MCMC Information: chain_length 40 burnin 10 starting_value true printout_frequency 41 output_samples_frequency 10 constraint on residual variance false constraint on marker effect variance for geno false missing_phenotypes true update_priors_frequency 0 seed 2026 Hyper-parameters Information: residual variances: 1.000 Genomic Information: complete genomic data (i.e., non-single-step analysis) Genomic Category geno Method BayesC genetic variances (genomic): 1.000 marker effect variances: 0.503 π 0.0 estimatePi true estimate_scale false Degree of freedom for hyper-parameters: residual variances: 4.000 marker effect variances: 4.000 The file dense_results/MCMC_samples_residual_variance.txt is created to save MCMC samples for residual_variance. The file dense_results/MCMC_samples_marker_effects_geno_y1.txt is created to save MCMC samples for marker_effects_geno_y1. The file dense_results/MCMC_samples_marker_effects_variances_geno.txt is created to save MCMC samples for marker_effects_variances_geno. The file dense_results/MCMC_samples_pi_geno.txt is created to save MCMC samples for pi_geno. running MCMC ... 5%|█▊ | ETA: 0:01:01 running MCMC ... 50%|█████████████████▌ | ETA: 0:00:07 running MCMC ... 75%|██████████████████████████▎ | ETA: 0:00:02 running MCMC ... 100%|███████████████████████████████████| Time: 0:00:06 The version of Julia and Platform in use: Julia Version 1.14.0-DEV.3055 Build Info: Commit 7e75a8061a* (2026-08-27 09:46 UTC) GC: Built with stock GC Platform Info: OS: Linux (x86_64-unknown-linux-gnu) CPU: 128 × AMD EPYC 7502 32-Core Processor (znver2) WORD_SIZE: 64 LLVM: libLLVM-22.1.8 (ORCJIT, znver2) Threads: 1 default, 0 interactive, 1 GC (on 1 virtual cores) Environment: JULIA_CPU_THREADS = 1 JULIA_NUM_PRECOMPILE_TASKS = 1 JULIA_PKG_PRECOMPILE_AUTO = 0 JULIA_PKGEVAL = true JULIA_DEPOT_PATH = /home/pkgeval/.julia:/usr/local/share/julia: JULIA_NUM_THREADS = 1 JULIA_LOAD_PATH = @:/tmp/jl_g0vHag The analysis has finished. Results are saved in the returned variable and text files. MCMC samples are saved in text files. Genotype informatin: #markers: 4; #individuals: 6 (storage=:stream) The folder stream_results is created to save results. Checking genotypes... Checking phenotypes... Individual IDs (strings) are provided in the first column of the phenotypic data. Predicted values for individuals of interest will be obtained as the summation of Any[] (Note that genomic data is always included for now).Phenotypes for 6 observations are used in the analysis.These individual IDs are saved in the file stream_results/IDs_for_individuals_with_phenotypes.txt. The prior for marker effects variance is calculated from the genetic variance and π. The mean of the prior for the marker effects variance is: 0.503496 storage=:stream is enabled; genotype alignment is skipped and original ID order is used. A Linear Mixed Model was build using model equations: y1 = intercept + geno Model Information: Term C/F F/R nLevels intercept factor fixed 1 MCMC Information: chain_length 40 burnin 10 starting_value true printout_frequency 41 output_samples_frequency 10 constraint on residual variance false constraint on marker effect variance for geno false missing_phenotypes true update_priors_frequency 0 seed 2026 Hyper-parameters Information: residual variances: 1.000 Genomic Information: complete genomic data (i.e., non-single-step analysis) Genomic Category geno Method BayesC genetic variances (genomic): 1.000 marker effect variances: 0.503 π 0.0 estimatePi true estimate_scale false Degree of freedom for hyper-parameters: residual variances: 4.000 marker effect variances: 4.000 The file stream_results/MCMC_samples_residual_variance.txt is created to save MCMC samples for residual_variance. The file stream_results/MCMC_samples_marker_effects_geno_y1.txt is created to save MCMC samples for marker_effects_geno_y1. The file stream_results/MCMC_samples_marker_effects_variances_geno.txt is created to save MCMC samples for marker_effects_variances_geno. The file stream_results/MCMC_samples_pi_geno.txt is created to save MCMC samples for pi_geno. running MCMC ... 5%|█▊ | ETA: 0:00:18 running MCMC ... 100%|███████████████████████████████████| Time: 0:00:00 The version of Julia and Platform in use: Julia Version 1.14.0-DEV.3055 Build Info: Commit 7e75a8061a* (2026-08-27 09:46 UTC) GC: Built with stock GC Platform Info: OS: Linux (x86_64-unknown-linux-gnu) CPU: 128 × AMD EPYC 7502 32-Core Processor (znver2) WORD_SIZE: 64 LLVM: libLLVM-22.1.8 (ORCJIT, znver2) Threads: 1 default, 0 interactive, 1 GC (on 1 virtual cores) Environment: JULIA_CPU_THREADS = 1 JULIA_NUM_PRECOMPILE_TASKS = 1 JULIA_PKG_PRECOMPILE_AUTO = 0 JULIA_PKGEVAL = true JULIA_DEPOT_PATH = /home/pkgeval/.julia:/usr/local/share/julia: JULIA_NUM_THREADS = 1 JULIA_LOAD_PATH = @:/tmp/jl_g0vHag The analysis has finished. Results are saved in the returned variable and text files. MCMC samples are saved in text files. Streaming genotype files are created with prefix /tmp/jl_iFZngD/geno_stream. Genotype informatin: #markers: 3; #individuals: 4 (storage=:stream) The folder stream_fast_blocks is created to save results. Genotype informatin: #markers: 3; #individuals: 4 (storage=:stream) The folder stream_weighted is created to save results. Checking genotypes... Checking phenotypes... Individual IDs (strings) are provided in the first column of the phenotypic data. Predicted values for individuals of interest will be obtained as the summation of Any[] (Note that genomic data is always included for now).Phenotypes for 4 observations are used in the analysis.These individual IDs are saved in the file stream_weighted/IDs_for_individuals_with_phenotypes.txt. The prior for marker effects variance is calculated from the genetic variance and π. The mean of the prior for the marker effects variance is: 0.680851 storage=:stream is enabled; genotype alignment is skipped and original ID order is used. Genotype informatin: #markers: 3; #individuals: 4 (storage=:stream) The folder stream_mt is created to save results. Genotype informatin: #markers: 3; #individuals: 4 (storage=:stream) The folder stream_double is created to save results. 0 loci which are fixed or have minor allele frequency < 0.01 are removed. Streaming genotype files are created with prefix /tmp/jl_gGUd0Q/geno_stream. The delimiter in geno.csv is ','. The header (marker IDs) is provided in geno.csv. Missing values (9.0) are replaced by column means. QC and decode parity vs dense: Error During Test at /home/pkgeval/.julia/packages/JWAS/AxFc6/test/unit/test_streaming_prepare_lowmem.jl:22 Got exception outside of a @test MethodError: no method matching reducedim1(::Matrix{Float32}, ::Matrix{Float32}) The function `reducedim1` exists, but no method is defined for this combination of argument types. Closest candidates are: reducedim1(::Any) @ Base reducedim.jl:1229 Stacktrace: [1] centralize_sumabs2!(R::Matrix{Float32}, A::Matrix{Float32}, means::Matrix{Float32}) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:282 [2] varm!(R::Matrix{Float32}, A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:309 [3] _varm(A::Matrix{Float32}, m::Matrix{Float32}, corrected::Bool, region::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:341 [4] varm(A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:339 [inlined] [5] _var(A::Matrix{Float32}, corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:386 [inlined] [6] var(A::Matrix{Float32}; corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:380 [inlined] [7] get_genotypes(file::String, G::Float64; method::String, Pi::Float64, estimatePi::Bool, G_is_marker_variance::Bool, df::Float64, estimate_variance::Bool, estimate_scale::Bool, constraint::Bool, separator::Char, header::Bool, double_precision::Bool, quality_control::Bool, MAF::Float64, missing_value::Float64, center::Bool, starting_value::Bool, annotations::Bool, multi_trait_sampler::Symbol, storage::Symbol) @ JWAS ~/.julia/packages/JWAS/AxFc6/src/1.JWAS/src/markers/readgenotypes.jl:390 [8] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_streaming_prepare_lowmem.jl:29 [inlined] [9] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [10] (::var"#33#34"{String})() @ Main ~/.julia/packages/JWAS/AxFc6/test/unit/test_streaming_prepare_lowmem.jl:23 Streaming genotype files are created with prefix /tmp/jl_gGUd0Q/geno_uncentered_stream. The argument center=true is ignored for storage=:stream. Backend metadata centered=false is used. Genotype informatin: #markers: 5; #individuals: 6 (storage=:stream) Streaming genotype files are created with prefix /tmp/jl_gGUd0Q/cleanup_true_stream. Streaming genotype files are created with prefix /tmp/jl_gGUd0Q/cleanup_false_stream. Auto conversion mode selected :dense (estimated dense bytes=120, auto_dense_max_bytes=10000). Streaming genotype files are created with prefix /tmp/jl_gGUd0Q/auto_dense_stream. Auto conversion mode selected :lowmem (estimated dense bytes=120, auto_dense_max_bytes=1). Streaming genotype files are created with prefix /tmp/jl_gGUd0Q/auto_lowmem_stream. Genotype informatin: #markers: 5; #individuals: 6 (storage=:stream) Genotype informatin: #markers: 5; #individuals: 6 (storage=:stream) The delimiter in genotypes.txt is ','. The header (marker IDs) is provided in genotypes.txt. The delimiter in genotypes.txt is ','. The header (marker IDs) is provided in genotypes.txt. The first column in the dataframe should be individual IDs. The remaining columns are markers with the data type Number. Missing values (9.0) are replaced by column means. filters annotations with QC and prepends intercept: Error During Test at /home/pkgeval/.julia/packages/JWAS/AxFc6/test/unit/test_annotated_bayesc.jl:92 Got exception outside of a @test MethodError: no method matching reducedim1(::Matrix{Float32}, ::Matrix{Float32}) The function `reducedim1` exists, but no method is defined for this combination of argument types. Closest candidates are: reducedim1(::Any) @ Base reducedim.jl:1229 Stacktrace: [1] centralize_sumabs2!(R::Matrix{Float32}, A::Matrix{Float32}, means::Matrix{Float32}) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:282 [2] varm!(R::Matrix{Float32}, A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:309 [3] _varm(A::Matrix{Float32}, m::Matrix{Float32}, corrected::Bool, region::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:341 [4] varm(A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:339 [inlined] [5] _var(A::Matrix{Float32}, corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:386 [inlined] [6] var(A::Matrix{Float32}; corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:380 [inlined] [7] get_genotypes(file::DataFrame, G::Float64; method::String, Pi::Float64, estimatePi::Bool, G_is_marker_variance::Bool, df::Float64, estimate_variance::Bool, estimate_scale::Bool, constraint::Bool, separator::Char, header::Bool, double_precision::Bool, quality_control::Bool, MAF::Float64, missing_value::Float64, center::Bool, starting_value::Bool, annotations::Matrix{Float64}, multi_trait_sampler::Symbol, storage::Symbol) @ JWAS ~/.julia/packages/JWAS/AxFc6/src/1.JWAS/src/markers/readgenotypes.jl:390 [8] top-level scope @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_annotated_bayesc.jl:34 [9] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [10] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_annotated_bayesc.jl:93 [inlined] [11] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [12] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_annotated_bayesc.jl:101 [inlined] The delimiter in genotypes.txt is ','. The header (marker IDs) is provided in genotypes.txt. Genotype informatin: #markers: 5; #individuals: 7 The delimiter in genotypes.txt is ','. The header (marker IDs) is provided in genotypes.txt. The delimiter in genotypes.txt is ','. The header (marker IDs) is provided in genotypes.txt. 1 loci which are fixed or have minor allele frequency < 0.01 are removed. Streaming genotype files are created with prefix /tmp/jl_51P8Io/annotated_stream_qc_stream. Genotype informatin: #markers: 2; #individuals: 4 (storage=:stream) 1 loci which are fixed or have minor allele frequency < 0.01 are removed. Streaming genotype files are created with prefix /tmp/jl_WkcFCb/annotated_stream_legacy_stream. The first column in the dataframe should be individual IDs. The remaining columns are markers with the data type Number. Genotype informatin: #markers: 20; #individuals: 2 The first column in the dataframe should be individual IDs. The remaining columns are markers with the data type Number. Genotype informatin: #markers: 20; #individuals: 2 The first column in the dataframe should be individual IDs. The remaining columns are markers with the data type Number. Genotype informatin: #markers: 20; #individuals: 2 The first column in the dataframe should be individual IDs. The remaining columns are markers with the data type Number. Genotype informatin: #markers: 20; #individuals: 2 The first column in the dataframe should be individual IDs. The remaining columns are markers with the data type Number. Genotype informatin: #markers: 1; #individuals: 2 The first column in the dataframe should be individual IDs. The remaining columns are markers with the data type Number. Genotype informatin: #markers: 1; #individuals: 3 The first column in the dataframe should be individual IDs. The remaining columns are markers with the data type Number. Genotype informatin: #markers: 1; #individuals: 2 The first column in the dataframe should be individual IDs. The remaining columns are markers with the data type Number. Genotype informatin: #markers: 3; #individuals: 3 The delimiter in genotypes.txt is ','. The header (marker IDs) is provided in genotypes.txt. Genotype informatin: #markers: 5; #individuals: 7 The delimiter in genotypes.txt is ','. The header (marker IDs) is provided in genotypes.txt. Genotype informatin: #markers: 5; #individuals: 7 The delimiter in genotypes.txt is ','. The header (marker IDs) is provided in genotypes.txt. Genotype informatin: #markers: 5; #individuals: 7 The delimiter in genotypes.txt is ','. The header (marker IDs) is provided in genotypes.txt. Genotype informatin: #markers: 5; #individuals: 7 The delimiter in genotypes.txt is ','. The header (marker IDs) is provided in genotypes.txt. Genotype informatin: #markers: 5; #individuals: 7 The delimiter in genotypes.txt is ','. The header (marker IDs) is provided in genotypes.txt. Genotype informatin: #markers: 5; #individuals: 7 The folder /tmp/jl_Qr6XMNGraB is created to save results. Checking genotypes... Checking phenotypes... Individual IDs (strings) are provided in the first column of the phenotypic data. In this complete genomic data (non-single-step) analyis, 1 phenotyped individuals are not genotyped. These are removed from the analysis. Predicted values for individuals of interest will be obtained as the summation of Any[] (Note that genomic data is always included for now).Phenotypes for 4 observations are used in the analysis.These individual IDs are saved in the file /tmp/jl_Qr6XMNGraB/IDs_for_individuals_with_phenotypes.txt. The prior for marker effects variance is calculated from the genetic variance and π. The mean of the prior for the marker effects variance is: 0.492462 A Linear Mixed Model was build using model equations: y1 = intercept + annotated_singletrait_sampler_auto Model Information: Term C/F F/R nLevels intercept factor fixed 1 The file /tmp/jl_Qr6XMNGraB/MCMC_samples_residual_variance.txt is created to save MCMC samples for residual_variance. The file /tmp/jl_Qr6XMNGraB/MCMC_samples_marker_effects_annotated_singletrait_sampler_auto_y1.txt is created to save MCMC samples for marker_effects_annotated_singletrait_sampler_auto_y1. The file /tmp/jl_Qr6XMNGraB/MCMC_samples_marker_effects_variances_annotated_singletrait_sampler_auto.txt is created to save MCMC samples for marker_effects_variances_annotated_singletrait_sampler_auto. The file /tmp/jl_Qr6XMNGraB/MCMC_samples_pi_annotated_singletrait_sampler_auto.txt is created to save MCMC samples for pi_annotated_singletrait_sampler_auto. running MCMC ... 20%|███████ | ETA: 0:00:01 running MCMC ... 100%|███████████████████████████████████| Time: 0:00:00 The version of Julia and Platform in use: Julia Version 1.14.0-DEV.3055 Build Info: Commit 7e75a8061a* (2026-08-27 09:46 UTC) GC: Built with stock GC Platform Info: OS: Linux (x86_64-unknown-linux-gnu) CPU: 128 × AMD EPYC 7502 32-Core Processor (znver2) WORD_SIZE: 64 LLVM: libLLVM-22.1.8 (ORCJIT, znver2) Threads: 1 default, 0 interactive, 1 GC (on 1 virtual cores) Environment: JULIA_CPU_THREADS = 1 JULIA_NUM_PRECOMPILE_TASKS = 1 JULIA_PKG_PRECOMPILE_AUTO = 0 JULIA_PKGEVAL = true JULIA_DEPOT_PATH = /home/pkgeval/.julia:/usr/local/share/julia: JULIA_NUM_THREADS = 1 JULIA_LOAD_PATH = @:/tmp/jl_g0vHag The analysis has finished. Results are saved in the returned variable and text files. MCMC samples are saved in text files. The delimiter in genotypes.txt is ','. The header (marker IDs) is provided in genotypes.txt. Genotype informatin: #markers: 5; #individuals: 7 The delimiter in genotypes.txt is ','. The header (marker IDs) is provided in genotypes.txt. Genotype informatin: #markers: 5; #individuals: 7 The delimiter in genotypes.txt is ','. The header (marker IDs) is provided in genotypes.txt. Genotype informatin: #markers: 5; #individuals: 7 The delimiter in genotypes.txt is ','. The header (marker IDs) is provided in genotypes.txt. Genotype informatin: #markers: 5; #individuals: 7 The delimiter in genotypes.txt is ','. The header (marker IDs) is provided in genotypes.txt. Genotype informatin: #markers: 5; #individuals: 7 The folder /tmp/jl_43ezkdY5y9 is created to save results. The delimiter in genotypes.txt is ','. The header (marker IDs) is provided in genotypes.txt. Genotype informatin: #markers: 5; #individuals: 7 The folder test_mt_annotated_bayesc_fastblocks is created to save results. Checking genotypes... Checking phenotypes... Individual IDs (strings) are provided in the first column of the phenotypic data. In this complete genomic data (non-single-step) analyis, 1 phenotyped individuals are not genotyped. These are removed from the analysis. Predicted values for individuals of interest will be obtained as the summation of Any[] (Note that genomic data is always included for now).Phenotypes for 7 observations are used in the analysis.These individual IDs are saved in the file test_mt_annotated_bayesc_fastblocks/IDs_for_individuals_with_phenotypes.txt. The prior for marker effects covariance matrix is calculated from genetic covariance matrix and Π. The mean of the prior for the marker effects covariance matrix is: BLOCK SIZE: 2 A Linear Mixed Model was build using model equations: y1 = intercept + annotated_mt_fastblocks y2 = intercept + annotated_mt_fastblocks Model Information: Term C/F F/R nLevels intercept factor fixed 1 The file test_mt_annotated_bayesc_fastblocks/MCMC_samples_residual_variance.txt is created to save MCMC samples for residual_variance. The file test_mt_annotated_bayesc_fastblocks/MCMC_samples_marker_effects_annotated_mt_fastblocks_y1.txt is created to save MCMC samples for marker_effects_annotated_mt_fastblocks_y1. The file test_mt_annotated_bayesc_fastblocks/MCMC_samples_marker_effects_annotated_mt_fastblocks_y2.txt is created to save MCMC samples for marker_effects_annotated_mt_fastblocks_y2. The file test_mt_annotated_bayesc_fastblocks/MCMC_samples_marker_effects_variances_annotated_mt_fastblocks.txt is created to save MCMC samples for marker_effects_variances_annotated_mt_fastblocks. The file test_mt_annotated_bayesc_fastblocks/MCMC_samples_pi_annotated_mt_fastblocks.txt is created to save MCMC samples for pi_annotated_mt_fastblocks. running MCMC ... 40%|██████████████ | ETA: 0:00:50 running MCMC ... 100%|███████████████████████████████████| Time: 0:00:36 The version of Julia and Platform in use: Julia Version 1.14.0-DEV.3055 Build Info: Commit 7e75a8061a* (2026-08-27 09:46 UTC) GC: Built with stock GC Platform Info: OS: Linux (x86_64-unknown-linux-gnu) CPU: 128 × AMD EPYC 7502 32-Core Processor (znver2) WORD_SIZE: 64 LLVM: libLLVM-22.1.8 (ORCJIT, znver2) Threads: 1 default, 0 interactive, 1 GC (on 1 virtual cores) Environment: JULIA_CPU_THREADS = 1 JULIA_NUM_PRECOMPILE_TASKS = 1 JULIA_PKG_PRECOMPILE_AUTO = 0 JULIA_PKGEVAL = true JULIA_DEPOT_PATH = /home/pkgeval/.julia:/usr/local/share/julia: JULIA_NUM_THREADS = 1 JULIA_LOAD_PATH = @:/tmp/jl_g0vHag The analysis has finished. Results are saved in the returned variable and text files. MCMC samples are saved in text files. Streaming genotype files are created with prefix /tmp/jl_XdcTF7/annotated_mt_stream_stream. Genotype informatin: #markers: 5; #individuals: 4 (storage=:stream) The folder /tmp/jl_WjKTqPYZk7 is created to save results. The delimiter in genotypes.txt is ','. The header (marker IDs) is provided in genotypes.txt. Genotype informatin: #markers: 5; #individuals: 7 The folder results is created to save results. Checking genotypes... Checking phenotypes... Individual IDs (strings) are provided in the first column of the phenotypic data. In this complete genomic data (non-single-step) analyis, 1 phenotyped individuals are not genotyped. These are removed from the analysis. Predicted values for individuals of interest will be obtained as the summation of Any[] (Note that genomic data is always included for now).Phenotypes for 4 observations are used in the analysis.These individual IDs are saved in the file results/IDs_for_individuals_with_phenotypes.txt. The prior for marker effects variance is calculated from the genetic variance and π. The mean of the prior for the marker effects variance is: 0.492462 A Linear Mixed Model was build using model equations: y1 = intercept + plain_geno Model Information: Term C/F F/R nLevels intercept factor fixed 1 MCMC Information: chain_length 12 burnin 2 starting_value true printout_frequency 99 output_samples_frequency 1 constraint on residual variance false constraint on marker effect variance for plain_geno false missing_phenotypes true update_priors_frequency 0 seed 2026 Hyper-parameters Information: residual variances: 1.000 Genomic Information: complete genomic data (i.e., non-single-step analysis) Genomic Category plain_geno Method BayesC genetic variances (genomic): 1.000 marker effect variances: 0.492 π 0.0 estimatePi true estimate_scale false Degree of freedom for hyper-parameters: residual variances: 4.000 marker effect variances: 4.000 The file results/MCMC_samples_residual_variance.txt is created to save MCMC samples for residual_variance. The file results/MCMC_samples_marker_effects_plain_geno_y1.txt is created to save MCMC samples for marker_effects_plain_geno_y1. The file results/MCMC_samples_marker_effects_variances_plain_geno.txt is created to save MCMC samples for marker_effects_variances_plain_geno. The file results/MCMC_samples_pi_plain_geno.txt is created to save MCMC samples for pi_plain_geno. The version of Julia and Platform in use: Julia Version 1.14.0-DEV.3055 Build Info: Commit 7e75a8061a* (2026-08-27 09:46 UTC) GC: Built with stock GC Platform Info: OS: Linux (x86_64-unknown-linux-gnu) CPU: 128 × AMD EPYC 7502 32-Core Processor (znver2) WORD_SIZE: 64 LLVM: libLLVM-22.1.8 (ORCJIT, znver2) Threads: 1 default, 0 interactive, 1 GC (on 1 virtual cores) Environment: JULIA_CPU_THREADS = 1 JULIA_NUM_PRECOMPILE_TASKS = 1 JULIA_PKG_PRECOMPILE_AUTO = 0 JULIA_PKGEVAL = true JULIA_DEPOT_PATH = /home/pkgeval/.julia:/usr/local/share/julia: JULIA_NUM_THREADS = 1 JULIA_LOAD_PATH = @:/tmp/jl_g0vHag The analysis has finished. Results are saved in the returned variable and text files. MCMC samples are saved in text files. The delimiter in genotypes.txt is ','. The header (marker IDs) is provided in genotypes.txt. Genotype informatin: #markers: 5; #individuals: 7 The folder results is created to save results. Checking genotypes... Checking phenotypes... Individual IDs (strings) are provided in the first column of the phenotypic data. In this complete genomic data (non-single-step) analyis, 1 phenotyped individuals are not genotyped. These are removed from the analysis. Predicted values for individuals of interest will be obtained as the summation of Any[] (Note that genomic data is always included for now).Phenotypes for 4 observations are used in the analysis.These individual IDs are saved in the file results/IDs_for_individuals_with_phenotypes.txt. The prior for marker effects variance is calculated from the genetic variance and π. The mean of the prior for the marker effects variance is: 0.492462 A Linear Mixed Model was build using model equations: y1 = intercept + annotated_geno Model Information: Term C/F F/R nLevels intercept factor fixed 1 MCMC Information: chain_length 30 burnin 10 starting_value true printout_frequency 31 output_samples_frequency 10 constraint on residual variance false constraint on marker effect variance for annotated_geno false missing_phenotypes true update_priors_frequency 0 seed 2026 Hyper-parameters Information: residual variances: 1.000 Genomic Information: complete genomic data (i.e., non-single-step analysis) Genomic Category annotated_geno Method BayesC genetic variances (genomic): 1.000 marker effect variances: 0.492 π_j (min/mean/max) 0.000 / 0.000 / 0.000 estimatePi true estimate_scale false Degree of freedom for hyper-parameters: residual variances: 4.000 marker effect variances: 4.000 The file results/MCMC_samples_residual_variance.txt is created to save MCMC samples for residual_variance. The file results/MCMC_samples_marker_effects_annotated_geno_y1.txt is created to save MCMC samples for marker_effects_annotated_geno_y1. The file results/MCMC_samples_marker_effects_variances_annotated_geno.txt is created to save MCMC samples for marker_effects_variances_annotated_geno. The file results/MCMC_samples_pi_annotated_geno.txt is created to save MCMC samples for pi_annotated_geno. The file results/MCMC_samples_EBV_y1.txt is created to save MCMC samples for EBV_y1. The file results/MCMC_samples_genetic_variance.txt is created to save MCMC samples for genetic_variance. The file results/MCMC_samples_heritability.txt is created to save MCMC samples for heritability. Annotated BayesC dense run: Error During Test at /home/pkgeval/.julia/packages/JWAS/AxFc6/test/unit/test_annotated_bayesc.jl:964 Got exception outside of a @test MethodError: no method matching reducedim1(::Matrix{Float64}, ::Matrix{Float64}) The function `reducedim1` exists, but no method is defined for this combination of argument types. Closest candidates are: reducedim1(::Any) @ Base reducedim.jl:1229 Stacktrace: [1] centralize_sumabs2!(R::Matrix{Float64}, A::Matrix{Float64}, means::Matrix{Float64}) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:282 [2] varm!(R::Matrix{Float64}, A::Matrix{Float64}, m::Matrix{Float64}; corrected::Bool) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:309 [3] _varm(A::Matrix{Float64}, m::Matrix{Float64}, corrected::Bool, region::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:341 [4] varm(A::Matrix{Float64}, m::Matrix{Float64}; corrected::Bool, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:339 [inlined] [5] _var(A::Matrix{Float64}, corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:386 [inlined] [6] var(A::Matrix{Float64}; corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:380 [inlined] [7] output_result(mme::JWAS.MME, output_folder::String, solMean::Vector{Float64}, meanVare::Float64, G0Mean::Bool, solMean2::Vector{Float64}, meanVare2::Float64, G0Mean2::Bool) @ JWAS ~/.julia/packages/JWAS/AxFc6/src/1.JWAS/src/output.jl:199 [8] MCMC_BayesianAlphabet(mme::JWAS.MME, df::DataFrame) @ JWAS ~/.julia/packages/JWAS/AxFc6/src/1.JWAS/src/MCMC/MCMC_BayesianAlphabet.jl:446 [9] runMCMC(mme::JWAS.MME, df::DataFrame; heterogeneous_residuals::Bool, chain_length::Int64, starting_value::Bool, burnin::Int64, output_samples_frequency::Int64, update_priors_frequency::Int64, single_step_analysis::Bool, pedigree::Bool, fitting_J_vector::Bool, causal_structure::Bool, missing_phenotypes::Bool, RRM::Bool, outputEBV::Bool, output_heritability::Bool, prediction_equation::Bool, seed::Int64, printout_model_info::Bool, printout_frequency::Int64, big_memory::Bool, double_precision::Bool, fast_blocks::Bool, independent_blocks::Bool, memory_guard::Symbol, memory_guard_ratio::Float64, output_folder::String, output_samples_for_all_parameters::Bool, methods::String, Pi::Float64, estimatePi::Bool, estimate_scale::Bool, estimate_variance::Bool, categorical_trait::Bool, censored_trait::Bool) @ JWAS ~/.julia/packages/JWAS/AxFc6/src/1.JWAS/src/JWAS.jl:466 [10] (::var"#84#85"{Matrix{Float64}, DataFrame, String})() @ Main ~/.julia/packages/JWAS/AxFc6/test/unit/test_annotated_bayesc.jl:986 [11] cd(f::var"#84#85"{Matrix{Float64}, DataFrame, String}, dir::String) @ Base.Filesystem file.jl:113 [12] (::var"#82#83"{Matrix{Float64}, DataFrame, String})(tmpdir::String) @ Main ~/.julia/packages/JWAS/AxFc6/test/unit/test_annotated_bayesc.jl:977 [inlined] [13] mktempdir(fn::var"#82#83"{Matrix{Float64}, DataFrame, String}, parent::String; prefix::String) @ Base.Filesystem file.jl:949 [14] mktempdir(fn::Function, parent::String) @ Base.Filesystem file.jl:945 [15] top-level scope @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_annotated_bayesc.jl:965 [16] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [17] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_annotated_bayesc.jl:976 [inlined] The delimiter in genotypes.txt is ','. The header (marker IDs) is provided in genotypes.txt. Genotype informatin: #markers: 5; #individuals: 7 The folder results is created to save results. Checking genotypes... Checking phenotypes... Individual IDs (strings) are provided in the first column of the phenotypic data. In this complete genomic data (non-single-step) analyis, 1 phenotyped individuals are not genotyped. These are removed from the analysis. Predicted values for individuals of interest will be obtained as the summation of Any[] (Note that genomic data is always included for now).Phenotypes for 4 observations are used in the analysis.These individual IDs are saved in the file results/IDs_for_individuals_with_phenotypes.txt. The prior for marker effects variance is calculated from the genetic variance and π. The mean of the prior for the marker effects variance is: 0.492462 BLOCK SIZE: 2 A Linear Mixed Model was build using model equations: y1 = intercept + annotated_blocks Model Information: Term C/F F/R nLevels intercept factor fixed 1 MCMC Information: chain_length 15 burnin 10 starting_value true printout_frequency 31 output_samples_frequency 10 constraint on residual variance false constraint on marker effect variance for annotated_blocks false missing_phenotypes true update_priors_frequency 0 seed 2026 Hyper-parameters Information: residual variances: 1.000 Genomic Information: complete genomic data (i.e., non-single-step analysis) Genomic Category annotated_blocks Method BayesC genetic variances (genomic): 1.000 marker effect variances: 0.492 π_j (min/mean/max) 0.000 / 0.000 / 0.000 estimatePi true estimate_scale false Degree of freedom for hyper-parameters: residual variances: 4.000 marker effect variances: 4.000 The file results/MCMC_samples_residual_variance.txt is created to save MCMC samples for residual_variance. The file results/MCMC_samples_marker_effects_annotated_blocks_y1.txt is created to save MCMC samples for marker_effects_annotated_blocks_y1. The file results/MCMC_samples_marker_effects_variances_annotated_blocks.txt is created to save MCMC samples for marker_effects_variances_annotated_blocks. The file results/MCMC_samples_pi_annotated_blocks.txt is created to save MCMC samples for pi_annotated_blocks. The file results/MCMC_samples_EBV_y1.txt is created to save MCMC samples for EBV_y1. The file results/MCMC_samples_genetic_variance.txt is created to save MCMC samples for genetic_variance. The file results/MCMC_samples_heritability.txt is created to save MCMC samples for heritability. running MCMC ... 13%|████▋ | ETA: 0:00:35 running MCMC ... 100%|███████████████████████████████████| Time: 0:00:05 The version of Julia and Platform in use: Julia Version 1.14.0-DEV.3055 Build Info: Commit 7e75a8061a* (2026-08-27 09:46 UTC) GC: Built with stock GC Platform Info: OS: Linux (x86_64-unknown-linux-gnu) CPU: 128 × AMD EPYC 7502 32-Core Processor (znver2) WORD_SIZE: 64 LLVM: libLLVM-22.1.8 (ORCJIT, znver2) Threads: 1 default, 0 interactive, 1 GC (on 1 virtual cores) Environment: JULIA_CPU_THREADS = 1 JULIA_NUM_PRECOMPILE_TASKS = 1 JULIA_PKG_PRECOMPILE_AUTO = 0 JULIA_PKGEVAL = true JULIA_DEPOT_PATH = /home/pkgeval/.julia:/usr/local/share/julia: JULIA_NUM_THREADS = 1 JULIA_LOAD_PATH = @:/tmp/jl_g0vHag The analysis has finished. Results are saved in the returned variable and text files. MCMC samples are saved in text files. The delimiter in genotypes.txt is ','. The header (marker IDs) is provided in genotypes.txt. Genotype informatin: #markers: 5; #individuals: 7 The folder results is created to save results. Checking genotypes... Checking phenotypes... Individual IDs (strings) are provided in the first column of the phenotypic data. In this complete genomic data (non-single-step) analyis, 1 phenotyped individuals are not genotyped. These are removed from the analysis. Predicted values for individuals of interest will be obtained as the summation of Any[] (Note that genomic data is always included for now).Phenotypes for 4 observations are used in the analysis.These individual IDs are saved in the file results/IDs_for_individuals_with_phenotypes.txt. The prior for marker effects variance is calculated from the genetic variance and π. The mean of the prior for the marker effects variance is: 0.492462 BLOCK STARTS: [1, 3, 5] A Linear Mixed Model was build using model equations: y1 = intercept + annotated_blocks_independent Model Information: Term C/F F/R nLevels intercept factor fixed 1 MCMC Information: chain_length 12 burnin 2 starting_value true printout_frequency 13 output_samples_frequency 10 constraint on residual variance false constraint on marker effect variance for annotated_blocks_independent false missing_phenotypes true update_priors_frequency 0 seed 2026 Hyper-parameters Information: residual variances: 1.000 Genomic Information: complete genomic data (i.e., non-single-step analysis) Genomic Category annotated_blocks_independent Method BayesC genetic variances (genomic): 1.000 marker effect variances: 0.492 π_j (min/mean/max) 0.000 / 0.000 / 0.000 estimatePi true estimate_scale false Degree of freedom for hyper-parameters: residual variances: 4.000 marker effect variances: 4.000 The file results/MCMC_samples_residual_variance.txt is created to save MCMC samples for residual_variance. The file results/MCMC_samples_marker_effects_annotated_blocks_independent_y1.txt is created to save MCMC samples for marker_effects_annotated_blocks_independent_y1. The file results/MCMC_samples_marker_effects_variances_annotated_blocks_independent.txt is created to save MCMC samples for marker_effects_variances_annotated_blocks_independent. The file results/MCMC_samples_pi_annotated_blocks_independent.txt is created to save MCMC samples for pi_annotated_blocks_independent. running MCMC ... 17%|█████▉ | ETA: 0:00:08 running MCMC ... 100%|███████████████████████████████████| Time: 0:00:01 The version of Julia and Platform in use: Julia Version 1.14.0-DEV.3055 Build Info: Commit 7e75a8061a* (2026-08-27 09:46 UTC) GC: Built with stock GC Platform Info: OS: Linux (x86_64-unknown-linux-gnu) CPU: 128 × AMD EPYC 7502 32-Core Processor (znver2) WORD_SIZE: 64 LLVM: libLLVM-22.1.8 (ORCJIT, znver2) Threads: 1 default, 0 interactive, 1 GC (on 1 virtual cores) Environment: JULIA_CPU_THREADS = 1 JULIA_NUM_PRECOMPILE_TASKS = 1 JULIA_PKG_PRECOMPILE_AUTO = 0 JULIA_PKGEVAL = true JULIA_DEPOT_PATH = /home/pkgeval/.julia:/usr/local/share/julia: JULIA_NUM_THREADS = 1 JULIA_LOAD_PATH = @:/tmp/jl_g0vHag The analysis has finished. Results are saved in the returned variable and text files. MCMC samples are saved in text files. Streaming genotype files are created with prefix /tmp/jl_3nN6sN/annotated_stream_stream. Genotype informatin: #markers: 5; #individuals: 6 (storage=:stream) The folder results is created to save results. Checking genotypes... Checking phenotypes... Individual IDs (strings) are provided in the first column of the phenotypic data. Predicted values for individuals of interest will be obtained as the summation of Any[] (Note that genomic data is always included for now).Phenotypes for 6 observations are used in the analysis.These individual IDs are saved in the file results/IDs_for_individuals_with_phenotypes.txt. The prior for marker effects variance is calculated from the genetic variance and π. The mean of the prior for the marker effects variance is: 0.402235 storage=:stream is enabled; genotype alignment is skipped and original ID order is used. A Linear Mixed Model was build using model equations: y1 = intercept + annotated_stream Model Information: Term C/F F/R nLevels intercept factor fixed 1 MCMC Information: chain_length 30 burnin 10 starting_value true printout_frequency 31 output_samples_frequency 10 constraint on residual variance false constraint on marker effect variance for annotated_stream false missing_phenotypes true update_priors_frequency 0 seed 2026 Hyper-parameters Information: residual variances: 1.000 Genomic Information: complete genomic data (i.e., non-single-step analysis) Genomic Category annotated_stream Method BayesC genetic variances (genomic): 1.000 marker effect variances: 0.402 π_j (min/mean/max) 0.000 / 0.000 / 0.000 estimatePi true estimate_scale false Degree of freedom for hyper-parameters: residual variances: 4.000 marker effect variances: 4.000 The file results/MCMC_samples_residual_variance.txt is created to save MCMC samples for residual_variance. The file results/MCMC_samples_marker_effects_annotated_stream_y1.txt is created to save MCMC samples for marker_effects_annotated_stream_y1. The file results/MCMC_samples_marker_effects_variances_annotated_stream.txt is created to save MCMC samples for marker_effects_variances_annotated_stream. The file results/MCMC_samples_pi_annotated_stream.txt is created to save MCMC samples for pi_annotated_stream. The version of Julia and Platform in use: Julia Version 1.14.0-DEV.3055 Build Info: Commit 7e75a8061a* (2026-08-27 09:46 UTC) GC: Built with stock GC Platform Info: OS: Linux (x86_64-unknown-linux-gnu) CPU: 128 × AMD EPYC 7502 32-Core Processor (znver2) WORD_SIZE: 64 LLVM: libLLVM-22.1.8 (ORCJIT, znver2) Threads: 1 default, 0 interactive, 1 GC (on 1 virtual cores) Environment: JULIA_CPU_THREADS = 1 JULIA_NUM_PRECOMPILE_TASKS = 1 JULIA_PKG_PRECOMPILE_AUTO = 0 JULIA_PKGEVAL = true JULIA_DEPOT_PATH = /home/pkgeval/.julia:/usr/local/share/julia: JULIA_NUM_THREADS = 1 JULIA_LOAD_PATH = @:/tmp/jl_g0vHag The analysis has finished. Results are saved in the returned variable and text files. MCMC samples are saved in text files. The delimiter in genotypes.txt is ','. The header (marker IDs) is provided in genotypes.txt. Genotype informatin: #markers: 5; #individuals: 7 Streaming genotype files are created with prefix /tmp/jl_KCkEBk/annotated_bayesr_stream_stream. Streaming genotype files are created with prefix /tmp/jl_GWoAcM/annotated_bayesr_mt_stream_stream. The delimiter in genotypes.txt is ','. The header (marker IDs) is provided in genotypes.txt. Genotype informatin: #markers: 5; #individuals: 7 The folder /tmp/jl_2l2JmZQLg9 is created to save results. The delimiter in genotypes.txt is ','. The header (marker IDs) is provided in genotypes.txt. Genotype informatin: #markers: 5; #individuals: 7 The folder /tmp/jl_cbsdqvYJqv is created to save results. The delimiter in genotypes.txt is ','. The header (marker IDs) is provided in genotypes.txt. Genotype informatin: #markers: 5; #individuals: 7 The delimiter in genotypes.txt is ','. The header (marker IDs) is provided in genotypes.txt. Genotype informatin: #markers: 5; #individuals: 7 The folder /tmp/jl_OzwNWv6Vq5 is created to save results. The delimiter in genotypes.txt is ','. The header (marker IDs) is provided in genotypes.txt. Genotype informatin: #markers: 5; #individuals: 7 The delimiter in genotypes.txt is ','. The header (marker IDs) is provided in genotypes.txt. Genotype informatin: #markers: 5; #individuals: 7 The delimiter in genotypes.txt is ','. The header (marker IDs) is provided in genotypes.txt. The delimiter in genotypes.txt is ','. The header (marker IDs) is provided in genotypes.txt. The delimiter in genotypes.txt is ','. The header (marker IDs) is provided in genotypes.txt. Genotype informatin: #markers: 5; #individuals: 7 The delimiter in genotypes.txt is ','. The header (marker IDs) is provided in genotypes.txt. Genotype informatin: #markers: 5; #individuals: 7 The delimiter in genotypes.txt is ','. The header (marker IDs) is provided in genotypes.txt. Genotype informatin: #markers: 5; #individuals: 7 The delimiter in genotypes.txt is ','. The header (marker IDs) is provided in genotypes.txt. Genotype informatin: #markers: 5; #individuals: 7 The delimiter in genotypes.txt is ','. The header (marker IDs) is provided in genotypes.txt. Genotype informatin: #markers: 5; #individuals: 7 The folder results is created to save results. Checking genotypes... Checking phenotypes... Individual IDs (strings) are provided in the first column of the phenotypic data. In this complete genomic data (non-single-step) analyis, 1 phenotyped individuals are not genotyped. These are removed from the analysis. Predicted values for individuals of interest will be obtained as the summation of Any[] (Note that genomic data is always included for now).Phenotypes for 4 observations are used in the analysis.These individual IDs are saved in the file results/IDs_for_individuals_with_phenotypes.txt. The prior for the BayesR shared marker variance is calculated from the genetic variance and π. The mean of the prior for the shared marker variance is: 72.420929 A Linear Mixed Model was build using model equations: y1 = intercept + annotated_bayesr_dense Model Information: Term C/F F/R nLevels intercept factor fixed 1 MCMC Information: chain_length 30 burnin 10 starting_value true printout_frequency 31 output_samples_frequency 10 constraint on residual variance false constraint on marker effect variance for annotated_bayesr_dense false missing_phenotypes true update_priors_frequency 0 seed 2026 Hyper-parameters Information: residual variances: 1.000 Genomic Information: complete genomic data (i.e., non-single-step analysis) Genomic Category annotated_bayesr_dense Method BayesR genetic variances (genomic): 1.000 marker effect variances: 72.421 π_j (min/mean/max) 0.005 / 0.250 / 0.950 estimatePi true estimate_scale false Degree of freedom for hyper-parameters: residual variances: 4.000 marker effect variances: 4.000 BayesR gamma: [0.0, 0.01, 0.1, 1.0] BayesR starting pi: [0.95, 0.03, 0.015, 0.005] BayesR expected class counts: [4.75, 0.15, 0.08, 0.02] The file results/MCMC_samples_residual_variance.txt is created to save MCMC samples for residual_variance. The file results/MCMC_samples_marker_effects_annotated_bayesr_dense_y1.txt is created to save MCMC samples for marker_effects_annotated_bayesr_dense_y1. The file results/MCMC_samples_marker_effects_variances_annotated_bayesr_dense.txt is created to save MCMC samples for marker_effects_variances_annotated_bayesr_dense. The file results/MCMC_samples_pi_annotated_bayesr_dense.txt is created to save MCMC samples for pi_annotated_bayesr_dense. running MCMC ... 7%|██▍ | ETA: 0:00:12 running MCMC ... 100%|███████████████████████████████████| Time: 0:00:01 The version of Julia and Platform in use: Julia Version 1.14.0-DEV.3055 Build Info: Commit 7e75a8061a* (2026-08-27 09:46 UTC) GC: Built with stock GC Platform Info: OS: Linux (x86_64-unknown-linux-gnu) CPU: 128 × AMD EPYC 7502 32-Core Processor (znver2) WORD_SIZE: 64 LLVM: libLLVM-22.1.8 (ORCJIT, znver2) Threads: 1 default, 0 interactive, 1 GC (on 1 virtual cores) Environment: JULIA_CPU_THREADS = 1 JULIA_NUM_PRECOMPILE_TASKS = 1 JULIA_PKG_PRECOMPILE_AUTO = 0 JULIA_PKGEVAL = true JULIA_DEPOT_PATH = /home/pkgeval/.julia:/usr/local/share/julia: JULIA_NUM_THREADS = 1 JULIA_LOAD_PATH = @:/tmp/jl_g0vHag The analysis has finished. Results are saved in the returned variable and text files. MCMC samples are saved in text files. The delimiter in genotypes.txt is ','. The header (marker IDs) is provided in genotypes.txt. Genotype informatin: #markers: 5; #individuals: 7 The folder results is created to save results. Checking genotypes... Checking phenotypes... Individual IDs (strings) are provided in the first column of the phenotypic data. In this complete genomic data (non-single-step) analyis, 1 phenotyped individuals are not genotyped. These are removed from the analysis. Predicted values for individuals of interest will be obtained as the summation of Any[] (Note that genomic data is always included for now).Phenotypes for 4 observations are used in the analysis.These individual IDs are saved in the file results/IDs_for_individuals_with_phenotypes.txt. The prior for the BayesR shared marker variance is calculated from the genetic variance and π. The mean of the prior for the shared marker variance is: 72.420929 BLOCK SIZE: 2 A Linear Mixed Model was build using model equations: y1 = intercept + annotated_bayesr_fast Model Information: Term C/F F/R nLevels intercept factor fixed 1 MCMC Information: chain_length 15 burnin 10 starting_value true printout_frequency 31 output_samples_frequency 10 constraint on residual variance false constraint on marker effect variance for annotated_bayesr_fast false missing_phenotypes true update_priors_frequency 0 seed 2026 Hyper-parameters Information: residual variances: 1.000 Genomic Information: complete genomic data (i.e., non-single-step analysis) Genomic Category annotated_bayesr_fast Method BayesR genetic variances (genomic): 1.000 marker effect variances: 72.421 π_j (min/mean/max) 0.005 / 0.250 / 0.950 estimatePi true estimate_scale false Degree of freedom for hyper-parameters: residual variances: 4.000 marker effect variances: 4.000 BayesR gamma: [0.0, 0.01, 0.1, 1.0] BayesR starting pi: [0.95, 0.03, 0.015, 0.005] BayesR expected class counts: [4.75, 0.15, 0.08, 0.02] The file results/MCMC_samples_residual_variance.txt is created to save MCMC samples for residual_variance. The file results/MCMC_samples_marker_effects_annotated_bayesr_fast_y1.txt is created to save MCMC samples for marker_effects_annotated_bayesr_fast_y1. The file results/MCMC_samples_marker_effects_variances_annotated_bayesr_fast.txt is created to save MCMC samples for marker_effects_variances_annotated_bayesr_fast. The file results/MCMC_samples_pi_annotated_bayesr_fast.txt is created to save MCMC samples for pi_annotated_bayesr_fast. running MCMC ... 13%|████▋ | ETA: 0:00:21 running MCMC ... 100%|███████████████████████████████████| Time: 0:00:03 The version of Julia and Platform in use: Julia Version 1.14.0-DEV.3055 Build Info: Commit 7e75a8061a* (2026-08-27 09:46 UTC) GC: Built with stock GC Platform Info: OS: Linux (x86_64-unknown-linux-gnu) CPU: 128 × AMD EPYC 7502 32-Core Processor (znver2) WORD_SIZE: 64 LLVM: libLLVM-22.1.8 (ORCJIT, znver2) Threads: 1 default, 0 interactive, 1 GC (on 1 virtual cores) Environment: JULIA_CPU_THREADS = 1 JULIA_NUM_PRECOMPILE_TASKS = 1 JULIA_PKG_PRECOMPILE_AUTO = 0 JULIA_PKGEVAL = true JULIA_DEPOT_PATH = /home/pkgeval/.julia:/usr/local/share/julia: JULIA_NUM_THREADS = 1 JULIA_LOAD_PATH = @:/tmp/jl_g0vHag The analysis has finished. Results are saved in the returned variable and text files. MCMC samples are saved in text files. The delimiter in genotypes.txt is ','. The header (marker IDs) is provided in genotypes.txt. Genotype informatin: #markers: 5; #individuals: 7 The folder results is created to save results. Checking genotypes... Checking phenotypes... Individual IDs (strings) are provided in the first column of the phenotypic data. In this complete genomic data (non-single-step) analyis, 1 phenotyped individuals are not genotyped. These are removed from the analysis. Predicted values for individuals of interest will be obtained as the summation of Any[] (Note that genomic data is always included for now).Phenotypes for 4 observations are used in the analysis.These individual IDs are saved in the file results/IDs_for_individuals_with_phenotypes.txt. The prior for the BayesR shared marker variance is calculated from the genetic variance and π. The mean of the prior for the shared marker variance is: 72.420929 BLOCK STARTS: [1, 3, 5] A Linear Mixed Model was build using model equations: y1 = intercept + annotated_bayesr_fast_independent Model Information: Term C/F F/R nLevels intercept factor fixed 1 MCMC Information: chain_length 12 burnin 2 starting_value true printout_frequency 13 output_samples_frequency 10 constraint on residual variance false constraint on marker effect variance for annotated_bayesr_fast_independent false missing_phenotypes true update_priors_frequency 0 seed 2026 Hyper-parameters Information: residual variances: 1.000 Genomic Information: complete genomic data (i.e., non-single-step analysis) Genomic Category annotated_bayesr_fast_independent Method BayesR genetic variances (genomic): 1.000 marker effect variances: 72.421 π_j (min/mean/max) 0.005 / 0.250 / 0.950 estimatePi true estimate_scale false Degree of freedom for hyper-parameters: residual variances: 4.000 marker effect variances: 4.000 BayesR gamma: [0.0, 0.01, 0.1, 1.0] BayesR starting pi: [0.95, 0.03, 0.015, 0.005] BayesR expected class counts: [4.75, 0.15, 0.08, 0.02] The file results/MCMC_samples_residual_variance.txt is created to save MCMC samples for residual_variance. The file results/MCMC_samples_marker_effects_annotated_bayesr_fast_independent_y1.txt is created to save MCMC samples for marker_effects_annotated_bayesr_fast_independent_y1. The file results/MCMC_samples_marker_effects_variances_annotated_bayesr_fast_independent.txt is created to save MCMC samples for marker_effects_variances_annotated_bayesr_fast_independent. The file results/MCMC_samples_pi_annotated_bayesr_fast_independent.txt is created to save MCMC samples for pi_annotated_bayesr_fast_independent. running MCMC ... 17%|█████▉ | ETA: 0:00:09 running MCMC ... 100%|███████████████████████████████████| Time: 0:00:01 The version of Julia and Platform in use: Julia Version 1.14.0-DEV.3055 Build Info: Commit 7e75a8061a* (2026-08-27 09:46 UTC) GC: Built with stock GC Platform Info: OS: Linux (x86_64-unknown-linux-gnu) CPU: 128 × AMD EPYC 7502 32-Core Processor (znver2) WORD_SIZE: 64 LLVM: libLLVM-22.1.8 (ORCJIT, znver2) Threads: 1 default, 0 interactive, 1 GC (on 1 virtual cores) Environment: JULIA_CPU_THREADS = 1 JULIA_NUM_PRECOMPILE_TASKS = 1 JULIA_PKG_PRECOMPILE_AUTO = 0 JULIA_PKGEVAL = true JULIA_DEPOT_PATH = /home/pkgeval/.julia:/usr/local/share/julia: JULIA_NUM_THREADS = 1 JULIA_LOAD_PATH = @:/tmp/jl_g0vHag The analysis has finished. Results are saved in the returned variable and text files. MCMC samples are saved in text files. The delimiter in pedigree.txt is ','. coding pedigree... 17%|█████▍ | ETA: 0:00:01 coding pedigree... 100%|████████████████████████████████| Time: 0:00:00 calculating inbreeding... 17%|████▏ | ETA: 0:00:02 calculating inbreeding... 100%|█████████████████████████| Time: 0:00:00 Pedigree information: #individuals: 12 #sires: 4 #dams: 5 #founders: 3 The folder test_set_random_ped is created to save results. Checking pedigree... Checking phenotypes... Individual IDs (strings) are provided in the first column of the phenotypic data. Predicted values for individuals of interest will be obtained as the summation of Any["y1:ID"] (Note that genomic data is always included for now).Phenotypes for 4 observations are used in the analysis.These individual IDs are saved in the file test_set_random_ped/IDs_for_individuals_with_phenotypes.txt. A Linear Mixed Model was build using model equations: y1 = intercept + ID Model Information: Term C/F F/R nLevels intercept factor fixed 1 ID factor random 12 MCMC Information: chain_length 50 burnin 0 starting_value true printout_frequency 51 output_samples_frequency 1 constraint on residual variance false missing_phenotypes true update_priors_frequency 0 seed 123 Hyper-parameters Information: random effect variances (y1:ID): [1.600000023841858;;] genetic variances (polygenic): 1.6f0 residual variances: 1.000 Genomic Information: Degree of freedom for hyper-parameters: residual variances: 4.000 polygenic effect variances: 5.000 The file test_set_random_ped/MCMC_samples_residual_variance.txt is created to save MCMC samples for residual_variance. The file test_set_random_ped/MCMC_samples_polygenic_effects_variance.txt is created to save MCMC samples for polygenic_effects_variance. The file test_set_random_ped/MCMC_samples_y1.ID_variances.txt is created to save MCMC samples for y1:ID_variances. The file test_set_random_ped/MCMC_samples_EBV_y1.txt is created to save MCMC samples for EBV_y1. The file test_set_random_ped/MCMC_samples_genetic_variance.txt is created to save MCMC samples for genetic_variance. The file test_set_random_ped/MCMC_samples_heritability.txt is created to save MCMC samples for heritability. running MCMC ... 4%|█▍ | ETA: 0:01:37 running MCMC ... 100%|███████████████████████████████████| Time: 0:00:04 The version of Julia and Platform in use: Julia Version 1.14.0-DEV.3055 Build Info: Commit 7e75a8061a* (2026-08-27 09:46 UTC) GC: Built with stock GC Platform Info: OS: Linux (x86_64-unknown-linux-gnu) CPU: 128 × AMD EPYC 7502 32-Core Processor (znver2) WORD_SIZE: 64 LLVM: libLLVM-22.1.8 (ORCJIT, znver2) Threads: 1 default, 0 interactive, 1 GC (on 1 virtual cores) Environment: JULIA_CPU_THREADS = 1 JULIA_NUM_PRECOMPILE_TASKS = 1 JULIA_PKG_PRECOMPILE_AUTO = 0 JULIA_PKGEVAL = true JULIA_DEPOT_PATH = /home/pkgeval/.julia:/usr/local/share/julia: JULIA_NUM_THREADS = 1 JULIA_LOAD_PATH = @:/tmp/jl_g0vHag The analysis has finished. Results are saved in the returned variable and text files. MCMC samples are saved in text files. The delimiter in genotypes.txt is ','. The header (marker IDs) is provided in genotypes.txt. Missing values (9.0) are replaced by column means. EBV output with genotypes: Error During Test at /home/pkgeval/.julia/packages/JWAS/AxFc6/test/unit/test_output_ebv.jl:9 Got exception outside of a @test MethodError: no method matching reducedim1(::Matrix{Float32}, ::Matrix{Float32}) The function `reducedim1` exists, but no method is defined for this combination of argument types. Closest candidates are: reducedim1(::Any) @ Base reducedim.jl:1229 Stacktrace: [1] centralize_sumabs2!(R::Matrix{Float32}, A::Matrix{Float32}, means::Matrix{Float32}) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:282 [2] varm!(R::Matrix{Float32}, A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:309 [3] _varm(A::Matrix{Float32}, m::Matrix{Float32}, corrected::Bool, region::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:341 [4] varm(A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:339 [inlined] [5] _var(A::Matrix{Float32}, corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:386 [inlined] [6] var(A::Matrix{Float32}; corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:380 [inlined] [7] get_genotypes(file::String, G::Float64; method::String, Pi::Float64, estimatePi::Bool, G_is_marker_variance::Bool, df::Float64, estimate_variance::Bool, estimate_scale::Bool, constraint::Bool, separator::Char, header::Bool, double_precision::Bool, quality_control::Bool, MAF::Float64, missing_value::Float64, center::Bool, starting_value::Bool, annotations::Bool, multi_trait_sampler::Symbol, storage::Symbol) @ JWAS ~/.julia/packages/JWAS/AxFc6/src/1.JWAS/src/markers/readgenotypes.jl:390 [8] top-level scope @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_output_ebv.jl:9 [9] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [10] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_output_ebv.jl:10 [inlined] [11] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [12] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_output_ebv.jl:10 [inlined] The delimiter in genotypes.txt is ','. The header (marker IDs) is provided in genotypes.txt. Missing values (9.0) are replaced by column means. EBV output with heritability: Error During Test at /home/pkgeval/.julia/packages/JWAS/AxFc6/test/unit/test_output_ebv.jl:33 Got exception outside of a @test MethodError: no method matching reducedim1(::Matrix{Float32}, ::Matrix{Float32}) The function `reducedim1` exists, but no method is defined for this combination of argument types. Closest candidates are: reducedim1(::Any) @ Base reducedim.jl:1229 Stacktrace: [1] centralize_sumabs2!(R::Matrix{Float32}, A::Matrix{Float32}, means::Matrix{Float32}) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:282 [2] varm!(R::Matrix{Float32}, A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:309 [3] _varm(A::Matrix{Float32}, m::Matrix{Float32}, corrected::Bool, region::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:341 [4] varm(A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:339 [inlined] [5] _var(A::Matrix{Float32}, corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:386 [inlined] [6] var(A::Matrix{Float32}; corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:380 [inlined] [7] get_genotypes(file::String, G::Float64; method::String, Pi::Float64, estimatePi::Bool, G_is_marker_variance::Bool, df::Float64, estimate_variance::Bool, estimate_scale::Bool, constraint::Bool, separator::Char, header::Bool, double_precision::Bool, quality_control::Bool, MAF::Float64, missing_value::Float64, center::Bool, starting_value::Bool, annotations::Bool, multi_trait_sampler::Symbol, storage::Symbol) @ JWAS ~/.julia/packages/JWAS/AxFc6/src/1.JWAS/src/markers/readgenotypes.jl:390 [8] top-level scope @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_output_ebv.jl:9 [9] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [10] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_output_ebv.jl:34 [inlined] [11] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [12] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_output_ebv.jl:34 [inlined] The delimiter in genotypes.txt is ','. The header (marker IDs) is provided in genotypes.txt. Missing values (9.0) are replaced by column means. outputMCMCsamples for location parameters: Error During Test at /home/pkgeval/.julia/packages/JWAS/AxFc6/test/unit/test_output_ebv.jl:58 Got exception outside of a @test MethodError: no method matching reducedim1(::Matrix{Float32}, ::Matrix{Float32}) The function `reducedim1` exists, but no method is defined for this combination of argument types. Closest candidates are: reducedim1(::Any) @ Base reducedim.jl:1229 Stacktrace: [1] centralize_sumabs2!(R::Matrix{Float32}, A::Matrix{Float32}, means::Matrix{Float32}) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:282 [2] varm!(R::Matrix{Float32}, A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:309 [3] _varm(A::Matrix{Float32}, m::Matrix{Float32}, corrected::Bool, region::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:341 [4] varm(A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:339 [inlined] [5] _var(A::Matrix{Float32}, corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:386 [inlined] [6] var(A::Matrix{Float32}; corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:380 [inlined] [7] get_genotypes(file::String, G::Float64; method::String, Pi::Float64, estimatePi::Bool, G_is_marker_variance::Bool, df::Float64, estimate_variance::Bool, estimate_scale::Bool, constraint::Bool, separator::Char, header::Bool, double_precision::Bool, quality_control::Bool, MAF::Float64, missing_value::Float64, center::Bool, starting_value::Bool, annotations::Bool, multi_trait_sampler::Symbol, storage::Symbol) @ JWAS ~/.julia/packages/JWAS/AxFc6/src/1.JWAS/src/markers/readgenotypes.jl:390 [8] top-level scope @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_output_ebv.jl:59 [9] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [10] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_output_ebv.jl:59 [inlined] The delimiter in pedigree.txt is ','. Pedigree information: #individuals: 12 #sires: 4 #dams: 5 #founders: 3 Pedigree information: #individuals: 12 #sires: 4 #dams: 5 #founders: 3 Get individual IDs, inverse of numerator relationship matrix, and inbreeding coefficients. Pedigree information: #individuals: 3 #sires: 1 #dams: 1 #founders: 2 The delimiter in pedigree.txt is ','. Pedigree information: #individuals: 12 #sires: 4 #dams: 5 #founders: 3 The delimiter in genotypes.txt is ','. The header (marker IDs) is provided in genotypes.txt. Missing values (9.0) are replaced by column means. Invalid Bayesian method: Error During Test at /home/pkgeval/.julia/packages/JWAS/AxFc6/test/unit/test_input_validation.jl:9 Got exception outside of a @test MethodError: no method matching reducedim1(::Matrix{Float32}, ::Matrix{Float32}) The function `reducedim1` exists, but no method is defined for this combination of argument types. Closest candidates are: reducedim1(::Any) @ Base reducedim.jl:1229 Stacktrace: [1] centralize_sumabs2!(R::Matrix{Float32}, A::Matrix{Float32}, means::Matrix{Float32}) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:282 [2] varm!(R::Matrix{Float32}, A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:309 [3] _varm(A::Matrix{Float32}, m::Matrix{Float32}, corrected::Bool, region::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:341 [4] varm(A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:339 [inlined] [5] _var(A::Matrix{Float32}, corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:386 [inlined] [6] var(A::Matrix{Float32}; corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:380 [inlined] [7] get_genotypes(file::String, G::Float64; method::String, Pi::Float64, estimatePi::Bool, G_is_marker_variance::Bool, df::Float64, estimate_variance::Bool, estimate_scale::Bool, constraint::Bool, separator::Char, header::Bool, double_precision::Bool, quality_control::Bool, MAF::Float64, missing_value::Float64, center::Bool, starting_value::Bool, annotations::Bool, multi_trait_sampler::Symbol, storage::Symbol) @ JWAS ~/.julia/packages/JWAS/AxFc6/src/1.JWAS/src/markers/readgenotypes.jl:390 [8] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_input_validation.jl:10 [inlined] [9] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [10] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_input_validation.jl:10 [inlined] [11] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [12] top-level scope @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_input_validation.jl:5 The folder test_ss_no_geno is created to save results. The delimiter in genotypes.txt is ','. The header (marker IDs) is provided in genotypes.txt. Missing values (9.0) are replaced by column means. output_samples_frequency validation: Error During Test at /home/pkgeval/.julia/packages/JWAS/AxFc6/test/unit/test_input_validation.jl:31 Got exception outside of a @test MethodError: no method matching reducedim1(::Matrix{Float32}, ::Matrix{Float32}) The function `reducedim1` exists, but no method is defined for this combination of argument types. Closest candidates are: reducedim1(::Any) @ Base reducedim.jl:1229 Stacktrace: [1] centralize_sumabs2!(R::Matrix{Float32}, A::Matrix{Float32}, means::Matrix{Float32}) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:282 [2] varm!(R::Matrix{Float32}, A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:309 [3] _varm(A::Matrix{Float32}, m::Matrix{Float32}, corrected::Bool, region::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:341 [4] varm(A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:339 [inlined] [5] _var(A::Matrix{Float32}, corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:386 [inlined] [6] var(A::Matrix{Float32}; corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:380 [inlined] [7] get_genotypes(file::String, G::Float64; method::String, Pi::Float64, estimatePi::Bool, G_is_marker_variance::Bool, df::Float64, estimate_variance::Bool, estimate_scale::Bool, constraint::Bool, separator::Char, header::Bool, double_precision::Bool, quality_control::Bool, MAF::Float64, missing_value::Float64, center::Bool, starting_value::Bool, annotations::Bool, multi_trait_sampler::Symbol, storage::Symbol) @ JWAS ~/.julia/packages/JWAS/AxFc6/src/1.JWAS/src/markers/readgenotypes.jl:390 [8] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_input_validation.jl:32 [inlined] [9] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [10] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_input_validation.jl:32 [inlined] [11] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [12] top-level scope @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_input_validation.jl:5 A Linear Mixed Model was build using model equations: y1 = intercept + x1 Model Information: Term C/F F/R nLevels intercept factor fixed 0 x1 factor fixed 0 The delimiter in genotypes.txt is ','. The header (marker IDs) is provided in genotypes.txt. Missing values (9.0) are replaced by column means. Multiple Bayesian methods load correctly: Error During Test at /home/pkgeval/.julia/packages/JWAS/AxFc6/test/unit/test_input_validation.jl:48 Got exception outside of a @test MethodError: no method matching reducedim1(::Matrix{Float32}, ::Matrix{Float32}) The function `reducedim1` exists, but no method is defined for this combination of argument types. Closest candidates are: reducedim1(::Any) @ Base reducedim.jl:1229 Stacktrace: [1] centralize_sumabs2!(R::Matrix{Float32}, A::Matrix{Float32}, means::Matrix{Float32}) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:282 [2] varm!(R::Matrix{Float32}, A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:309 [3] _varm(A::Matrix{Float32}, m::Matrix{Float32}, corrected::Bool, region::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:341 [4] varm(A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:339 [inlined] [5] _var(A::Matrix{Float32}, corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:386 [inlined] [6] var(A::Matrix{Float32}; corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:380 [inlined] [7] get_genotypes(file::String, G::Float64; method::String, Pi::Float64, estimatePi::Bool, G_is_marker_variance::Bool, df::Float64, estimate_variance::Bool, estimate_scale::Bool, constraint::Bool, separator::Char, header::Bool, double_precision::Bool, quality_control::Bool, MAF::Float64, missing_value::Float64, center::Bool, starting_value::Bool, annotations::Bool, multi_trait_sampler::Symbol, storage::Symbol) @ JWAS ~/.julia/packages/JWAS/AxFc6/src/1.JWAS/src/markers/readgenotypes.jl:390 [8] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_input_validation.jl:50 [inlined] [9] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [10] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_input_validation.jl:49 [inlined] [11] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [12] top-level scope @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_input_validation.jl:5 The delimiter in pedigree.txt is ','. Pedigree information: #individuals: 12 #sires: 4 #dams: 5 #founders: 3 The delimiter in genotypes.txt is ','. The header (marker IDs) is provided in genotypes.txt. Missing values (9.0) are replaced by column means. BayesC accepts CSV inline-string IDs: Error During Test at /home/pkgeval/.julia/packages/JWAS/AxFc6/test/unit/test_single_step.jl:12 Got exception outside of a @test MethodError: no method matching reducedim1(::Matrix{Float32}, ::Matrix{Float32}) The function `reducedim1` exists, but no method is defined for this combination of argument types. Closest candidates are: reducedim1(::Any) @ Base reducedim.jl:1229 Stacktrace: [1] centralize_sumabs2!(R::Matrix{Float32}, A::Matrix{Float32}, means::Matrix{Float32}) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:282 [2] varm!(R::Matrix{Float32}, A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:309 [3] _varm(A::Matrix{Float32}, m::Matrix{Float32}, corrected::Bool, region::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:341 [4] varm(A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:339 [inlined] [5] _var(A::Matrix{Float32}, corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:386 [inlined] [6] var(A::Matrix{Float32}; corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:380 [inlined] [7] get_genotypes(file::String, G::Bool; method::String, Pi::Float64, estimatePi::Bool, G_is_marker_variance::Bool, df::Float64, estimate_variance::Bool, estimate_scale::Bool, constraint::Bool, separator::Char, header::Bool, double_precision::Bool, quality_control::Bool, MAF::Float64, missing_value::Float64, center::Bool, starting_value::Bool, annotations::Bool, multi_trait_sampler::Symbol, storage::Symbol) @ JWAS ~/.julia/packages/JWAS/AxFc6/src/1.JWAS/src/markers/readgenotypes.jl:390 [8] top-level scope @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_single_step.jl:5 [9] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [10] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_single_step.jl:13 [inlined] [11] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [12] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_single_step.jl:15 [inlined] The delimiter in genotypes.txt is ','. The header (marker IDs) is provided in genotypes.txt. Missing values (9.0) are replaced by column means. BayesC accepts multiple genotype categories: Error During Test at /home/pkgeval/.julia/packages/JWAS/AxFc6/test/unit/test_single_step.jl:41 Got exception outside of a @test MethodError: no method matching reducedim1(::Matrix{Float32}, ::Matrix{Float32}) The function `reducedim1` exists, but no method is defined for this combination of argument types. Closest candidates are: reducedim1(::Any) @ Base reducedim.jl:1229 Stacktrace: [1] centralize_sumabs2!(R::Matrix{Float32}, A::Matrix{Float32}, means::Matrix{Float32}) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:282 [2] varm!(R::Matrix{Float32}, A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:309 [3] _varm(A::Matrix{Float32}, m::Matrix{Float32}, corrected::Bool, region::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:341 [4] varm(A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:339 [inlined] [5] _var(A::Matrix{Float32}, corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:386 [inlined] [6] var(A::Matrix{Float32}; corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:380 [inlined] [7] get_genotypes(file::String, G::Bool; method::String, Pi::Float64, estimatePi::Bool, G_is_marker_variance::Bool, df::Float64, estimate_variance::Bool, estimate_scale::Bool, constraint::Bool, separator::Char, header::Bool, double_precision::Bool, quality_control::Bool, MAF::Float64, missing_value::Float64, center::Bool, starting_value::Bool, annotations::Bool, multi_trait_sampler::Symbol, storage::Symbol) @ JWAS ~/.julia/packages/JWAS/AxFc6/src/1.JWAS/src/markers/readgenotypes.jl:390 [8] top-level scope @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_single_step.jl:5 [9] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [10] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_single_step.jl:42 [inlined] [11] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [12] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_single_step.jl:44 [inlined] The delimiter in genotypes.txt is ','. The header (marker IDs) is provided in genotypes.txt. Genotype informatin: #markers: 5; #individuals: 7 The delimiter in genotypes.txt is ','. The header (marker IDs) is provided in genotypes.txt. Genotype informatin: #markers: 5; #individuals: 7 The folder test_single_step_annotated_bayesc is created to save results. Checking pedigree... Checking genotypes... Checking phenotypes... Individual IDs (strings) are provided in the first column of the phenotypic data. Predicted values for individuals of interest will be obtained as the summation of Any[] (Note that genomic data is always included for now).Phenotypes for 4 observations are used in the analysis.These individual IDs are saved in the file test_single_step_annotated_bayesc/IDs_for_individuals_with_phenotypes.txt. calculating A inverse 0.718042 seconds (126.35 k allocations: 7.897 MiB, 99.88% compilation time) imputing missing genotypes for annotated_ss_geno1 7.567814 seconds (2.30 M allocations: 148.767 MiB, 8.40% gc time, 91.37% compilation time) completed imputing genotypes for annotated_ss_geno1 imputing missing genotypes for annotated_ss_geno2 0.455182 seconds (540 allocations: 35.664 KiB, 99.86% gc time) completed imputing genotypes for annotated_ss_geno2 The prior for marker effects variance is calculated from the genetic variance and π. The mean of the prior for the marker effects variance is: 0.492462 The prior for marker effects variance is calculated from the genetic variance and π. The mean of the prior for the marker effects variance is: 0.492462 A Linear Mixed Model was build using model equations: y1 = intercept + annotated_ss_geno1 + annotated_ss_geno2 Model Information: Term C/F F/R nLevels intercept factor fixed 1 ϵ factor random 5 J covariate fixed 1 The file test_single_step_annotated_bayesc/MCMC_samples_residual_variance.txt is created to save MCMC samples for residual_variance. The file test_single_step_annotated_bayesc/MCMC_samples_marker_effects_annotated_ss_geno1_y1.txt is created to save MCMC samples for marker_effects_annotated_ss_geno1_y1. The file test_single_step_annotated_bayesc/MCMC_samples_marker_effects_variances_annotated_ss_geno1.txt is created to save MCMC samples for marker_effects_variances_annotated_ss_geno1. The file test_single_step_annotated_bayesc/MCMC_samples_pi_annotated_ss_geno1.txt is created to save MCMC samples for pi_annotated_ss_geno1. The file test_single_step_annotated_bayesc/MCMC_samples_marker_effects_annotated_ss_geno2_y1.txt is created to save MCMC samples for marker_effects_annotated_ss_geno2_y1. The file test_single_step_annotated_bayesc/MCMC_samples_marker_effects_variances_annotated_ss_geno2.txt is created to save MCMC samples for marker_effects_variances_annotated_ss_geno2. The file test_single_step_annotated_bayesc/MCMC_samples_pi_annotated_ss_geno2.txt is created to save MCMC samples for pi_annotated_ss_geno2. The file test_single_step_annotated_bayesc/MCMC_samples_y1.J.txt is created to save MCMC samples for y1:J. The file test_single_step_annotated_bayesc/MCMC_samples_y1.ϵ.txt is created to save MCMC samples for y1:ϵ. The file test_single_step_annotated_bayesc/MCMC_samples_y1.ϵ_variances.txt is created to save MCMC samples for y1:ϵ_variances. The file test_single_step_annotated_bayesc/MCMC_samples_EBV_y1.txt is created to save MCMC samples for EBV_y1. Annotated BayesC and BayesR accept multiple genotype categories: Error During Test at /home/pkgeval/.julia/packages/JWAS/AxFc6/test/unit/test_single_step.jl:78 Got exception outside of a @test MethodError: no method matching reducedim1(::Matrix{Float64}, ::Matrix{Float64}) The function `reducedim1` exists, but no method is defined for this combination of argument types. Closest candidates are: reducedim1(::Any) @ Base reducedim.jl:1229 Stacktrace: [1] centralize_sumabs2!(R::Matrix{Float64}, A::Matrix{Float64}, means::Matrix{Float64}) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:282 [2] varm!(R::Matrix{Float64}, A::Matrix{Float64}, m::Matrix{Float64}; corrected::Bool) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:309 [3] _varm(A::Matrix{Float64}, m::Matrix{Float64}, corrected::Bool, region::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:341 [4] varm(A::Matrix{Float64}, m::Matrix{Float64}; corrected::Bool, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:339 [inlined] [5] _var(A::Matrix{Float64}, corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:386 [inlined] [6] var(A::Matrix{Float64}; corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:380 [inlined] [7] output_result(mme::JWAS.MME, output_folder::String, solMean::Vector{Float64}, meanVare::Float64, G0Mean::Bool, solMean2::Vector{Float64}, meanVare2::Float64, G0Mean2::Bool) @ JWAS ~/.julia/packages/JWAS/AxFc6/src/1.JWAS/src/output.jl:199 [8] MCMC_BayesianAlphabet(mme::JWAS.MME, df::DataFrame) @ JWAS ~/.julia/packages/JWAS/AxFc6/src/1.JWAS/src/MCMC/MCMC_BayesianAlphabet.jl:446 [9] runMCMC(mme::JWAS.MME, df::DataFrame; heterogeneous_residuals::Bool, chain_length::Int64, starting_value::Bool, burnin::Int64, output_samples_frequency::Int64, update_priors_frequency::Int64, single_step_analysis::Bool, pedigree::JWAS.PedModule.Pedigree, fitting_J_vector::Bool, causal_structure::Bool, missing_phenotypes::Bool, RRM::Bool, outputEBV::Bool, output_heritability::Bool, prediction_equation::Bool, seed::Int64, printout_model_info::Bool, printout_frequency::Int64, big_memory::Bool, double_precision::Bool, fast_blocks::Bool, independent_blocks::Bool, memory_guard::Symbol, memory_guard_ratio::Float64, output_folder::String, output_samples_for_all_parameters::Bool, methods::String, Pi::Float64, estimatePi::Bool, estimate_scale::Bool, estimate_variance::Bool, categorical_trait::Bool, censored_trait::Bool) @ JWAS ~/.julia/packages/JWAS/AxFc6/src/1.JWAS/src/JWAS.jl:466 [10] top-level scope @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_single_step.jl:5 [11] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [12] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_single_step.jl:79 [inlined] [13] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [14] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_single_step.jl:110 [inlined] The delimiter in genotypes.txt is ','. The header (marker IDs) is provided in genotypes.txt. Missing values (9.0) are replaced by column means. Multi-trait BayesC: Error During Test at /home/pkgeval/.julia/packages/JWAS/AxFc6/test/unit/test_multitrait_mcmc.jl:131 Got exception outside of a @test MethodError: no method matching reducedim1(::Matrix{Float32}, ::Matrix{Float32}) The function `reducedim1` exists, but no method is defined for this combination of argument types. Closest candidates are: reducedim1(::Any) @ Base reducedim.jl:1229 Stacktrace: [1] centralize_sumabs2!(R::Matrix{Float32}, A::Matrix{Float32}, means::Matrix{Float32}) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:282 [2] varm!(R::Matrix{Float32}, A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:309 [3] _varm(A::Matrix{Float32}, m::Matrix{Float32}, corrected::Bool, region::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:341 [4] varm(A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:339 [inlined] [5] _var(A::Matrix{Float32}, corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:386 [inlined] [6] var(A::Matrix{Float32}; corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:380 [inlined] [7] get_genotypes(file::String, G::Matrix{Float64}; method::String, Pi::Float64, estimatePi::Bool, G_is_marker_variance::Bool, df::Float64, estimate_variance::Bool, estimate_scale::Bool, constraint::Bool, separator::Char, header::Bool, double_precision::Bool, quality_control::Bool, MAF::Float64, missing_value::Float64, center::Bool, starting_value::Bool, annotations::Bool, multi_trait_sampler::Symbol, storage::Symbol) @ JWAS ~/.julia/packages/JWAS/AxFc6/src/1.JWAS/src/markers/readgenotypes.jl:390 [8] top-level scope @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_multitrait_mcmc.jl:132 [9] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [10] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_multitrait_mcmc.jl:133 [inlined] The delimiter in genotypes.txt is ','. The header (marker IDs) is provided in genotypes.txt. Missing values (9.0) are replaced by column means. Multi-trait BayesC sampler default and auto selection: Error During Test at /home/pkgeval/.julia/packages/JWAS/AxFc6/test/unit/test_multitrait_mcmc.jl:150 Got exception outside of a @test MethodError: no method matching reducedim1(::Matrix{Float32}, ::Matrix{Float32}) The function `reducedim1` exists, but no method is defined for this combination of argument types. Closest candidates are: reducedim1(::Any) @ Base reducedim.jl:1229 Stacktrace: [1] centralize_sumabs2!(R::Matrix{Float32}, A::Matrix{Float32}, means::Matrix{Float32}) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:282 [2] varm!(R::Matrix{Float32}, A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:309 [3] _varm(A::Matrix{Float32}, m::Matrix{Float32}, corrected::Bool, region::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:341 [4] varm(A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:339 [inlined] [5] _var(A::Matrix{Float32}, corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:386 [inlined] [6] var(A::Matrix{Float32}; corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:380 [inlined] [7] get_genotypes(file::String, G::Matrix{Float64}; method::String, Pi::Float64, estimatePi::Bool, G_is_marker_variance::Bool, df::Float64, estimate_variance::Bool, estimate_scale::Bool, constraint::Bool, separator::Char, header::Bool, double_precision::Bool, quality_control::Bool, MAF::Float64, missing_value::Float64, center::Bool, starting_value::Bool, annotations::Bool, multi_trait_sampler::Symbol, storage::Symbol) @ JWAS ~/.julia/packages/JWAS/AxFc6/src/1.JWAS/src/markers/readgenotypes.jl:390 [8] top-level scope @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_multitrait_mcmc.jl:151 [9] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [10] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_multitrait_mcmc.jl:153 [inlined] The delimiter in genotypes.txt is ','. The header (marker IDs) is provided in genotypes.txt. Genotype informatin: #markers: 5; #individuals: 7 The folder test_mt_annotated_bayesc is created to save results. Checking genotypes... Checking phenotypes... Individual IDs (strings) are provided in the first column of the phenotypic data. In this complete genomic data (non-single-step) analyis, 1 phenotyped individuals are not genotyped. These are removed from the analysis. Predicted values for individuals of interest will be obtained as the summation of Any[] (Note that genomic data is always included for now).Phenotypes for 7 observations are used in the analysis.These individual IDs are saved in the file test_mt_annotated_bayesc/IDs_for_individuals_with_phenotypes.txt. The prior for marker effects covariance matrix is calculated from genetic covariance matrix and Π. The mean of the prior for the marker effects covariance matrix is: 1.231156 1.231156 1.231156 1.407035 A Linear Mixed Model was build using model equations: y1 = intercept + annotated_mt_geno y2 = intercept + annotated_mt_geno Model Information: Term C/F F/R nLevels intercept factor fixed 1 MCMC Information: chain_length 40 burnin 10 starting_value true printout_frequency 41 output_samples_frequency 10 constraint on residual variance false constraint on marker effect variance for annotated_mt_geno false missing_phenotypes true update_priors_frequency 0 seed 123 Hyper-parameters Information: residual variances: 1.0f0 0.5f0 0.5f0 1.0f0 Genomic Information: complete genomic data (i.e., non-single-step analysis) Genomic Category annotated_mt_geno Method BayesC genetic variances (genomic): 1.0 0.5 0.5 1.0 marker effect variances: 1.231 1.231 1.231 1.407 Π: (Y(yes):included; N(no):excluded) ["y1", "y2"] probability ["N", "Y"] 0.15 ["N", "N"] 0.45 ["Y", "Y"] 0.2 ["Y", "N"] 0.2 estimatePi true estimate_scale false Degree of freedom for hyper-parameters: residual variances: 6.000 marker effect variances: 6.000 The file test_mt_annotated_bayesc/MCMC_samples_residual_variance.txt is created to save MCMC samples for residual_variance. The file test_mt_annotated_bayesc/MCMC_samples_marker_effects_annotated_mt_geno_y1.txt is created to save MCMC samples for marker_effects_annotated_mt_geno_y1. The file test_mt_annotated_bayesc/MCMC_samples_marker_effects_annotated_mt_geno_y2.txt is created to save MCMC samples for marker_effects_annotated_mt_geno_y2. The file test_mt_annotated_bayesc/MCMC_samples_marker_effects_variances_annotated_mt_geno.txt is created to save MCMC samples for marker_effects_variances_annotated_mt_geno. The file test_mt_annotated_bayesc/MCMC_samples_pi_annotated_mt_geno.txt is created to save MCMC samples for pi_annotated_mt_geno. The file test_mt_annotated_bayesc/MCMC_samples_EBV_y1.txt is created to save MCMC samples for EBV_y1. The file test_mt_annotated_bayesc/MCMC_samples_EBV_y2.txt is created to save MCMC samples for EBV_y2. The file test_mt_annotated_bayesc/MCMC_samples_genetic_variance.txt is created to save MCMC samples for genetic_variance. The file test_mt_annotated_bayesc/MCMC_samples_heritability.txt is created to save MCMC samples for heritability. running MCMC ... 5%|█▊ | ETA: 0:01:31 running MCMC ... 100%|███████████████████████████████████| Time: 0:00:05 Multi-trait annotated BayesC: Error During Test at /home/pkgeval/.julia/packages/JWAS/AxFc6/test/unit/test_multitrait_mcmc.jl:160 Got exception outside of a @test MethodError: no method matching reducedim1(::Matrix{Float64}, ::Matrix{Float64}) The function `reducedim1` exists, but no method is defined for this combination of argument types. Closest candidates are: reducedim1(::Any) @ Base reducedim.jl:1229 Stacktrace: [1] centralize_sumabs2!(R::Matrix{Float64}, A::Matrix{Float64}, means::Matrix{Float64}) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:282 [2] varm!(R::Matrix{Float64}, A::Matrix{Float64}, m::Matrix{Float64}; corrected::Bool) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:309 [3] _varm(A::Matrix{Float64}, m::Matrix{Float64}, corrected::Bool, region::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:341 [4] varm(A::Matrix{Float64}, m::Matrix{Float64}; corrected::Bool, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:339 [inlined] [5] _var(A::Matrix{Float64}, corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:386 [inlined] [6] var(A::Matrix{Float64}; corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:380 [inlined] [7] output_result(mme::JWAS.MME, output_folder::String, solMean::Vector{Float64}, meanVare::Matrix{Float64}, G0Mean::Bool, solMean2::Vector{Float64}, meanVare2::Matrix{Float64}, G0Mean2::Bool) @ JWAS ~/.julia/packages/JWAS/AxFc6/src/1.JWAS/src/output.jl:199 [8] MCMC_BayesianAlphabet(mme::JWAS.MME, df::DataFrame) @ JWAS ~/.julia/packages/JWAS/AxFc6/src/1.JWAS/src/MCMC/MCMC_BayesianAlphabet.jl:446 [9] runMCMC(mme::JWAS.MME, df::DataFrame; heterogeneous_residuals::Bool, chain_length::Int64, starting_value::Bool, burnin::Int64, output_samples_frequency::Int64, update_priors_frequency::Int64, single_step_analysis::Bool, pedigree::Bool, fitting_J_vector::Bool, causal_structure::Bool, missing_phenotypes::Bool, RRM::Bool, outputEBV::Bool, output_heritability::Bool, prediction_equation::Bool, seed::Int64, printout_model_info::Bool, printout_frequency::Int64, big_memory::Bool, double_precision::Bool, fast_blocks::Bool, independent_blocks::Bool, memory_guard::Symbol, memory_guard_ratio::Float64, output_folder::String, output_samples_for_all_parameters::Bool, methods::String, Pi::Float64, estimatePi::Bool, estimate_scale::Bool, estimate_variance::Bool, categorical_trait::Bool, censored_trait::Bool) @ JWAS ~/.julia/packages/JWAS/AxFc6/src/1.JWAS/src/JWAS.jl:466 [10] top-level scope @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_multitrait_mcmc.jl:161 [11] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [12] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_multitrait_mcmc.jl:191 [inlined] The delimiter in genotypes.txt is ','. The header (marker IDs) is provided in genotypes.txt. Genotype informatin: #markers: 5; #individuals: 7 The folder test_mt_annotated_bayesr is created to save results. Checking genotypes... Checking phenotypes... Individual IDs (strings) are provided in the first column of the phenotypic data. In this complete genomic data (non-single-step) analyis, 1 phenotyped individuals are not genotyped. These are removed from the analysis. Predicted values for individuals of interest will be obtained as the summation of Any[] (Note that genomic data is always included for now).Phenotypes for 7 observations are used in the analysis.These individual IDs are saved in the file test_mt_annotated_bayesr/IDs_for_individuals_with_phenotypes.txt. The prior for marker effects covariance matrix is calculated from genetic covariance matrix and Π. The mean of the prior for the marker effects covariance matrix is: A Linear Mixed Model was build using model equations: y1 = intercept + annotated_mt_bayesr y2 = intercept + annotated_mt_bayesr Model Information: Term C/F F/R nLevels intercept factor fixed 1 The file test_mt_annotated_bayesr/MCMC_samples_residual_variance.txt is created to save MCMC samples for residual_variance. The file test_mt_annotated_bayesr/MCMC_samples_marker_effects_annotated_mt_bayesr_y1.txt is created to save MCMC samples for marker_effects_annotated_mt_bayesr_y1. The file test_mt_annotated_bayesr/MCMC_samples_marker_effects_annotated_mt_bayesr_y2.txt is created to save MCMC samples for marker_effects_annotated_mt_bayesr_y2. The file test_mt_annotated_bayesr/MCMC_samples_marker_effects_variances_annotated_mt_bayesr.txt is created to save MCMC samples for marker_effects_variances_annotated_mt_bayesr. The file test_mt_annotated_bayesr/MCMC_samples_pi_annotated_mt_bayesr.txt is created to save MCMC samples for pi_annotated_mt_bayesr. running MCMC ... 10%|███▌ | ETA: 0:00:33 running MCMC ... 100%|███████████████████████████████████| Time: 0:00:03 The version of Julia and Platform in use: Julia Version 1.14.0-DEV.3055 Build Info: Commit 7e75a8061a* (2026-08-27 09:46 UTC) GC: Built with stock GC Platform Info: OS: Linux (x86_64-unknown-linux-gnu) CPU: 128 × AMD EPYC 7502 32-Core Processor (znver2) WORD_SIZE: 64 LLVM: libLLVM-22.1.8 (ORCJIT, znver2) Threads: 1 default, 0 interactive, 1 GC (on 1 virtual cores) Environment: JULIA_CPU_THREADS = 1 JULIA_NUM_PRECOMPILE_TASKS = 1 JULIA_PKG_PRECOMPILE_AUTO = 0 JULIA_PKGEVAL = true JULIA_DEPOT_PATH = /home/pkgeval/.julia:/usr/local/share/julia: JULIA_NUM_THREADS = 1 JULIA_LOAD_PATH = @:/tmp/jl_g0vHag The analysis has finished. Results are saved in the returned variable and text files. MCMC samples are saved in text files. The delimiter in genotypes.txt is ','. The header (marker IDs) is provided in genotypes.txt. Genotype informatin: #markers: 5; #individuals: 7 The folder test_mt_annotated_bayesc_sampler2 is created to save results. Checking genotypes... Checking phenotypes... Individual IDs (strings) are provided in the first column of the phenotypic data. In this complete genomic data (non-single-step) analyis, 1 phenotyped individuals are not genotyped. These are removed from the analysis. Predicted values for individuals of interest will be obtained as the summation of Any[] (Note that genomic data is always included for now).Phenotypes for 7 observations are used in the analysis.These individual IDs are saved in the file test_mt_annotated_bayesc_sampler2/IDs_for_individuals_with_phenotypes.txt. The prior for marker effects covariance matrix is calculated from genetic covariance matrix and Π. The mean of the prior for the marker effects covariance matrix is: 1.231156 1.231156 1.231156 1.407035 A Linear Mixed Model was build using model equations: y1 = intercept + annotated_mt_geno_sampler2 y2 = intercept + annotated_mt_geno_sampler2 Model Information: Term C/F F/R nLevels intercept factor fixed 1 MCMC Information: chain_length 40 burnin 10 starting_value true printout_frequency 41 output_samples_frequency 10 constraint on residual variance false constraint on marker effect variance for annotated_mt_geno_sampler2 false missing_phenotypes true update_priors_frequency 0 seed 123 Hyper-parameters Information: residual variances: 1.0f0 0.5f0 0.5f0 1.0f0 Genomic Information: complete genomic data (i.e., non-single-step analysis) Genomic Category annotated_mt_geno_sampler2 Method BayesC genetic variances (genomic): 1.0 0.5 0.5 1.0 marker effect variances: 1.231 1.231 1.231 1.407 Π: (Y(yes):included; N(no):excluded) ["y1", "y2"] probability ["N", "Y"] 0.15 ["N", "N"] 0.45 ["Y", "Y"] 0.2 ["Y", "N"] 0.2 estimatePi true estimate_scale false Degree of freedom for hyper-parameters: residual variances: 6.000 marker effect variances: 6.000 The file test_mt_annotated_bayesc_sampler2/MCMC_samples_residual_variance.txt is created to save MCMC samples for residual_variance. The file test_mt_annotated_bayesc_sampler2/MCMC_samples_marker_effects_annotated_mt_geno_sampler2_y1.txt is created to save MCMC samples for marker_effects_annotated_mt_geno_sampler2_y1. The file test_mt_annotated_bayesc_sampler2/MCMC_samples_marker_effects_annotated_mt_geno_sampler2_y2.txt is created to save MCMC samples for marker_effects_annotated_mt_geno_sampler2_y2. The file test_mt_annotated_bayesc_sampler2/MCMC_samples_marker_effects_variances_annotated_mt_geno_sampler2.txt is created to save MCMC samples for marker_effects_variances_annotated_mt_geno_sampler2. The file test_mt_annotated_bayesc_sampler2/MCMC_samples_pi_annotated_mt_geno_sampler2.txt is created to save MCMC samples for pi_annotated_mt_geno_sampler2. The file test_mt_annotated_bayesc_sampler2/MCMC_samples_EBV_y1.txt is created to save MCMC samples for EBV_y1. The file test_mt_annotated_bayesc_sampler2/MCMC_samples_EBV_y2.txt is created to save MCMC samples for EBV_y2. The file test_mt_annotated_bayesc_sampler2/MCMC_samples_genetic_variance.txt is created to save MCMC samples for genetic_variance. The file test_mt_annotated_bayesc_sampler2/MCMC_samples_heritability.txt is created to save MCMC samples for heritability. running MCMC ... 5%|█▊ | ETA: 0:01:23 running MCMC ... 100%|███████████████████████████████████| Time: 0:00:04 Multi-trait annotated BayesC sampler II override: Error During Test at /home/pkgeval/.julia/packages/JWAS/AxFc6/test/unit/test_multitrait_mcmc.jl:257 Got exception outside of a @test MethodError: no method matching reducedim1(::Matrix{Float64}, ::Matrix{Float64}) The function `reducedim1` exists, but no method is defined for this combination of argument types. Closest candidates are: reducedim1(::Any) @ Base reducedim.jl:1229 Stacktrace: [1] centralize_sumabs2!(R::Matrix{Float64}, A::Matrix{Float64}, means::Matrix{Float64}) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:282 [2] varm!(R::Matrix{Float64}, A::Matrix{Float64}, m::Matrix{Float64}; corrected::Bool) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:309 [3] _varm(A::Matrix{Float64}, m::Matrix{Float64}, corrected::Bool, region::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:341 [4] varm(A::Matrix{Float64}, m::Matrix{Float64}; corrected::Bool, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:339 [inlined] [5] _var(A::Matrix{Float64}, corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:386 [inlined] [6] var(A::Matrix{Float64}; corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:380 [inlined] [7] output_result(mme::JWAS.MME, output_folder::String, solMean::Vector{Float64}, meanVare::Matrix{Float64}, G0Mean::Bool, solMean2::Vector{Float64}, meanVare2::Matrix{Float64}, G0Mean2::Bool) @ JWAS ~/.julia/packages/JWAS/AxFc6/src/1.JWAS/src/output.jl:199 [8] MCMC_BayesianAlphabet(mme::JWAS.MME, df::DataFrame) @ JWAS ~/.julia/packages/JWAS/AxFc6/src/1.JWAS/src/MCMC/MCMC_BayesianAlphabet.jl:446 [9] runMCMC(mme::JWAS.MME, df::DataFrame; heterogeneous_residuals::Bool, chain_length::Int64, starting_value::Bool, burnin::Int64, output_samples_frequency::Int64, update_priors_frequency::Int64, single_step_analysis::Bool, pedigree::Bool, fitting_J_vector::Bool, causal_structure::Bool, missing_phenotypes::Bool, RRM::Bool, outputEBV::Bool, output_heritability::Bool, prediction_equation::Bool, seed::Int64, printout_model_info::Bool, printout_frequency::Int64, big_memory::Bool, double_precision::Bool, fast_blocks::Bool, independent_blocks::Bool, memory_guard::Symbol, memory_guard_ratio::Float64, output_folder::String, output_samples_for_all_parameters::Bool, methods::String, Pi::Float64, estimatePi::Bool, estimate_scale::Bool, estimate_variance::Bool, categorical_trait::Bool, censored_trait::Bool) @ JWAS ~/.julia/packages/JWAS/AxFc6/src/1.JWAS/src/JWAS.jl:466 [10] top-level scope @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_multitrait_mcmc.jl:258 [11] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [12] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_multitrait_mcmc.jl:291 [inlined] The delimiter in genotypes.txt is ','. The header (marker IDs) is provided in genotypes.txt. Genotype informatin: #markers: 5; #individuals: 7 The folder test_mt_bayesc_dense_sampler2 is created to save results. Checking genotypes... Checking phenotypes... Individual IDs (strings) are provided in the first column of the phenotypic data. In this complete genomic data (non-single-step) analyis, 1 phenotyped individuals are not genotyped. These are removed from the analysis. Predicted values for individuals of interest will be obtained as the summation of Any[] (Note that genomic data is always included for now).Phenotypes for 4 observations are used in the analysis.These individual IDs are saved in the file test_mt_bayesc_dense_sampler2/IDs_for_individuals_with_phenotypes.txt. Pi (Π) is not provided. Pi (Π) is generated assuming all markers have effects on all traits. The prior for marker effects covariance matrix is calculated from genetic covariance matrix and Π. The mean of the prior for the marker effects covariance matrix is: 0.492462 0.246231 0.246231 0.492462 A Linear Mixed Model was build using model equations: y1 = intercept + plain_mt_dense_sampler2 y2 = intercept + plain_mt_dense_sampler2 Model Information: Term C/F F/R nLevels intercept factor fixed 1 MCMC Information: chain_length 40 burnin 10 starting_value true printout_frequency 41 output_samples_frequency 10 constraint on residual variance false constraint on marker effect variance for plain_mt_dense_sampler2 false missing_phenotypes true update_priors_frequency 0 seed 123 Hyper-parameters Information: residual variances: 1.0f0 0.5f0 0.5f0 1.0f0 Genomic Information: complete genomic data (i.e., non-single-step analysis) Genomic Category plain_mt_dense_sampler2 Method BayesC genetic variances (genomic): 1.0 0.5 0.5 1.0 marker effect variances: 0.492 0.246 0.246 0.492 Π: (Y(yes):included; N(no):excluded) ["y1", "y2"] probability ["N", "Y"] 0.0 ["N", "N"] 0.0 ["Y", "Y"] 1.0 ["Y", "N"] 0.0 estimatePi true estimate_scale false Degree of freedom for hyper-parameters: residual variances: 6.000 marker effect variances: 6.000 The file test_mt_bayesc_dense_sampler2/MCMC_samples_residual_variance.txt is created to save MCMC samples for residual_variance. The file test_mt_bayesc_dense_sampler2/MCMC_samples_marker_effects_plain_mt_dense_sampler2_y1.txt is created to save MCMC samples for marker_effects_plain_mt_dense_sampler2_y1. The file test_mt_bayesc_dense_sampler2/MCMC_samples_marker_effects_plain_mt_dense_sampler2_y2.txt is created to save MCMC samples for marker_effects_plain_mt_dense_sampler2_y2. The file test_mt_bayesc_dense_sampler2/MCMC_samples_marker_effects_variances_plain_mt_dense_sampler2.txt is created to save MCMC samples for marker_effects_variances_plain_mt_dense_sampler2. The file test_mt_bayesc_dense_sampler2/MCMC_samples_pi_plain_mt_dense_sampler2.txt is created to save MCMC samples for pi_plain_mt_dense_sampler2. The file test_mt_bayesc_dense_sampler2/MCMC_samples_EBV_y1.txt is created to save MCMC samples for EBV_y1. The file test_mt_bayesc_dense_sampler2/MCMC_samples_EBV_y2.txt is created to save MCMC samples for EBV_y2. The file test_mt_bayesc_dense_sampler2/MCMC_samples_genetic_variance.txt is created to save MCMC samples for genetic_variance. The file test_mt_bayesc_dense_sampler2/MCMC_samples_heritability.txt is created to save MCMC samples for heritability. running MCMC ... 5%|█▊ | ETA: 0:02:12 running MCMC ... 100%|███████████████████████████████████| Time: 0:00:06 Multi-trait BayesC dense sampler II run: Error During Test at /home/pkgeval/.julia/packages/JWAS/AxFc6/test/unit/test_multitrait_mcmc.jl:306 Got exception outside of a @test MethodError: no method matching reducedim1(::Matrix{Float64}, ::Matrix{Float64}) The function `reducedim1` exists, but no method is defined for this combination of argument types. Closest candidates are: reducedim1(::Any) @ Base reducedim.jl:1229 Stacktrace: [1] centralize_sumabs2!(R::Matrix{Float64}, A::Matrix{Float64}, means::Matrix{Float64}) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:282 [2] varm!(R::Matrix{Float64}, A::Matrix{Float64}, m::Matrix{Float64}; corrected::Bool) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:309 [3] _varm(A::Matrix{Float64}, m::Matrix{Float64}, corrected::Bool, region::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:341 [4] varm(A::Matrix{Float64}, m::Matrix{Float64}; corrected::Bool, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:339 [inlined] [5] _var(A::Matrix{Float64}, corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:386 [inlined] [6] var(A::Matrix{Float64}; corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:380 [inlined] [7] output_result(mme::JWAS.MME, output_folder::String, solMean::Vector{Float64}, meanVare::Matrix{Float64}, G0Mean::Bool, solMean2::Vector{Float64}, meanVare2::Matrix{Float64}, G0Mean2::Bool) @ JWAS ~/.julia/packages/JWAS/AxFc6/src/1.JWAS/src/output.jl:199 [8] MCMC_BayesianAlphabet(mme::JWAS.MME, df::DataFrame) @ JWAS ~/.julia/packages/JWAS/AxFc6/src/1.JWAS/src/MCMC/MCMC_BayesianAlphabet.jl:446 [9] runMCMC(mme::JWAS.MME, df::DataFrame; heterogeneous_residuals::Bool, chain_length::Int64, starting_value::Bool, burnin::Int64, output_samples_frequency::Int64, update_priors_frequency::Int64, single_step_analysis::Bool, pedigree::Bool, fitting_J_vector::Bool, causal_structure::Bool, missing_phenotypes::Bool, RRM::Bool, outputEBV::Bool, output_heritability::Bool, prediction_equation::Bool, seed::Int64, printout_model_info::Bool, printout_frequency::Int64, big_memory::Bool, double_precision::Bool, fast_blocks::Bool, independent_blocks::Bool, memory_guard::Symbol, memory_guard_ratio::Float64, output_folder::String, output_samples_for_all_parameters::Bool, methods::String, Pi::Float64, estimatePi::Bool, estimate_scale::Bool, estimate_variance::Bool, categorical_trait::Bool, censored_trait::Bool) @ JWAS ~/.julia/packages/JWAS/AxFc6/src/1.JWAS/src/JWAS.jl:466 [10] top-level scope @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_multitrait_mcmc.jl:307 [11] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [12] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_multitrait_mcmc.jl:319 [inlined] The delimiter in genotypes.txt is ','. The header (marker IDs) is provided in genotypes.txt. Genotype informatin: #markers: 5; #individuals: 7 The folder test_mt_bayesc_fastblocks is created to save results. Checking genotypes... Checking phenotypes... Individual IDs (strings) are provided in the first column of the phenotypic data. In this complete genomic data (non-single-step) analyis, 1 phenotyped individuals are not genotyped. These are removed from the analysis. Predicted values for individuals of interest will be obtained as the summation of Any[] (Note that genomic data is always included for now).Phenotypes for 4 observations are used in the analysis.These individual IDs are saved in the file test_mt_bayesc_fastblocks/IDs_for_individuals_with_phenotypes.txt. Pi (Π) is not provided. Pi (Π) is generated assuming all markers have effects on all traits. The prior for marker effects covariance matrix is calculated from genetic covariance matrix and Π. The mean of the prior for the marker effects covariance matrix is: 0.492462 0.246231 0.246231 0.492462 BLOCK SIZE: 2 A Linear Mixed Model was build using model equations: y1 = intercept + plain_mt_fastblocks y2 = intercept + plain_mt_fastblocks Model Information: Term C/F F/R nLevels intercept factor fixed 1 MCMC Information: chain_length 20 burnin 10 starting_value true printout_frequency 41 output_samples_frequency 10 constraint on residual variance false constraint on marker effect variance for plain_mt_fastblocks false missing_phenotypes true update_priors_frequency 0 seed 123 Hyper-parameters Information: residual variances: 1.0f0 0.5f0 0.5f0 1.0f0 Genomic Information: complete genomic data (i.e., non-single-step analysis) Genomic Category plain_mt_fastblocks Method BayesC genetic variances (genomic): 1.0 0.5 0.5 1.0 marker effect variances: 0.492 0.246 0.246 0.492 Π: (Y(yes):included; N(no):excluded) ["y1", "y2"] probability ["N", "Y"] 0.0 ["N", "N"] 0.0 ["Y", "Y"] 1.0 ["Y", "N"] 0.0 estimatePi true estimate_scale false Degree of freedom for hyper-parameters: residual variances: 6.000 marker effect variances: 6.000 The file test_mt_bayesc_fastblocks/MCMC_samples_residual_variance.txt is created to save MCMC samples for residual_variance. The file test_mt_bayesc_fastblocks/MCMC_samples_marker_effects_plain_mt_fastblocks_y1.txt is created to save MCMC samples for marker_effects_plain_mt_fastblocks_y1. The file test_mt_bayesc_fastblocks/MCMC_samples_marker_effects_plain_mt_fastblocks_y2.txt is created to save MCMC samples for marker_effects_plain_mt_fastblocks_y2. The file test_mt_bayesc_fastblocks/MCMC_samples_marker_effects_variances_plain_mt_fastblocks.txt is created to save MCMC samples for marker_effects_variances_plain_mt_fastblocks. The file test_mt_bayesc_fastblocks/MCMC_samples_pi_plain_mt_fastblocks.txt is created to save MCMC samples for pi_plain_mt_fastblocks. The file test_mt_bayesc_fastblocks/MCMC_samples_EBV_y1.txt is created to save MCMC samples for EBV_y1. The file test_mt_bayesc_fastblocks/MCMC_samples_EBV_y2.txt is created to save MCMC samples for EBV_y2. The file test_mt_bayesc_fastblocks/MCMC_samples_genetic_variance.txt is created to save MCMC samples for genetic_variance. The file test_mt_bayesc_fastblocks/MCMC_samples_heritability.txt is created to save MCMC samples for heritability. running MCMC ... 10%|███▌ | ETA: 0:01:28 running MCMC ... 100%|███████████████████████████████████| Time: 0:00:09 Multi-trait BayesC fast_blocks run: Error During Test at /home/pkgeval/.julia/packages/JWAS/AxFc6/test/unit/test_multitrait_mcmc.jl:334 Got exception outside of a @test MethodError: no method matching reducedim1(::Matrix{Float64}, ::Matrix{Float64}) The function `reducedim1` exists, but no method is defined for this combination of argument types. Closest candidates are: reducedim1(::Any) @ Base reducedim.jl:1229 Stacktrace: [1] centralize_sumabs2!(R::Matrix{Float64}, A::Matrix{Float64}, means::Matrix{Float64}) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:282 [2] varm!(R::Matrix{Float64}, A::Matrix{Float64}, m::Matrix{Float64}; corrected::Bool) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:309 [3] _varm(A::Matrix{Float64}, m::Matrix{Float64}, corrected::Bool, region::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:341 [4] varm(A::Matrix{Float64}, m::Matrix{Float64}; corrected::Bool, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:339 [inlined] [5] _var(A::Matrix{Float64}, corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:386 [inlined] [6] var(A::Matrix{Float64}; corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:380 [inlined] [7] output_result(mme::JWAS.MME, output_folder::String, solMean::Vector{Float64}, meanVare::Matrix{Float64}, G0Mean::Bool, solMean2::Vector{Float64}, meanVare2::Matrix{Float64}, G0Mean2::Bool) @ JWAS ~/.julia/packages/JWAS/AxFc6/src/1.JWAS/src/output.jl:199 [8] MCMC_BayesianAlphabet(mme::JWAS.MME, df::DataFrame) @ JWAS ~/.julia/packages/JWAS/AxFc6/src/1.JWAS/src/MCMC/MCMC_BayesianAlphabet.jl:446 [9] runMCMC(mme::JWAS.MME, df::DataFrame; heterogeneous_residuals::Bool, chain_length::Int64, starting_value::Bool, burnin::Int64, output_samples_frequency::Int64, update_priors_frequency::Int64, single_step_analysis::Bool, pedigree::Bool, fitting_J_vector::Bool, causal_structure::Bool, missing_phenotypes::Bool, RRM::Bool, outputEBV::Bool, output_heritability::Bool, prediction_equation::Bool, seed::Int64, printout_model_info::Bool, printout_frequency::Int64, big_memory::Bool, double_precision::Bool, fast_blocks::Bool, independent_blocks::Bool, memory_guard::Symbol, memory_guard_ratio::Float64, output_folder::String, output_samples_for_all_parameters::Bool, methods::String, Pi::Float64, estimatePi::Bool, estimate_scale::Bool, estimate_variance::Bool, categorical_trait::Bool, censored_trait::Bool) @ JWAS ~/.julia/packages/JWAS/AxFc6/src/1.JWAS/src/JWAS.jl:466 [10] top-level scope @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_multitrait_mcmc.jl:335 [11] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [12] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_multitrait_mcmc.jl:346 [inlined] The delimiter in genotypes.txt is ','. The header (marker IDs) is provided in genotypes.txt. Genotype informatin: #markers: 5; #individuals: 7 The folder test_mt_bayesc_fastblocks_sampler2 is created to save results. Checking genotypes... Checking phenotypes... Individual IDs (strings) are provided in the first column of the phenotypic data. In this complete genomic data (non-single-step) analyis, 1 phenotyped individuals are not genotyped. These are removed from the analysis. Predicted values for individuals of interest will be obtained as the summation of Any[] (Note that genomic data is always included for now).Phenotypes for 4 observations are used in the analysis.These individual IDs are saved in the file test_mt_bayesc_fastblocks_sampler2/IDs_for_individuals_with_phenotypes.txt. Pi (Π) is not provided. Pi (Π) is generated assuming all markers have effects on all traits. The prior for marker effects covariance matrix is calculated from genetic covariance matrix and Π. The mean of the prior for the marker effects covariance matrix is: 0.492462 0.246231 0.246231 0.492462 BLOCK SIZE: 2 A Linear Mixed Model was build using model equations: y1 = intercept + plain_mt_fastblocks_sampler2 y2 = intercept + plain_mt_fastblocks_sampler2 Model Information: Term C/F F/R nLevels intercept factor fixed 1 MCMC Information: chain_length 20 burnin 10 starting_value true printout_frequency 41 output_samples_frequency 10 constraint on residual variance false constraint on marker effect variance for plain_mt_fastblocks_sampler2 false missing_phenotypes true update_priors_frequency 0 seed 123 Hyper-parameters Information: residual variances: 1.0f0 0.5f0 0.5f0 1.0f0 Genomic Information: complete genomic data (i.e., non-single-step analysis) Genomic Category plain_mt_fastblocks_sampler2 Method BayesC genetic variances (genomic): 1.0 0.5 0.5 1.0 marker effect variances: 0.492 0.246 0.246 0.492 Π: (Y(yes):included; N(no):excluded) ["y1", "y2"] probability ["N", "Y"] 0.0 ["N", "N"] 0.0 ["Y", "Y"] 1.0 ["Y", "N"] 0.0 estimatePi true estimate_scale false Degree of freedom for hyper-parameters: residual variances: 6.000 marker effect variances: 6.000 The file test_mt_bayesc_fastblocks_sampler2/MCMC_samples_residual_variance.txt is created to save MCMC samples for residual_variance. The file test_mt_bayesc_fastblocks_sampler2/MCMC_samples_marker_effects_plain_mt_fastblocks_sampler2_y1.txt is created to save MCMC samples for marker_effects_plain_mt_fastblocks_sampler2_y1. The file test_mt_bayesc_fastblocks_sampler2/MCMC_samples_marker_effects_plain_mt_fastblocks_sampler2_y2.txt is created to save MCMC samples for marker_effects_plain_mt_fastblocks_sampler2_y2. The file test_mt_bayesc_fastblocks_sampler2/MCMC_samples_marker_effects_variances_plain_mt_fastblocks_sampler2.txt is created to save MCMC samples for marker_effects_variances_plain_mt_fastblocks_sampler2. The file test_mt_bayesc_fastblocks_sampler2/MCMC_samples_pi_plain_mt_fastblocks_sampler2.txt is created to save MCMC samples for pi_plain_mt_fastblocks_sampler2. The file test_mt_bayesc_fastblocks_sampler2/MCMC_samples_EBV_y1.txt is created to save MCMC samples for EBV_y1. The file test_mt_bayesc_fastblocks_sampler2/MCMC_samples_EBV_y2.txt is created to save MCMC samples for EBV_y2. The file test_mt_bayesc_fastblocks_sampler2/MCMC_samples_genetic_variance.txt is created to save MCMC samples for genetic_variance. The file test_mt_bayesc_fastblocks_sampler2/MCMC_samples_heritability.txt is created to save MCMC samples for heritability. running MCMC ... 10%|███▌ | ETA: 0:01:08 running MCMC ... 100%|███████████████████████████████████| Time: 0:00:07 Multi-trait BayesC fast_blocks sampler II run: Error During Test at /home/pkgeval/.julia/packages/JWAS/AxFc6/test/unit/test_multitrait_mcmc.jl:362 Got exception outside of a @test MethodError: no method matching reducedim1(::Matrix{Float64}, ::Matrix{Float64}) The function `reducedim1` exists, but no method is defined for this combination of argument types. Closest candidates are: reducedim1(::Any) @ Base reducedim.jl:1229 Stacktrace: [1] centralize_sumabs2!(R::Matrix{Float64}, A::Matrix{Float64}, means::Matrix{Float64}) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:282 [2] varm!(R::Matrix{Float64}, A::Matrix{Float64}, m::Matrix{Float64}; corrected::Bool) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:309 [3] _varm(A::Matrix{Float64}, m::Matrix{Float64}, corrected::Bool, region::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:341 [4] varm(A::Matrix{Float64}, m::Matrix{Float64}; corrected::Bool, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:339 [inlined] [5] _var(A::Matrix{Float64}, corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:386 [inlined] [6] var(A::Matrix{Float64}; corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:380 [inlined] [7] output_result(mme::JWAS.MME, output_folder::String, solMean::Vector{Float64}, meanVare::Matrix{Float64}, G0Mean::Bool, solMean2::Vector{Float64}, meanVare2::Matrix{Float64}, G0Mean2::Bool) @ JWAS ~/.julia/packages/JWAS/AxFc6/src/1.JWAS/src/output.jl:199 [8] MCMC_BayesianAlphabet(mme::JWAS.MME, df::DataFrame) @ JWAS ~/.julia/packages/JWAS/AxFc6/src/1.JWAS/src/MCMC/MCMC_BayesianAlphabet.jl:446 [9] runMCMC(mme::JWAS.MME, df::DataFrame; heterogeneous_residuals::Bool, chain_length::Int64, starting_value::Bool, burnin::Int64, output_samples_frequency::Int64, update_priors_frequency::Int64, single_step_analysis::Bool, pedigree::Bool, fitting_J_vector::Bool, causal_structure::Bool, missing_phenotypes::Bool, RRM::Bool, outputEBV::Bool, output_heritability::Bool, prediction_equation::Bool, seed::Int64, printout_model_info::Bool, printout_frequency::Int64, big_memory::Bool, double_precision::Bool, fast_blocks::Bool, independent_blocks::Bool, memory_guard::Symbol, memory_guard_ratio::Float64, output_folder::String, output_samples_for_all_parameters::Bool, methods::String, Pi::Float64, estimatePi::Bool, estimate_scale::Bool, estimate_variance::Bool, categorical_trait::Bool, censored_trait::Bool) @ JWAS ~/.julia/packages/JWAS/AxFc6/src/1.JWAS/src/JWAS.jl:466 [10] top-level scope @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_multitrait_mcmc.jl:363 [11] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [12] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_multitrait_mcmc.jl:375 [inlined] The delimiter in genotypes.txt is ','. The header (marker IDs) is provided in genotypes.txt. Genotype informatin: #markers: 5; #individuals: 7 The folder test_mt_annotated_bayesc_fastblocks_sampler2 is created to save results. Checking genotypes... Checking phenotypes... Individual IDs (strings) are provided in the first column of the phenotypic data. In this complete genomic data (non-single-step) analyis, 1 phenotyped individuals are not genotyped. These are removed from the analysis. Predicted values for individuals of interest will be obtained as the summation of Any[] (Note that genomic data is always included for now).Phenotypes for 7 observations are used in the analysis.These individual IDs are saved in the file test_mt_annotated_bayesc_fastblocks_sampler2/IDs_for_individuals_with_phenotypes.txt. The prior for marker effects covariance matrix is calculated from genetic covariance matrix and Π. The mean of the prior for the marker effects covariance matrix is: 1.231156 1.231156 1.231156 1.407035 BLOCK SIZE: 2 A Linear Mixed Model was build using model equations: y1 = intercept + annotated_mt_fastblocks_sampler2 y2 = intercept + annotated_mt_fastblocks_sampler2 Model Information: Term C/F F/R nLevels intercept factor fixed 1 MCMC Information: chain_length 20 burnin 10 starting_value true printout_frequency 41 output_samples_frequency 10 constraint on residual variance false constraint on marker effect variance for annotated_mt_fastblocks_sampler2 false missing_phenotypes true update_priors_frequency 0 seed 123 Hyper-parameters Information: residual variances: 1.0f0 0.5f0 0.5f0 1.0f0 Genomic Information: complete genomic data (i.e., non-single-step analysis) Genomic Category annotated_mt_fastblocks_sampler2 Method BayesC genetic variances (genomic): 1.0 0.5 0.5 1.0 marker effect variances: 1.231 1.231 1.231 1.407 Π: (Y(yes):included; N(no):excluded) ["y1", "y2"] probability ["N", "Y"] 0.15 ["N", "N"] 0.45 ["Y", "Y"] 0.2 ["Y", "N"] 0.2 estimatePi true estimate_scale false Degree of freedom for hyper-parameters: residual variances: 6.000 marker effect variances: 6.000 The file test_mt_annotated_bayesc_fastblocks_sampler2/MCMC_samples_residual_variance.txt is created to save MCMC samples for residual_variance. The file test_mt_annotated_bayesc_fastblocks_sampler2/MCMC_samples_marker_effects_annotated_mt_fastblocks_sampler2_y1.txt is created to save MCMC samples for marker_effects_annotated_mt_fastblocks_sampler2_y1. The file test_mt_annotated_bayesc_fastblocks_sampler2/MCMC_samples_marker_effects_annotated_mt_fastblocks_sampler2_y2.txt is created to save MCMC samples for marker_effects_annotated_mt_fastblocks_sampler2_y2. The file test_mt_annotated_bayesc_fastblocks_sampler2/MCMC_samples_marker_effects_variances_annotated_mt_fastblocks_sampler2.txt is created to save MCMC samples for marker_effects_variances_annotated_mt_fastblocks_sampler2. The file test_mt_annotated_bayesc_fastblocks_sampler2/MCMC_samples_pi_annotated_mt_fastblocks_sampler2.txt is created to save MCMC samples for pi_annotated_mt_fastblocks_sampler2. The file test_mt_annotated_bayesc_fastblocks_sampler2/MCMC_samples_EBV_y1.txt is created to save MCMC samples for EBV_y1. The file test_mt_annotated_bayesc_fastblocks_sampler2/MCMC_samples_EBV_y2.txt is created to save MCMC samples for EBV_y2. The file test_mt_annotated_bayesc_fastblocks_sampler2/MCMC_samples_genetic_variance.txt is created to save MCMC samples for genetic_variance. The file test_mt_annotated_bayesc_fastblocks_sampler2/MCMC_samples_heritability.txt is created to save MCMC samples for heritability. running MCMC ... 10%|███▌ | ETA: 0:01:03 running MCMC ... 100%|███████████████████████████████████| Time: 0:00:07 Multi-trait annotated BayesC fast_blocks sampler II run: Error During Test at /home/pkgeval/.julia/packages/JWAS/AxFc6/test/unit/test_multitrait_mcmc.jl:391 Got exception outside of a @test MethodError: no method matching reducedim1(::Matrix{Float64}, ::Matrix{Float64}) The function `reducedim1` exists, but no method is defined for this combination of argument types. Closest candidates are: reducedim1(::Any) @ Base reducedim.jl:1229 Stacktrace: [1] centralize_sumabs2!(R::Matrix{Float64}, A::Matrix{Float64}, means::Matrix{Float64}) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:282 [2] varm!(R::Matrix{Float64}, A::Matrix{Float64}, m::Matrix{Float64}; corrected::Bool) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:309 [3] _varm(A::Matrix{Float64}, m::Matrix{Float64}, corrected::Bool, region::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:341 [4] varm(A::Matrix{Float64}, m::Matrix{Float64}; corrected::Bool, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:339 [inlined] [5] _var(A::Matrix{Float64}, corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:386 [inlined] [6] var(A::Matrix{Float64}; corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:380 [inlined] [7] output_result(mme::JWAS.MME, output_folder::String, solMean::Vector{Float64}, meanVare::Matrix{Float64}, G0Mean::Bool, solMean2::Vector{Float64}, meanVare2::Matrix{Float64}, G0Mean2::Bool) @ JWAS ~/.julia/packages/JWAS/AxFc6/src/1.JWAS/src/output.jl:199 [8] MCMC_BayesianAlphabet(mme::JWAS.MME, df::DataFrame) @ JWAS ~/.julia/packages/JWAS/AxFc6/src/1.JWAS/src/MCMC/MCMC_BayesianAlphabet.jl:446 [9] runMCMC(mme::JWAS.MME, df::DataFrame; heterogeneous_residuals::Bool, chain_length::Int64, starting_value::Bool, burnin::Int64, output_samples_frequency::Int64, update_priors_frequency::Int64, single_step_analysis::Bool, pedigree::Bool, fitting_J_vector::Bool, causal_structure::Bool, missing_phenotypes::Bool, RRM::Bool, outputEBV::Bool, output_heritability::Bool, prediction_equation::Bool, seed::Int64, printout_model_info::Bool, printout_frequency::Int64, big_memory::Bool, double_precision::Bool, fast_blocks::Bool, independent_blocks::Bool, memory_guard::Symbol, memory_guard_ratio::Float64, output_folder::String, output_samples_for_all_parameters::Bool, methods::String, Pi::Float64, estimatePi::Bool, estimate_scale::Bool, estimate_variance::Bool, categorical_trait::Bool, censored_trait::Bool) @ JWAS ~/.julia/packages/JWAS/AxFc6/src/1.JWAS/src/JWAS.jl:466 [10] top-level scope @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_multitrait_mcmc.jl:392 [11] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [12] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_multitrait_mcmc.jl:424 [inlined] The delimiter in genotypes.txt is ','. The header (marker IDs) is provided in genotypes.txt. Genotype informatin: #markers: 5; #individuals: 7 The folder test_mt_bayesc_independent_sampler1 is created to save results. Checking genotypes... Checking phenotypes... Individual IDs (strings) are provided in the first column of the phenotypic data. In this complete genomic data (non-single-step) analyis, 1 phenotyped individuals are not genotyped. These are removed from the analysis. Predicted values for individuals of interest will be obtained as the summation of Any[] (Note that genomic data is always included for now).Phenotypes for 4 observations are used in the analysis.These individual IDs are saved in the file test_mt_bayesc_independent_sampler1/IDs_for_individuals_with_phenotypes.txt. Pi (Π) is not provided. Pi (Π) is generated assuming all markers have effects on all traits. The prior for marker effects covariance matrix is calculated from genetic covariance matrix and Π. The mean of the prior for the marker effects covariance matrix is: 0.492462 0.246231 0.246231 0.492462 BLOCK STARTS: [1, 3, 5] A Linear Mixed Model was build using model equations: y1 = intercept + plain_mt_independent_sampler1 y2 = intercept + plain_mt_independent_sampler1 Model Information: Term C/F F/R nLevels intercept factor fixed 1 MCMC Information: chain_length 12 burnin 2 starting_value true printout_frequency 13 output_samples_frequency 10 constraint on residual variance false constraint on marker effect variance for plain_mt_independent_sampler1 false missing_phenotypes true update_priors_frequency 0 seed 123 Hyper-parameters Information: residual variances: 1.0f0 0.5f0 0.5f0 1.0f0 Genomic Information: complete genomic data (i.e., non-single-step analysis) Genomic Category plain_mt_independent_sampler1 Method BayesC genetic variances (genomic): 1.0 0.5 0.5 1.0 marker effect variances: 0.492 0.246 0.246 0.492 Π: (Y(yes):included; N(no):excluded) ["y1", "y2"] probability ["N", "Y"] 0.0 ["N", "N"] 0.0 ["Y", "Y"] 1.0 ["Y", "N"] 0.0 estimatePi true estimate_scale false Degree of freedom for hyper-parameters: residual variances: 6.000 marker effect variances: 6.000 The file test_mt_bayesc_independent_sampler1/MCMC_samples_residual_variance.txt is created to save MCMC samples for residual_variance. The file test_mt_bayesc_independent_sampler1/MCMC_samples_marker_effects_plain_mt_independent_sampler1_y1.txt is created to save MCMC samples for marker_effects_plain_mt_independent_sampler1_y1. The file test_mt_bayesc_independent_sampler1/MCMC_samples_marker_effects_plain_mt_independent_sampler1_y2.txt is created to save MCMC samples for marker_effects_plain_mt_independent_sampler1_y2. The file test_mt_bayesc_independent_sampler1/MCMC_samples_marker_effects_variances_plain_mt_independent_sampler1.txt is created to save MCMC samples for marker_effects_variances_plain_mt_independent_sampler1. The file test_mt_bayesc_independent_sampler1/MCMC_samples_pi_plain_mt_independent_sampler1.txt is created to save MCMC samples for pi_plain_mt_independent_sampler1. running MCMC ... 17%|█████▉ | ETA: 0:00:55 running MCMC ... 100%|███████████████████████████████████| Time: 0:00:10 The version of Julia and Platform in use: Julia Version 1.14.0-DEV.3055 Build Info: Commit 7e75a8061a* (2026-08-27 09:46 UTC) GC: Built with stock GC Platform Info: OS: Linux (x86_64-unknown-linux-gnu) CPU: 128 × AMD EPYC 7502 32-Core Processor (znver2) WORD_SIZE: 64 LLVM: libLLVM-22.1.8 (ORCJIT, znver2) Threads: 1 default, 0 interactive, 1 GC (on 1 virtual cores) Environment: JULIA_CPU_THREADS = 1 JULIA_NUM_PRECOMPILE_TASKS = 1 JULIA_PKG_PRECOMPILE_AUTO = 0 JULIA_PKGEVAL = true JULIA_DEPOT_PATH = /home/pkgeval/.julia:/usr/local/share/julia: JULIA_NUM_THREADS = 1 JULIA_LOAD_PATH = @:/tmp/jl_g0vHag The analysis has finished. Results are saved in the returned variable and text files. MCMC samples are saved in text files. The delimiter in genotypes.txt is ','. The header (marker IDs) is provided in genotypes.txt. Genotype informatin: #markers: 5; #individuals: 7 The folder test_mt_bayesc_independent_sampler2 is created to save results. Checking genotypes... Checking phenotypes... Individual IDs (strings) are provided in the first column of the phenotypic data. In this complete genomic data (non-single-step) analyis, 1 phenotyped individuals are not genotyped. These are removed from the analysis. Predicted values for individuals of interest will be obtained as the summation of Any[] (Note that genomic data is always included for now).Phenotypes for 4 observations are used in the analysis.These individual IDs are saved in the file test_mt_bayesc_independent_sampler2/IDs_for_individuals_with_phenotypes.txt. Pi (Π) is not provided. Pi (Π) is generated assuming all markers have effects on all traits. The prior for marker effects covariance matrix is calculated from genetic covariance matrix and Π. The mean of the prior for the marker effects covariance matrix is: 0.492462 0.246231 0.246231 0.492462 BLOCK STARTS: [1, 3, 5] A Linear Mixed Model was build using model equations: y1 = intercept + plain_mt_independent_sampler2 y2 = intercept + plain_mt_independent_sampler2 Model Information: Term C/F F/R nLevels intercept factor fixed 1 MCMC Information: chain_length 12 burnin 2 starting_value true printout_frequency 13 output_samples_frequency 10 constraint on residual variance false constraint on marker effect variance for plain_mt_independent_sampler2 false missing_phenotypes true update_priors_frequency 0 seed 123 Hyper-parameters Information: residual variances: 1.0f0 0.5f0 0.5f0 1.0f0 Genomic Information: complete genomic data (i.e., non-single-step analysis) Genomic Category plain_mt_independent_sampler2 Method BayesC genetic variances (genomic): 1.0 0.5 0.5 1.0 marker effect variances: 0.492 0.246 0.246 0.492 Π: (Y(yes):included; N(no):excluded) ["y1", "y2"] probability ["N", "Y"] 0.0 ["N", "N"] 0.0 ["Y", "Y"] 1.0 ["Y", "N"] 0.0 estimatePi true estimate_scale false Degree of freedom for hyper-parameters: residual variances: 6.000 marker effect variances: 6.000 The file test_mt_bayesc_independent_sampler2/MCMC_samples_residual_variance.txt is created to save MCMC samples for residual_variance. The file test_mt_bayesc_independent_sampler2/MCMC_samples_marker_effects_plain_mt_independent_sampler2_y1.txt is created to save MCMC samples for marker_effects_plain_mt_independent_sampler2_y1. The file test_mt_bayesc_independent_sampler2/MCMC_samples_marker_effects_plain_mt_independent_sampler2_y2.txt is created to save MCMC samples for marker_effects_plain_mt_independent_sampler2_y2. The file test_mt_bayesc_independent_sampler2/MCMC_samples_marker_effects_variances_plain_mt_independent_sampler2.txt is created to save MCMC samples for marker_effects_variances_plain_mt_independent_sampler2. The file test_mt_bayesc_independent_sampler2/MCMC_samples_pi_plain_mt_independent_sampler2.txt is created to save MCMC samples for pi_plain_mt_independent_sampler2. running MCMC ... 17%|█████▉ | ETA: 0:00:44 running MCMC ... 100%|███████████████████████████████████| Time: 0:00:08 The version of Julia and Platform in use: Julia Version 1.14.0-DEV.3055 Build Info: Commit 7e75a8061a* (2026-08-27 09:46 UTC) GC: Built with stock GC Platform Info: OS: Linux (x86_64-unknown-linux-gnu) CPU: 128 × AMD EPYC 7502 32-Core Processor (znver2) WORD_SIZE: 64 LLVM: libLLVM-22.1.8 (ORCJIT, znver2) Threads: 1 default, 0 interactive, 1 GC (on 1 virtual cores) Environment: JULIA_CPU_THREADS = 1 JULIA_NUM_PRECOMPILE_TASKS = 1 JULIA_PKG_PRECOMPILE_AUTO = 0 JULIA_PKGEVAL = true JULIA_DEPOT_PATH = /home/pkgeval/.julia:/usr/local/share/julia: JULIA_NUM_THREADS = 1 JULIA_LOAD_PATH = @:/tmp/jl_g0vHag The analysis has finished. Results are saved in the returned variable and text files. MCMC samples are saved in text files. The delimiter in genotypes.txt is ','. The header (marker IDs) is provided in genotypes.txt. Genotype informatin: #markers: 5; #individuals: 7 The folder test_mt_annotated_bayesc_independent_sampler1 is created to save results. Checking genotypes... Checking phenotypes... Individual IDs (strings) are provided in the first column of the phenotypic data. In this complete genomic data (non-single-step) analyis, 1 phenotyped individuals are not genotyped. These are removed from the analysis. Predicted values for individuals of interest will be obtained as the summation of Any[] (Note that genomic data is always included for now).Phenotypes for 7 observations are used in the analysis.These individual IDs are saved in the file test_mt_annotated_bayesc_independent_sampler1/IDs_for_individuals_with_phenotypes.txt. The prior for marker effects covariance matrix is calculated from genetic covariance matrix and Π. The mean of the prior for the marker effects covariance matrix is: 1.231156 1.231156 1.231156 1.407035 BLOCK STARTS: [1, 3, 5] A Linear Mixed Model was build using model equations: y1 = intercept + annotated_mt_independent_sampler1 y2 = intercept + annotated_mt_independent_sampler1 Model Information: Term C/F F/R nLevels intercept factor fixed 1 MCMC Information: chain_length 12 burnin 2 starting_value true printout_frequency 13 output_samples_frequency 10 constraint on residual variance false constraint on marker effect variance for annotated_mt_independent_sampler1 false missing_phenotypes true update_priors_frequency 0 seed 123 Hyper-parameters Information: residual variances: 1.0f0 0.5f0 0.5f0 1.0f0 Genomic Information: complete genomic data (i.e., non-single-step analysis) Genomic Category annotated_mt_independent_sampler1 Method BayesC genetic variances (genomic): 1.0 0.5 0.5 1.0 marker effect variances: 1.231 1.231 1.231 1.407 Π: (Y(yes):included; N(no):excluded) ["y1", "y2"] probability ["N", "Y"] 0.15 ["N", "N"] 0.45 ["Y", "Y"] 0.2 ["Y", "N"] 0.2 estimatePi true estimate_scale false Degree of freedom for hyper-parameters: residual variances: 6.000 marker effect variances: 6.000 The file test_mt_annotated_bayesc_independent_sampler1/MCMC_samples_residual_variance.txt is created to save MCMC samples for residual_variance. The file test_mt_annotated_bayesc_independent_sampler1/MCMC_samples_marker_effects_annotated_mt_independent_sampler1_y1.txt is created to save MCMC samples for marker_effects_annotated_mt_independent_sampler1_y1. The file test_mt_annotated_bayesc_independent_sampler1/MCMC_samples_marker_effects_annotated_mt_independent_sampler1_y2.txt is created to save MCMC samples for marker_effects_annotated_mt_independent_sampler1_y2. The file test_mt_annotated_bayesc_independent_sampler1/MCMC_samples_marker_effects_variances_annotated_mt_independent_sampler1.txt is created to save MCMC samples for marker_effects_variances_annotated_mt_independent_sampler1. The file test_mt_annotated_bayesc_independent_sampler1/MCMC_samples_pi_annotated_mt_independent_sampler1.txt is created to save MCMC samples for pi_annotated_mt_independent_sampler1. running MCMC ... 17%|█████▉ | ETA: 0:00:45 running MCMC ... 100%|███████████████████████████████████| Time: 0:00:08 The version of Julia and Platform in use: Julia Version 1.14.0-DEV.3055 Build Info: Commit 7e75a8061a* (2026-08-27 09:46 UTC) GC: Built with stock GC Platform Info: OS: Linux (x86_64-unknown-linux-gnu) CPU: 128 × AMD EPYC 7502 32-Core Processor (znver2) WORD_SIZE: 64 LLVM: libLLVM-22.1.8 (ORCJIT, znver2) Threads: 1 default, 0 interactive, 1 GC (on 1 virtual cores) Environment: JULIA_CPU_THREADS = 1 JULIA_NUM_PRECOMPILE_TASKS = 1 JULIA_PKG_PRECOMPILE_AUTO = 0 JULIA_PKGEVAL = true JULIA_DEPOT_PATH = /home/pkgeval/.julia:/usr/local/share/julia: JULIA_NUM_THREADS = 1 JULIA_LOAD_PATH = @:/tmp/jl_g0vHag The analysis has finished. Results are saved in the returned variable and text files. MCMC samples are saved in text files. The delimiter in genotypes.txt is ','. The header (marker IDs) is provided in genotypes.txt. Genotype informatin: #markers: 5; #individuals: 7 The folder test_mt_annotated_bayesc_independent_sampler2 is created to save results. Checking genotypes... Checking phenotypes... Individual IDs (strings) are provided in the first column of the phenotypic data. In this complete genomic data (non-single-step) analyis, 1 phenotyped individuals are not genotyped. These are removed from the analysis. Predicted values for individuals of interest will be obtained as the summation of Any[] (Note that genomic data is always included for now).Phenotypes for 7 observations are used in the analysis.These individual IDs are saved in the file test_mt_annotated_bayesc_independent_sampler2/IDs_for_individuals_with_phenotypes.txt. The prior for marker effects covariance matrix is calculated from genetic covariance matrix and Π. The mean of the prior for the marker effects covariance matrix is: 1.231156 1.231156 1.231156 1.407035 BLOCK STARTS: [1, 3, 5] A Linear Mixed Model was build using model equations: y1 = intercept + annotated_mt_independent_sampler2 y2 = intercept + annotated_mt_independent_sampler2 Model Information: Term C/F F/R nLevels intercept factor fixed 1 MCMC Information: chain_length 12 burnin 2 starting_value true printout_frequency 13 output_samples_frequency 10 constraint on residual variance false constraint on marker effect variance for annotated_mt_independent_sampler2 false missing_phenotypes true update_priors_frequency 0 seed 123 Hyper-parameters Information: residual variances: 1.0f0 0.5f0 0.5f0 1.0f0 Genomic Information: complete genomic data (i.e., non-single-step analysis) Genomic Category annotated_mt_independent_sampler2 Method BayesC genetic variances (genomic): 1.0 0.5 0.5 1.0 marker effect variances: 1.231 1.231 1.231 1.407 Π: (Y(yes):included; N(no):excluded) ["y1", "y2"] probability ["N", "Y"] 0.15 ["N", "N"] 0.45 ["Y", "Y"] 0.2 ["Y", "N"] 0.2 estimatePi true estimate_scale false Degree of freedom for hyper-parameters: residual variances: 6.000 marker effect variances: 6.000 The file test_mt_annotated_bayesc_independent_sampler2/MCMC_samples_residual_variance.txt is created to save MCMC samples for residual_variance. The file test_mt_annotated_bayesc_independent_sampler2/MCMC_samples_marker_effects_annotated_mt_independent_sampler2_y1.txt is created to save MCMC samples for marker_effects_annotated_mt_independent_sampler2_y1. The file test_mt_annotated_bayesc_independent_sampler2/MCMC_samples_marker_effects_annotated_mt_independent_sampler2_y2.txt is created to save MCMC samples for marker_effects_annotated_mt_independent_sampler2_y2. The file test_mt_annotated_bayesc_independent_sampler2/MCMC_samples_marker_effects_variances_annotated_mt_independent_sampler2.txt is created to save MCMC samples for marker_effects_variances_annotated_mt_independent_sampler2. The file test_mt_annotated_bayesc_independent_sampler2/MCMC_samples_pi_annotated_mt_independent_sampler2.txt is created to save MCMC samples for pi_annotated_mt_independent_sampler2. running MCMC ... 17%|█████▉ | ETA: 0:00:38 running MCMC ... 100%|███████████████████████████████████| Time: 0:00:07 The version of Julia and Platform in use: Julia Version 1.14.0-DEV.3055 Build Info: Commit 7e75a8061a* (2026-08-27 09:46 UTC) GC: Built with stock GC Platform Info: OS: Linux (x86_64-unknown-linux-gnu) CPU: 128 × AMD EPYC 7502 32-Core Processor (znver2) WORD_SIZE: 64 LLVM: libLLVM-22.1.8 (ORCJIT, znver2) Threads: 1 default, 0 interactive, 1 GC (on 1 virtual cores) Environment: JULIA_CPU_THREADS = 1 JULIA_NUM_PRECOMPILE_TASKS = 1 JULIA_PKG_PRECOMPILE_AUTO = 0 JULIA_PKGEVAL = true JULIA_DEPOT_PATH = /home/pkgeval/.julia:/usr/local/share/julia: JULIA_NUM_THREADS = 1 JULIA_LOAD_PATH = @:/tmp/jl_g0vHag The analysis has finished. Results are saved in the returned variable and text files. MCMC samples are saved in text files. The delimiter in genotypes.txt is ','. The header (marker IDs) is provided in genotypes.txt. Genotype informatin: #markers: 5; #individuals: 7 The delimiter in genotypes.txt is ','. The header (marker IDs) is provided in genotypes.txt. Genotype informatin: #markers: 5; #individuals: 7 The delimiter in genotypes.txt is ','. The header (marker IDs) is provided in genotypes.txt. Genotype informatin: #markers: 5; #individuals: 7 The delimiter in genotypes.txt is ','. The header (marker IDs) is provided in genotypes.txt. Missing values (9.0) are replaced by column means. Multi-trait RR-BLUP: Error During Test at /home/pkgeval/.julia/packages/JWAS/AxFc6/test/unit/test_multitrait_mcmc.jl:768 Got exception outside of a @test MethodError: no method matching reducedim1(::Matrix{Float32}, ::Matrix{Float32}) The function `reducedim1` exists, but no method is defined for this combination of argument types. Closest candidates are: reducedim1(::Any) @ Base reducedim.jl:1229 Stacktrace: [1] centralize_sumabs2!(R::Matrix{Float32}, A::Matrix{Float32}, means::Matrix{Float32}) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:282 [2] varm!(R::Matrix{Float32}, A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:309 [3] _varm(A::Matrix{Float32}, m::Matrix{Float32}, corrected::Bool, region::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:341 [4] varm(A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:339 [inlined] [5] _var(A::Matrix{Float32}, corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:386 [inlined] [6] var(A::Matrix{Float32}; corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:380 [inlined] [7] get_genotypes(file::String, G::Matrix{Float64}; method::String, Pi::Float64, estimatePi::Bool, G_is_marker_variance::Bool, df::Float64, estimate_variance::Bool, estimate_scale::Bool, constraint::Bool, separator::Char, header::Bool, double_precision::Bool, quality_control::Bool, MAF::Float64, missing_value::Float64, center::Bool, starting_value::Bool, annotations::Bool, multi_trait_sampler::Symbol, storage::Symbol) @ JWAS ~/.julia/packages/JWAS/AxFc6/src/1.JWAS/src/markers/readgenotypes.jl:390 [8] top-level scope @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_multitrait_mcmc.jl:769 [9] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [10] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_multitrait_mcmc.jl:770 [inlined] The delimiter in pedigree.txt is ','. Pedigree information: #individuals: 12 #sires: 4 #dams: 5 #founders: 3 The folder test_mt_ped is created to save results. Checking pedigree... Checking phenotypes... Individual IDs (strings) are provided in the first column of the phenotypic data. Predicted values for individuals of interest will be obtained as the summation of Any["y1:ID", "y2:ID"] (Note that genomic data is always included for now).Phenotypes for 4 observations are used in the analysis.These individual IDs are saved in the file test_mt_ped/IDs_for_individuals_with_phenotypes.txt. A Linear Mixed Model was build using model equations: y1 = intercept + ID y2 = intercept + ID Model Information: Term C/F F/R nLevels intercept factor fixed 1 ID factor random 12 MCMC Information: chain_length 100 burnin 20 starting_value true printout_frequency 101 output_samples_frequency 10 constraint on residual variance false missing_phenotypes true update_priors_frequency 0 seed 123 Hyper-parameters Information: random effect variances (y1:ID,y2:ID): 1.0f0 0.5f0 0.5f0 1.0f0 genetic variances (polygenic): 1.0f0 0.5f0 0.5f0 1.0f0 residual variances: 1.0f0 0.5f0 0.5f0 1.0f0 Genomic Information: Degree of freedom for hyper-parameters: residual variances: 6.000 polygenic effect variances: 6.000 The file test_mt_ped/MCMC_samples_residual_variance.txt is created to save MCMC samples for residual_variance. The file test_mt_ped/MCMC_samples_polygenic_effects_variance.txt is created to save MCMC samples for polygenic_effects_variance. The file test_mt_ped/MCMC_samples_y1.ID_y2.ID_variances.txt is created to save MCMC samples for y1:ID_y2:ID_variances. The file test_mt_ped/MCMC_samples_EBV_y1.txt is created to save MCMC samples for EBV_y1. The file test_mt_ped/MCMC_samples_EBV_y2.txt is created to save MCMC samples for EBV_y2. The file test_mt_ped/MCMC_samples_genetic_variance.txt is created to save MCMC samples for genetic_variance. The file test_mt_ped/MCMC_samples_heritability.txt is created to save MCMC samples for heritability. Multi-trait with pedigree: Error During Test at /home/pkgeval/.julia/packages/JWAS/AxFc6/test/unit/test_multitrait_mcmc.jl:785 Got exception outside of a @test MethodError: no method matching reducedim1(::Matrix{Float64}, ::Matrix{Float64}) The function `reducedim1` exists, but no method is defined for this combination of argument types. Closest candidates are: reducedim1(::Any) @ Base reducedim.jl:1229 Stacktrace: [1] centralize_sumabs2!(R::Matrix{Float64}, A::Matrix{Float64}, means::Matrix{Float64}) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:282 [2] varm!(R::Matrix{Float64}, A::Matrix{Float64}, m::Matrix{Float64}; corrected::Bool) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:309 [3] _varm(A::Matrix{Float64}, m::Matrix{Float64}, corrected::Bool, region::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:341 [4] varm(A::Matrix{Float64}, m::Matrix{Float64}; corrected::Bool, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:339 [inlined] [5] _var(A::Matrix{Float64}, corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:386 [inlined] [6] var(A::Matrix{Float64}; corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:380 [inlined] [7] output_result(mme::JWAS.MME, output_folder::String, solMean::Vector{Float64}, meanVare::Matrix{Float64}, G0Mean::Matrix{Float64}, solMean2::Vector{Float64}, meanVare2::Matrix{Float64}, G0Mean2::Matrix{Float64}) @ JWAS ~/.julia/packages/JWAS/AxFc6/src/1.JWAS/src/output.jl:199 [8] MCMC_BayesianAlphabet(mme::JWAS.MME, df::DataFrame) @ JWAS ~/.julia/packages/JWAS/AxFc6/src/1.JWAS/src/MCMC/MCMC_BayesianAlphabet.jl:446 [9] runMCMC(mme::JWAS.MME, df::DataFrame; heterogeneous_residuals::Bool, chain_length::Int64, starting_value::Bool, burnin::Int64, output_samples_frequency::Int64, update_priors_frequency::Int64, single_step_analysis::Bool, pedigree::Bool, fitting_J_vector::Bool, causal_structure::Bool, missing_phenotypes::Bool, RRM::Bool, outputEBV::Bool, output_heritability::Bool, prediction_equation::Bool, seed::Int64, printout_model_info::Bool, printout_frequency::Int64, big_memory::Bool, double_precision::Bool, fast_blocks::Bool, independent_blocks::Bool, memory_guard::Symbol, memory_guard_ratio::Float64, output_folder::String, output_samples_for_all_parameters::Bool, methods::String, Pi::Float64, estimatePi::Bool, estimate_scale::Bool, estimate_variance::Bool, categorical_trait::Bool, censored_trait::Bool) @ JWAS ~/.julia/packages/JWAS/AxFc6/src/1.JWAS/src/JWAS.jl:466 [10] top-level scope @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_multitrait_mcmc.jl:786 [11] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [12] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_multitrait_mcmc.jl:791 [inlined] The delimiter in genotypes.txt is ','. The header (marker IDs) is provided in genotypes.txt. Missing values (9.0) are replaced by column means. Multi-trait with i.i.d. random effect: Error During Test at /home/pkgeval/.julia/packages/JWAS/AxFc6/test/unit/test_multitrait_mcmc.jl:804 Got exception outside of a @test MethodError: no method matching reducedim1(::Matrix{Float32}, ::Matrix{Float32}) The function `reducedim1` exists, but no method is defined for this combination of argument types. Closest candidates are: reducedim1(::Any) @ Base reducedim.jl:1229 Stacktrace: [1] centralize_sumabs2!(R::Matrix{Float32}, A::Matrix{Float32}, means::Matrix{Float32}) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:282 [2] varm!(R::Matrix{Float32}, A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:309 [3] _varm(A::Matrix{Float32}, m::Matrix{Float32}, corrected::Bool, region::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:341 [4] varm(A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:339 [inlined] [5] _var(A::Matrix{Float32}, corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:386 [inlined] [6] var(A::Matrix{Float32}; corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:380 [inlined] [7] get_genotypes(file::String, G::Matrix{Float64}; method::String, Pi::Float64, estimatePi::Bool, G_is_marker_variance::Bool, df::Float64, estimate_variance::Bool, estimate_scale::Bool, constraint::Bool, separator::Char, header::Bool, double_precision::Bool, quality_control::Bool, MAF::Float64, missing_value::Float64, center::Bool, starting_value::Bool, annotations::Bool, multi_trait_sampler::Symbol, storage::Symbol) @ JWAS ~/.julia/packages/JWAS/AxFc6/src/1.JWAS/src/markers/readgenotypes.jl:390 [8] top-level scope @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_multitrait_mcmc.jl:805 [9] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [10] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_multitrait_mcmc.jl:806 [inlined] The delimiter in genotypes.txt is ','. The header (marker IDs) is provided in genotypes.txt. Missing values (9.0) are replaced by column means. BayesB single-trait: Error During Test at /home/pkgeval/.julia/packages/JWAS/AxFc6/test/unit/test_bayesb_methods.jl:8 Got exception outside of a @test MethodError: no method matching reducedim1(::Matrix{Float32}, ::Matrix{Float32}) The function `reducedim1` exists, but no method is defined for this combination of argument types. Closest candidates are: reducedim1(::Any) @ Base reducedim.jl:1229 Stacktrace: [1] centralize_sumabs2!(R::Matrix{Float32}, A::Matrix{Float32}, means::Matrix{Float32}) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:282 [2] varm!(R::Matrix{Float32}, A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:309 [3] _varm(A::Matrix{Float32}, m::Matrix{Float32}, corrected::Bool, region::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:341 [4] varm(A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:339 [inlined] [5] _var(A::Matrix{Float32}, corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:386 [inlined] [6] var(A::Matrix{Float32}; corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:380 [inlined] [7] get_genotypes(file::String, G::Float64; method::String, Pi::Float64, estimatePi::Bool, G_is_marker_variance::Bool, df::Float64, estimate_variance::Bool, estimate_scale::Bool, constraint::Bool, separator::Char, header::Bool, double_precision::Bool, quality_control::Bool, MAF::Float64, missing_value::Float64, center::Bool, starting_value::Bool, annotations::Bool, multi_trait_sampler::Symbol, storage::Symbol) @ JWAS ~/.julia/packages/JWAS/AxFc6/src/1.JWAS/src/markers/readgenotypes.jl:390 [8] top-level scope @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_bayesb_methods.jl:9 [9] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [10] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_bayesb_methods.jl:9 [inlined] The delimiter in genotypes.txt is ','. The header (marker IDs) is provided in genotypes.txt. Missing values (9.0) are replaced by column means. BayesA single-trait (converted to BayesB with π=0): Error During Test at /home/pkgeval/.julia/packages/JWAS/AxFc6/test/unit/test_bayesb_methods.jl:24 Got exception outside of a @test MethodError: no method matching reducedim1(::Matrix{Float32}, ::Matrix{Float32}) The function `reducedim1` exists, but no method is defined for this combination of argument types. Closest candidates are: reducedim1(::Any) @ Base reducedim.jl:1229 Stacktrace: [1] centralize_sumabs2!(R::Matrix{Float32}, A::Matrix{Float32}, means::Matrix{Float32}) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:282 [2] varm!(R::Matrix{Float32}, A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:309 [3] _varm(A::Matrix{Float32}, m::Matrix{Float32}, corrected::Bool, region::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:341 [4] varm(A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:339 [inlined] [5] _var(A::Matrix{Float32}, corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:386 [inlined] [6] var(A::Matrix{Float32}; corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:380 [inlined] [7] get_genotypes(file::String, G::Float64; method::String, Pi::Float64, estimatePi::Bool, G_is_marker_variance::Bool, df::Float64, estimate_variance::Bool, estimate_scale::Bool, constraint::Bool, separator::Char, header::Bool, double_precision::Bool, quality_control::Bool, MAF::Float64, missing_value::Float64, center::Bool, starting_value::Bool, annotations::Bool, multi_trait_sampler::Symbol, storage::Symbol) @ JWAS ~/.julia/packages/JWAS/AxFc6/src/1.JWAS/src/markers/readgenotypes.jl:390 [8] top-level scope @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_bayesb_methods.jl:25 [9] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [10] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_bayesb_methods.jl:25 [inlined] The delimiter in genotypes.txt is ','. The header (marker IDs) is provided in genotypes.txt. Missing values (9.0) are replaced by column means. BayesL (Lasso) single-trait: Error During Test at /home/pkgeval/.julia/packages/JWAS/AxFc6/test/unit/test_bayesb_methods.jl:40 Got exception outside of a @test MethodError: no method matching reducedim1(::Matrix{Float32}, ::Matrix{Float32}) The function `reducedim1` exists, but no method is defined for this combination of argument types. Closest candidates are: reducedim1(::Any) @ Base reducedim.jl:1229 Stacktrace: [1] centralize_sumabs2!(R::Matrix{Float32}, A::Matrix{Float32}, means::Matrix{Float32}) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:282 [2] varm!(R::Matrix{Float32}, A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:309 [3] _varm(A::Matrix{Float32}, m::Matrix{Float32}, corrected::Bool, region::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:341 [4] varm(A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:339 [inlined] [5] _var(A::Matrix{Float32}, corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:386 [inlined] [6] var(A::Matrix{Float32}; corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:380 [inlined] [7] get_genotypes(file::String, G::Float64; method::String, Pi::Float64, estimatePi::Bool, G_is_marker_variance::Bool, df::Float64, estimate_variance::Bool, estimate_scale::Bool, constraint::Bool, separator::Char, header::Bool, double_precision::Bool, quality_control::Bool, MAF::Float64, missing_value::Float64, center::Bool, starting_value::Bool, annotations::Bool, multi_trait_sampler::Symbol, storage::Symbol) @ JWAS ~/.julia/packages/JWAS/AxFc6/src/1.JWAS/src/markers/readgenotypes.jl:390 [8] top-level scope @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_bayesb_methods.jl:41 [9] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [10] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_bayesb_methods.jl:41 [inlined] The delimiter in genotypes.txt is ','. The header (marker IDs) is provided in genotypes.txt. Missing values (9.0) are replaced by column means. GBLUP: Error During Test at /home/pkgeval/.julia/packages/JWAS/AxFc6/test/unit/test_bayesb_methods.jl:56 Got exception outside of a @test MethodError: no method matching reducedim1(::Matrix{Float32}, ::Matrix{Float32}) The function `reducedim1` exists, but no method is defined for this combination of argument types. Closest candidates are: reducedim1(::Any) @ Base reducedim.jl:1229 Stacktrace: [1] centralize_sumabs2!(R::Matrix{Float32}, A::Matrix{Float32}, means::Matrix{Float32}) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:282 [2] varm!(R::Matrix{Float32}, A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:309 [3] _varm(A::Matrix{Float32}, m::Matrix{Float32}, corrected::Bool, region::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:341 [4] varm(A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:339 [inlined] [5] _var(A::Matrix{Float32}, corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:386 [inlined] [6] var(A::Matrix{Float32}; corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:380 [inlined] [7] get_genotypes(file::String, G::Float64; method::String, Pi::Float64, estimatePi::Bool, G_is_marker_variance::Bool, df::Float64, estimate_variance::Bool, estimate_scale::Bool, constraint::Bool, separator::Char, header::Bool, double_precision::Bool, quality_control::Bool, MAF::Float64, missing_value::Float64, center::Bool, starting_value::Bool, annotations::Bool, multi_trait_sampler::Symbol, storage::Symbol) @ JWAS ~/.julia/packages/JWAS/AxFc6/src/1.JWAS/src/markers/readgenotypes.jl:390 [8] top-level scope @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_bayesb_methods.jl:57 [9] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [10] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_bayesb_methods.jl:57 [inlined] The delimiter in genotypes.txt is ','. The header (marker IDs) is provided in genotypes.txt. Missing values (9.0) are replaced by column means. single-trait dense BayesR genotype loads: Error During Test at /home/pkgeval/.julia/packages/JWAS/AxFc6/test/unit/test_bayesr.jl:63 Got exception outside of a @test MethodError: no method matching reducedim1(::Matrix{Float32}, ::Matrix{Float32}) The function `reducedim1` exists, but no method is defined for this combination of argument types. Closest candidates are: reducedim1(::Any) @ Base reducedim.jl:1229 Stacktrace: [1] centralize_sumabs2!(R::Matrix{Float32}, A::Matrix{Float32}, means::Matrix{Float32}) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:282 [2] varm!(R::Matrix{Float32}, A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:309 [3] _varm(A::Matrix{Float32}, m::Matrix{Float32}, corrected::Bool, region::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:341 [4] varm(A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:339 [inlined] [5] _var(A::Matrix{Float32}, corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:386 [inlined] [6] var(A::Matrix{Float32}; corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:380 [inlined] [7] get_genotypes(file::String, G::Float64; method::String, Pi::Vector{Float64}, estimatePi::Bool, G_is_marker_variance::Bool, df::Float64, estimate_variance::Bool, estimate_scale::Bool, constraint::Bool, separator::Char, header::Bool, double_precision::Bool, quality_control::Bool, MAF::Float64, missing_value::Float64, center::Bool, starting_value::Bool, annotations::Bool, multi_trait_sampler::Symbol, storage::Symbol) @ JWAS ~/.julia/packages/JWAS/AxFc6/src/1.JWAS/src/markers/readgenotypes.jl:390 [8] top-level scope @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_bayesr.jl:63 [9] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [10] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_bayesr.jl:64 [inlined] [11] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [12] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_bayesr.jl:64 [inlined] The delimiter in genotypes.txt is ','. The header (marker IDs) is provided in genotypes.txt. Missing values (9.0) are replaced by column means. BayesR rejects bad Pi length: Error During Test at /home/pkgeval/.julia/packages/JWAS/AxFc6/test/unit/test_bayesr.jl:73 Got exception outside of a @test MethodError: no method matching reducedim1(::Matrix{Float32}, ::Matrix{Float32}) The function `reducedim1` exists, but no method is defined for this combination of argument types. Closest candidates are: reducedim1(::Any) @ Base reducedim.jl:1229 Stacktrace: [1] centralize_sumabs2!(R::Matrix{Float32}, A::Matrix{Float32}, means::Matrix{Float32}) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:282 [2] varm!(R::Matrix{Float32}, A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:309 [3] _varm(A::Matrix{Float32}, m::Matrix{Float32}, corrected::Bool, region::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:341 [4] varm(A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:339 [inlined] [5] _var(A::Matrix{Float32}, corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:386 [inlined] [6] var(A::Matrix{Float32}; corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:380 [inlined] [7] get_genotypes(file::String, G::Float64; method::String, Pi::Vector{Float64}, estimatePi::Bool, G_is_marker_variance::Bool, df::Float64, estimate_variance::Bool, estimate_scale::Bool, constraint::Bool, separator::Char, header::Bool, double_precision::Bool, quality_control::Bool, MAF::Float64, missing_value::Float64, center::Bool, starting_value::Bool, annotations::Bool, multi_trait_sampler::Symbol, storage::Symbol) @ JWAS ~/.julia/packages/JWAS/AxFc6/src/1.JWAS/src/markers/readgenotypes.jl:390 [8] top-level scope @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_bayesr.jl:63 [9] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [10] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_bayesr.jl:74 [inlined] [11] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [12] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_bayesr.jl:74 [inlined] The delimiter in genotypes.txt is ','. The header (marker IDs) is provided in genotypes.txt. Missing values (9.0) are replaced by column means. BayesR fast_blocks gets past validation: Error During Test at /home/pkgeval/.julia/packages/JWAS/AxFc6/test/unit/test_bayesr.jl:84 Got exception outside of a @test MethodError: no method matching reducedim1(::Matrix{Float32}, ::Matrix{Float32}) The function `reducedim1` exists, but no method is defined for this combination of argument types. Closest candidates are: reducedim1(::Any) @ Base reducedim.jl:1229 Stacktrace: [1] centralize_sumabs2!(R::Matrix{Float32}, A::Matrix{Float32}, means::Matrix{Float32}) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:282 [2] varm!(R::Matrix{Float32}, A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:309 [3] _varm(A::Matrix{Float32}, m::Matrix{Float32}, corrected::Bool, region::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:341 [4] varm(A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:339 [inlined] [5] _var(A::Matrix{Float32}, corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:386 [inlined] [6] var(A::Matrix{Float32}; corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:380 [inlined] [7] get_genotypes(file::String, G::Float64; method::String, Pi::Vector{Float64}, estimatePi::Bool, G_is_marker_variance::Bool, df::Float64, estimate_variance::Bool, estimate_scale::Bool, constraint::Bool, separator::Char, header::Bool, double_precision::Bool, quality_control::Bool, MAF::Float64, missing_value::Float64, center::Bool, starting_value::Bool, annotations::Bool, multi_trait_sampler::Symbol, storage::Symbol) @ JWAS ~/.julia/packages/JWAS/AxFc6/src/1.JWAS/src/markers/readgenotypes.jl:390 [8] top-level scope @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_bayesr.jl:63 [9] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [10] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_bayesr.jl:85 [inlined] [11] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [12] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_bayesr.jl:85 [inlined] The delimiter in genotypes.txt is ','. The header (marker IDs) is provided in genotypes.txt. Missing values (9.0) are replaced by column means. BayesR fast_blocks=1 means block size 1: Error During Test at /home/pkgeval/.julia/packages/JWAS/AxFc6/test/unit/test_bayesr.jl:95 Got exception outside of a @test MethodError: no method matching reducedim1(::Matrix{Float32}, ::Matrix{Float32}) The function `reducedim1` exists, but no method is defined for this combination of argument types. Closest candidates are: reducedim1(::Any) @ Base reducedim.jl:1229 Stacktrace: [1] centralize_sumabs2!(R::Matrix{Float32}, A::Matrix{Float32}, means::Matrix{Float32}) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:282 [2] varm!(R::Matrix{Float32}, A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:309 [3] _varm(A::Matrix{Float32}, m::Matrix{Float32}, corrected::Bool, region::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:341 [4] varm(A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:339 [inlined] [5] _var(A::Matrix{Float32}, corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:386 [inlined] [6] var(A::Matrix{Float32}; corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:380 [inlined] [7] get_genotypes(file::String, G::Float64; method::String, Pi::Vector{Float64}, estimatePi::Bool, G_is_marker_variance::Bool, df::Float64, estimate_variance::Bool, estimate_scale::Bool, constraint::Bool, separator::Char, header::Bool, double_precision::Bool, quality_control::Bool, MAF::Float64, missing_value::Float64, center::Bool, starting_value::Bool, annotations::Bool, multi_trait_sampler::Symbol, storage::Symbol) @ JWAS ~/.julia/packages/JWAS/AxFc6/src/1.JWAS/src/markers/readgenotypes.jl:390 [8] top-level scope @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_bayesr.jl:63 [9] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [10] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_bayesr.jl:96 [inlined] [11] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [12] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_bayesr.jl:96 [inlined] The delimiter in genotypes.txt is ','. The header (marker IDs) is provided in genotypes.txt. Missing values (9.0) are replaced by column means. BayesR copies caller Pi input: Error During Test at /home/pkgeval/.julia/packages/JWAS/AxFc6/test/unit/test_bayesr.jl:117 Got exception outside of a @test MethodError: no method matching reducedim1(::Matrix{Float32}, ::Matrix{Float32}) The function `reducedim1` exists, but no method is defined for this combination of argument types. Closest candidates are: reducedim1(::Any) @ Base reducedim.jl:1229 Stacktrace: [1] centralize_sumabs2!(R::Matrix{Float32}, A::Matrix{Float32}, means::Matrix{Float32}) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:282 [2] varm!(R::Matrix{Float32}, A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:309 [3] _varm(A::Matrix{Float32}, m::Matrix{Float32}, corrected::Bool, region::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:341 [4] varm(A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:339 [inlined] [5] _var(A::Matrix{Float32}, corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:386 [inlined] [6] var(A::Matrix{Float32}; corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:380 [inlined] [7] get_genotypes(file::String, G::Float64; method::String, Pi::Vector{Float64}, estimatePi::Bool, G_is_marker_variance::Bool, df::Float64, estimate_variance::Bool, estimate_scale::Bool, constraint::Bool, separator::Char, header::Bool, double_precision::Bool, quality_control::Bool, MAF::Float64, missing_value::Float64, center::Bool, starting_value::Bool, annotations::Bool, multi_trait_sampler::Symbol, storage::Symbol) @ JWAS ~/.julia/packages/JWAS/AxFc6/src/1.JWAS/src/markers/readgenotypes.jl:390 [8] top-level scope @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_bayesr.jl:63 [9] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [10] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_bayesr.jl:118 [inlined] [11] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [12] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_bayesr.jl:120 [inlined] Streaming genotype files are created with prefix /tmp/jl_Q7cyyn/geno_stream. Genotype informatin: #markers: 3; #individuals: 4 (storage=:stream) The folder /tmp/jl_apiFG72LG3 is created to save results. The delimiter in genotypes.txt is ','. The header (marker IDs) is provided in genotypes.txt. Missing values (9.0) are replaced by column means. unannotated multi-trait is rejected: Error During Test at /home/pkgeval/.julia/packages/JWAS/AxFc6/test/unit/test_bayesr.jl:172 Got exception outside of a @test MethodError: no method matching reducedim1(::Matrix{Float32}, ::Matrix{Float32}) The function `reducedim1` exists, but no method is defined for this combination of argument types. Closest candidates are: reducedim1(::Any) @ Base reducedim.jl:1229 Stacktrace: [1] centralize_sumabs2!(R::Matrix{Float32}, A::Matrix{Float32}, means::Matrix{Float32}) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:282 [2] varm!(R::Matrix{Float32}, A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:309 [3] _varm(A::Matrix{Float32}, m::Matrix{Float32}, corrected::Bool, region::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:341 [4] varm(A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:339 [inlined] [5] _var(A::Matrix{Float32}, corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:386 [inlined] [6] var(A::Matrix{Float32}; corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:380 [inlined] [7] get_genotypes(file::String, G::Matrix{Float64}; method::String, Pi::Vector{Float64}, estimatePi::Bool, G_is_marker_variance::Bool, df::Float64, estimate_variance::Bool, estimate_scale::Bool, constraint::Bool, separator::Char, header::Bool, double_precision::Bool, quality_control::Bool, MAF::Float64, missing_value::Float64, center::Bool, starting_value::Bool, annotations::Bool, multi_trait_sampler::Symbol, storage::Symbol) @ JWAS ~/.julia/packages/JWAS/AxFc6/src/1.JWAS/src/markers/readgenotypes.jl:390 [8] top-level scope @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_bayesr.jl:63 [9] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [10] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_bayesr.jl:142 [inlined] [11] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [12] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_bayesr.jl:173 [inlined] [13] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [14] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_bayesr.jl:176 [inlined] The delimiter in genotypes.txt is ','. The header (marker IDs) is provided in genotypes.txt. Missing values (9.0) are replaced by column means. RRM is rejected: Error During Test at /home/pkgeval/.julia/packages/JWAS/AxFc6/test/unit/test_bayesr.jl:189 Got exception outside of a @test MethodError: no method matching reducedim1(::Matrix{Float32}, ::Matrix{Float32}) The function `reducedim1` exists, but no method is defined for this combination of argument types. Closest candidates are: reducedim1(::Any) @ Base reducedim.jl:1229 Stacktrace: [1] centralize_sumabs2!(R::Matrix{Float32}, A::Matrix{Float32}, means::Matrix{Float32}) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:282 [2] varm!(R::Matrix{Float32}, A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:309 [3] _varm(A::Matrix{Float32}, m::Matrix{Float32}, corrected::Bool, region::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:341 [4] varm(A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:339 [inlined] [5] _var(A::Matrix{Float32}, corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:386 [inlined] [6] var(A::Matrix{Float32}; corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:380 [inlined] [7] get_genotypes(file::String, G::Float64; method::String, Pi::Vector{Float64}, estimatePi::Bool, G_is_marker_variance::Bool, df::Float64, estimate_variance::Bool, estimate_scale::Bool, constraint::Bool, separator::Char, header::Bool, double_precision::Bool, quality_control::Bool, MAF::Float64, missing_value::Float64, center::Bool, starting_value::Bool, annotations::Bool, multi_trait_sampler::Symbol, storage::Symbol) @ JWAS ~/.julia/packages/JWAS/AxFc6/src/1.JWAS/src/markers/readgenotypes.jl:390 [8] top-level scope @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_bayesr.jl:63 [9] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [10] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_bayesr.jl:142 [inlined] [11] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [12] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_bayesr.jl:190 [inlined] [13] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [14] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_bayesr.jl:190 [inlined] The delimiter in genotypes.txt is ','. The header (marker IDs) is provided in genotypes.txt. Missing values (9.0) are replaced by column means. BayesR single-trait run: Error During Test at /home/pkgeval/.julia/packages/JWAS/AxFc6/test/unit/test_bayesr.jl:282 Got exception outside of a @test MethodError: no method matching reducedim1(::Matrix{Float32}, ::Matrix{Float32}) The function `reducedim1` exists, but no method is defined for this combination of argument types. Closest candidates are: reducedim1(::Any) @ Base reducedim.jl:1229 Stacktrace: [1] centralize_sumabs2!(R::Matrix{Float32}, A::Matrix{Float32}, means::Matrix{Float32}) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:282 [2] varm!(R::Matrix{Float32}, A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:309 [3] _varm(A::Matrix{Float32}, m::Matrix{Float32}, corrected::Bool, region::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:341 [4] varm(A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:339 [inlined] [5] _var(A::Matrix{Float32}, corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:386 [inlined] [6] var(A::Matrix{Float32}; corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:380 [inlined] [7] get_genotypes(file::String, G::Float64; method::String, Pi::Vector{Float64}, estimatePi::Bool, G_is_marker_variance::Bool, df::Float64, estimate_variance::Bool, estimate_scale::Bool, constraint::Bool, separator::Char, header::Bool, double_precision::Bool, quality_control::Bool, MAF::Float64, missing_value::Float64, center::Bool, starting_value::Bool, annotations::Bool, multi_trait_sampler::Symbol, storage::Symbol) @ JWAS ~/.julia/packages/JWAS/AxFc6/src/1.JWAS/src/markers/readgenotypes.jl:390 [8] top-level scope @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_bayesr.jl:283 [9] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [10] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_bayesr.jl:283 [inlined] The delimiter in genotypes.txt is ','. The header (marker IDs) is provided in genotypes.txt. Missing values (9.0) are replaced by column means. BayesR estimatePi output: Error During Test at /home/pkgeval/.julia/packages/JWAS/AxFc6/test/unit/test_bayesr.jl:320 Got exception outside of a @test MethodError: no method matching reducedim1(::Matrix{Float32}, ::Matrix{Float32}) The function `reducedim1` exists, but no method is defined for this combination of argument types. Closest candidates are: reducedim1(::Any) @ Base reducedim.jl:1229 Stacktrace: [1] centralize_sumabs2!(R::Matrix{Float32}, A::Matrix{Float32}, means::Matrix{Float32}) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:282 [2] varm!(R::Matrix{Float32}, A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:309 [3] _varm(A::Matrix{Float32}, m::Matrix{Float32}, corrected::Bool, region::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:341 [4] varm(A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:339 [inlined] [5] _var(A::Matrix{Float32}, corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:386 [inlined] [6] var(A::Matrix{Float32}; corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:380 [inlined] [7] get_genotypes(file::String, G::Float64; method::String, Pi::Vector{Float64}, estimatePi::Bool, G_is_marker_variance::Bool, df::Float64, estimate_variance::Bool, estimate_scale::Bool, constraint::Bool, separator::Char, header::Bool, double_precision::Bool, quality_control::Bool, MAF::Float64, missing_value::Float64, center::Bool, starting_value::Bool, annotations::Bool, multi_trait_sampler::Symbol, storage::Symbol) @ JWAS ~/.julia/packages/JWAS/AxFc6/src/1.JWAS/src/markers/readgenotypes.jl:390 [8] top-level scope @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_bayesr.jl:321 [9] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [10] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_bayesr.jl:321 [inlined] The delimiter in genotypes.txt is ','. The header (marker IDs) is provided in genotypes.txt. Missing values (9.0) are replaced by column means. BayesR fast_blocks dispatch: Error During Test at /home/pkgeval/.julia/packages/JWAS/AxFc6/test/unit/test_bayesr.jl:346 Got exception outside of a @test MethodError: no method matching reducedim1(::Matrix{Float32}, ::Matrix{Float32}) The function `reducedim1` exists, but no method is defined for this combination of argument types. Closest candidates are: reducedim1(::Any) @ Base reducedim.jl:1229 Stacktrace: [1] centralize_sumabs2!(R::Matrix{Float32}, A::Matrix{Float32}, means::Matrix{Float32}) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:282 [2] varm!(R::Matrix{Float32}, A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:309 [3] _varm(A::Matrix{Float32}, m::Matrix{Float32}, corrected::Bool, region::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:341 [4] varm(A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:339 [inlined] [5] _var(A::Matrix{Float32}, corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:386 [inlined] [6] var(A::Matrix{Float32}; corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:380 [inlined] [7] get_genotypes(file::String, G::Float64; method::String, Pi::Vector{Float64}, estimatePi::Bool, G_is_marker_variance::Bool, df::Float64, estimate_variance::Bool, estimate_scale::Bool, constraint::Bool, separator::Char, header::Bool, double_precision::Bool, quality_control::Bool, MAF::Float64, missing_value::Float64, center::Bool, starting_value::Bool, annotations::Bool, multi_trait_sampler::Symbol, storage::Symbol) @ JWAS ~/.julia/packages/JWAS/AxFc6/src/1.JWAS/src/markers/readgenotypes.jl:390 [8] top-level scope @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_bayesr.jl:347 [9] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [10] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_bayesr.jl:347 [inlined] BayesC and BayesR fast-block benchmark mode: Test Failed at /home/pkgeval/.julia/packages/JWAS/AxFc6/test/unit/test_bayesr_parity.jl:296 Expression: success(pipeline(setenv(cmd, env), stdout = devnull, stderr = devnull)) Evaluated: success(pipeline(pipeline(setenv(`/opt/julia/bin/julia -C native -J/opt/julia/lib/julia/sys.so --depwarn=yes --check-bounds=yes --pkgimages=existing -g1 --startup-file=no --project=/tmp/jl_g0vHag/Project.toml --startup-file=no /home/pkgeval/.julia/packages/JWAS/AxFc6/benchmarks/bayesc_bayesr_fast_blocks_comparison.jl /tmp/jl_ckdtdq`,["JWAS_METHOD_BLOCK_N_OBS=20", "OPENBLAS_NUM_THREADS=1", "OPENBLAS_MAIN_FREE=1", "JULIA_LOAD_PATH=@:/tmp/jl_g0vHag", "JWAS_METHOD_BLOCK_BURNIN=20", "JWAS_METHOD_BLOCK_SEEDS=2026,2027", "JULIA_DEPOT_PATH=/home/pkgeval/.julia:/usr/local/share/julia:", "JULIA_PKG_PRECOMPILE_AUTO=0", "JULIA_PKGEVAL=true", "PATH=/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/bin:/sbin:/opt/julia/bin", "JWAS_METHOD_BLOCK_N_MARKERS=12", "CI=true", "JWAS_METHOD_BLOCK_CHAIN_LENGTH=60", "JULIA_CPU_THREADS=1", "PYTHON=", "R_HOME=*", "JULIA_NUM_PRECOMPILE_TASKS=1", "HOME=/home/pkgeval", "JULIA_NUM_THREADS=1", "DISPLAY=:1", "PKGEVAL=true", "LANG=C.UTF-8"]), stdout>Base.DevNull()), stderr>Base.DevNull())) Stacktrace: [1] top-level scope @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_bayesr_parity.jl:285 [2] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [3] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_bayesr_parity.jl:296 [inlined] [4] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:784 [inlined] BayesC and BayesR fast-block benchmark mode: Test Failed at /home/pkgeval/.julia/packages/JWAS/AxFc6/test/unit/test_bayesr_parity.jl:297 Expression: isfile(joinpath(outdir, "comparison_runs.csv")) Evaluated: isfile("/tmp/jl_ckdtdq/comparison_runs.csv") Stacktrace: [1] top-level scope @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_bayesr_parity.jl:285 [2] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [3] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_bayesr_parity.jl:297 [inlined] [4] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:784 [inlined] BayesC and BayesR fast-block benchmark mode: Test Failed at /home/pkgeval/.julia/packages/JWAS/AxFc6/test/unit/test_bayesr_parity.jl:298 Expression: isfile(joinpath(outdir, "comparison_pairwise_summary.csv")) Evaluated: isfile("/tmp/jl_ckdtdq/comparison_pairwise_summary.csv") Stacktrace: [1] top-level scope @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_bayesr_parity.jl:285 [2] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [3] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_bayesr_parity.jl:298 [inlined] [4] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:784 [inlined] BayesC and BayesR fast-block benchmark mode: Error During Test at /home/pkgeval/.julia/packages/JWAS/AxFc6/test/unit/test_bayesr_parity.jl:284 Got exception outside of a @test ArgumentError: "/tmp/jl_ckdtdq/comparison_runs.csv" is not a valid file or doesn't exist Stacktrace: [1] macro expansion @ ~/.julia/packages/CSV/T1GBD/src/context.jl:316 [inlined] [2] CSV.Context(source::CSV.Arg, header::CSV.Arg, normalizenames::CSV.Arg, datarow::CSV.Arg, skipto::CSV.Arg, footerskip::CSV.Arg, transpose::CSV.Arg, comment::CSV.Arg, ignoreemptyrows::CSV.Arg, ignoreemptylines::CSV.Arg, select::CSV.Arg, drop::CSV.Arg, limit::CSV.Arg, buffer_in_memory::CSV.Arg, threaded::CSV.Arg, ntasks::CSV.Arg, tasks::CSV.Arg, rows_to_check::CSV.Arg, lines_to_check::CSV.Arg, missingstrings::CSV.Arg, missingstring::CSV.Arg, delim::CSV.Arg, ignorerepeated::CSV.Arg, quoted::CSV.Arg, quotechar::CSV.Arg, openquotechar::CSV.Arg, closequotechar::CSV.Arg, escapechar::CSV.Arg, dateformat::CSV.Arg, dateformats::CSV.Arg, decimal::CSV.Arg, groupmark::CSV.Arg, truestrings::CSV.Arg, falsestrings::CSV.Arg, stripwhitespace::CSV.Arg, type::CSV.Arg, types::CSV.Arg, typemap::CSV.Arg, pool::CSV.Arg, downcast::CSV.Arg, lazystrings::CSV.Arg, stringtype::CSV.Arg, strict::CSV.Arg, silencewarnings::CSV.Arg, maxwarnings::CSV.Arg, debug::CSV.Arg, parsingdebug::CSV.Arg, validate::CSV.Arg, streaming::CSV.Arg) @ CSV ~/.julia/packages/CSV/T1GBD/src/context.jl:0 [3] CSV.File(source::String; header::Int64, normalizenames::Bool, datarow::Int64, skipto::Int64, footerskip::Int64, transpose::Bool, comment::Nothing, ignoreemptyrows::Bool, ignoreemptylines::Nothing, select::Nothing, drop::Nothing, limit::Nothing, buffer_in_memory::Bool, threaded::Nothing, ntasks::Nothing, tasks::Nothing, rows_to_check::Int64, lines_to_check::Nothing, missingstrings::Vector{String}, missingstring::String, delim::Nothing, ignorerepeated::Bool, quoted::Bool, quotechar::Char, openquotechar::Nothing, closequotechar::Nothing, escapechar::Char, dateformat::Nothing, dateformats::Nothing, decimal::UInt8, groupmark::Nothing, truestrings::Vector{String}, falsestrings::Vector{String}, stripwhitespace::Bool, type::Nothing, types::Nothing, typemap::IdDict{Type, Type}, pool::Tuple{Float64, Int64}, downcast::Bool, lazystrings::Bool, stringtype::Core.TypeEgal{InlineString}, strict::Bool, silencewarnings::Bool, maxwarnings::Int64, debug::Bool, parsingdebug::Bool, validate::Bool) @ CSV ~/.julia/packages/CSV/T1GBD/src/file.jl:222 [inlined] [4] CSV.File(source::String) @ CSV ~/.julia/packages/CSV/T1GBD/src/file.jl:162 [inlined] [5] read(source::String, sink::Type; copycols::Bool, kwargs::@Kwargs{}) @ CSV ~/.julia/packages/CSV/T1GBD/src/CSV.jl:117 [6] read(source::String, sink::Type) @ CSV ~/.julia/packages/CSV/T1GBD/src/CSV.jl:113 [7] top-level scope @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_bayesr_parity.jl:285 [8] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [9] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_bayesr_parity.jl:300 [inlined] Annotated BayesR production benchmark mode: Test Failed at /home/pkgeval/.julia/packages/JWAS/AxFc6/test/unit/test_bayesr_parity.jl:327 Expression: success(pipeline(setenv(cmd, env), stdout = devnull, stderr = devnull)) Evaluated: success(pipeline(pipeline(setenv(`/opt/julia/bin/julia -C native -J/opt/julia/lib/julia/sys.so --depwarn=yes --check-bounds=yes --pkgimages=existing -g1 --startup-file=no --project=/tmp/jl_g0vHag/Project.toml --startup-file=no /home/pkgeval/.julia/packages/JWAS/AxFc6/benchmarks/annotated_bayesr_comparison.jl /tmp/jl_vlsqPx`,["OPENBLAS_NUM_THREADS=1", "OPENBLAS_MAIN_FREE=1", "JULIA_LOAD_PATH=@:/tmp/jl_g0vHag", "JWAS_ANNOT_BENCH_CHAIN_LENGTH=60", "JULIA_DEPOT_PATH=/home/pkgeval/.julia:/usr/local/share/julia:", "JULIA_PKG_PRECOMPILE_AUTO=0", "JULIA_PKGEVAL=true", "PATH=/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/bin:/sbin:/opt/julia/bin", "CI=true", "JWAS_ANNOT_BENCH_SCENARIO=stepwise_annotation_signal", "JWAS_ANNOT_BENCH_N_MARKERS=40", "JULIA_CPU_THREADS=1", "PYTHON=", "R_HOME=*", "JULIA_NUM_PRECOMPILE_TASKS=1", "JWAS_ANNOT_BENCH_N_OBS=30", "HOME=/home/pkgeval", "JULIA_NUM_THREADS=1", "DISPLAY=:1", "JWAS_ANNOT_BENCH_SEEDS=2026,2027", "PKGEVAL=true", "JWAS_ANNOT_BENCH_BURNIN=20", "LANG=C.UTF-8"]), stdout>Base.DevNull()), stderr>Base.DevNull())) Stacktrace: [1] top-level scope @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_bayesr_parity.jl:315 [2] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [3] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_bayesr_parity.jl:327 [inlined] [4] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:784 [inlined] Annotated BayesR production benchmark mode: Test Failed at /home/pkgeval/.julia/packages/JWAS/AxFc6/test/unit/test_bayesr_parity.jl:328 Expression: isfile(joinpath(outdir, "comparison_runs.csv")) Evaluated: isfile("/tmp/jl_vlsqPx/comparison_runs.csv") Stacktrace: [1] top-level scope @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_bayesr_parity.jl:315 [2] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [3] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_bayesr_parity.jl:328 [inlined] [4] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:784 [inlined] Annotated BayesR production benchmark mode: Test Failed at /home/pkgeval/.julia/packages/JWAS/AxFc6/test/unit/test_bayesr_parity.jl:329 Expression: isfile(joinpath(outdir, "comparison_summary.csv")) Evaluated: isfile("/tmp/jl_vlsqPx/comparison_summary.csv") Stacktrace: [1] top-level scope @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_bayesr_parity.jl:315 [2] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [3] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_bayesr_parity.jl:329 [inlined] [4] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:784 [inlined] Annotated BayesR production benchmark mode: Test Failed at /home/pkgeval/.julia/packages/JWAS/AxFc6/test/unit/test_bayesr_parity.jl:330 Expression: isfile(joinpath(outdir, "pip_group_summary.csv")) Evaluated: isfile("/tmp/jl_vlsqPx/pip_group_summary.csv") Stacktrace: [1] top-level scope @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_bayesr_parity.jl:315 [2] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [3] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_bayesr_parity.jl:330 [inlined] [4] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:784 [inlined] Annotated BayesR production benchmark mode: Test Failed at /home/pkgeval/.julia/packages/JWAS/AxFc6/test/unit/test_bayesr_parity.jl:331 Expression: isfile(joinpath(outdir, "annotation_coefficients.csv")) Evaluated: isfile("/tmp/jl_vlsqPx/annotation_coefficients.csv") Stacktrace: [1] top-level scope @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_bayesr_parity.jl:315 [2] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [3] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_bayesr_parity.jl:331 [inlined] [4] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:784 [inlined] Annotated BayesR production benchmark mode: Error During Test at /home/pkgeval/.julia/packages/JWAS/AxFc6/test/unit/test_bayesr_parity.jl:314 Got exception outside of a @test ArgumentError: "/tmp/jl_vlsqPx/comparison_runs.csv" is not a valid file or doesn't exist Stacktrace: [1] macro expansion @ ~/.julia/packages/CSV/T1GBD/src/context.jl:316 [inlined] [2] CSV.Context(source::CSV.Arg, header::CSV.Arg, normalizenames::CSV.Arg, datarow::CSV.Arg, skipto::CSV.Arg, footerskip::CSV.Arg, transpose::CSV.Arg, comment::CSV.Arg, ignoreemptyrows::CSV.Arg, ignoreemptylines::CSV.Arg, select::CSV.Arg, drop::CSV.Arg, limit::CSV.Arg, buffer_in_memory::CSV.Arg, threaded::CSV.Arg, ntasks::CSV.Arg, tasks::CSV.Arg, rows_to_check::CSV.Arg, lines_to_check::CSV.Arg, missingstrings::CSV.Arg, missingstring::CSV.Arg, delim::CSV.Arg, ignorerepeated::CSV.Arg, quoted::CSV.Arg, quotechar::CSV.Arg, openquotechar::CSV.Arg, closequotechar::CSV.Arg, escapechar::CSV.Arg, dateformat::CSV.Arg, dateformats::CSV.Arg, decimal::CSV.Arg, groupmark::CSV.Arg, truestrings::CSV.Arg, falsestrings::CSV.Arg, stripwhitespace::CSV.Arg, type::CSV.Arg, types::CSV.Arg, typemap::CSV.Arg, pool::CSV.Arg, downcast::CSV.Arg, lazystrings::CSV.Arg, stringtype::CSV.Arg, strict::CSV.Arg, silencewarnings::CSV.Arg, maxwarnings::CSV.Arg, debug::CSV.Arg, parsingdebug::CSV.Arg, validate::CSV.Arg, streaming::CSV.Arg) @ CSV ~/.julia/packages/CSV/T1GBD/src/context.jl:0 [3] CSV.File(source::String; header::Int64, normalizenames::Bool, datarow::Int64, skipto::Int64, footerskip::Int64, transpose::Bool, comment::Nothing, ignoreemptyrows::Bool, ignoreemptylines::Nothing, select::Nothing, drop::Nothing, limit::Nothing, buffer_in_memory::Bool, threaded::Nothing, ntasks::Nothing, tasks::Nothing, rows_to_check::Int64, lines_to_check::Nothing, missingstrings::Vector{String}, missingstring::String, delim::Nothing, ignorerepeated::Bool, quoted::Bool, quotechar::Char, openquotechar::Nothing, closequotechar::Nothing, escapechar::Char, dateformat::Nothing, dateformats::Nothing, decimal::UInt8, groupmark::Nothing, truestrings::Vector{String}, falsestrings::Vector{String}, stripwhitespace::Bool, type::Nothing, types::Nothing, typemap::IdDict{Type, Type}, pool::Tuple{Float64, Int64}, downcast::Bool, lazystrings::Bool, stringtype::Core.TypeEgal{InlineString}, strict::Bool, silencewarnings::Bool, maxwarnings::Int64, debug::Bool, parsingdebug::Bool, validate::Bool) @ CSV ~/.julia/packages/CSV/T1GBD/src/file.jl:222 [inlined] [4] CSV.File(source::String) @ CSV ~/.julia/packages/CSV/T1GBD/src/file.jl:162 [inlined] [5] read(source::String, sink::Type; copycols::Bool, kwargs::@Kwargs{}) @ CSV ~/.julia/packages/CSV/T1GBD/src/CSV.jl:117 [6] read(source::String, sink::Type) @ CSV ~/.julia/packages/CSV/T1GBD/src/CSV.jl:113 [7] top-level scope @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_bayesr_parity.jl:315 [8] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [9] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_bayesr_parity.jl:334 [inlined] The delimiter in genotypes.txt is ','. The header (marker IDs) is provided in genotypes.txt. Missing values (9.0) are replaced by column means. GWAS Window Analysis: Error During Test at /home/pkgeval/.julia/packages/JWAS/AxFc6/test/runtests.jl:139 Got exception outside of a @test LoadError: MethodError: no method matching reducedim1(::Matrix{Float32}, ::Matrix{Float32}) The function `reducedim1` exists, but no method is defined for this combination of argument types. Closest candidates are: reducedim1(::Any) @ Base reducedim.jl:1229 Stacktrace: [1] centralize_sumabs2!(R::Matrix{Float32}, A::Matrix{Float32}, means::Matrix{Float32}) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:282 [2] varm!(R::Matrix{Float32}, A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:309 [3] _varm(A::Matrix{Float32}, m::Matrix{Float32}, corrected::Bool, region::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:341 [4] varm(A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:339 [inlined] [5] _var(A::Matrix{Float32}, corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:386 [inlined] [6] var(A::Matrix{Float32}; corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:380 [inlined] [7] get_genotypes(file::String, G::Float64; method::String, Pi::Float64, estimatePi::Bool, G_is_marker_variance::Bool, df::Float64, estimate_variance::Bool, estimate_scale::Bool, constraint::Bool, separator::Char, header::Bool, double_precision::Bool, quality_control::Bool, MAF::Float64, missing_value::Float64, center::Bool, starting_value::Bool, annotations::Bool, multi_trait_sampler::Symbol, storage::Symbol) @ JWAS ~/.julia/packages/JWAS/AxFc6/src/1.JWAS/src/markers/readgenotypes.jl:390 [8] top-level scope @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_gwas_windows.jl:10 [9] include(mapexpr::Function, mod::Module, _path::String) @ Base Base.jl:335 [10] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/runtests.jl:140 [inlined] [11] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [12] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/runtests.jl:140 [inlined] [13] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [14] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/runtests.jl:71 [inlined] [15] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [16] top-level scope @ ~/.julia/packages/JWAS/AxFc6/test/runtests.jl:70 in expression starting at /home/pkgeval/.julia/packages/JWAS/AxFc6/test/unit/test_gwas_windows.jl:10 The delimiter in genotypes.txt is ','. The header (marker IDs) is provided in genotypes.txt. Missing values (9.0) are replaced by column means. Reproducibility across methods: Error During Test at /home/pkgeval/.julia/packages/JWAS/AxFc6/test/unit/test_misc_coverage.jl:53 Got exception outside of a @test MethodError: no method matching reducedim1(::Matrix{Float32}, ::Matrix{Float32}) The function `reducedim1` exists, but no method is defined for this combination of argument types. Closest candidates are: reducedim1(::Any) @ Base reducedim.jl:1229 Stacktrace: [1] centralize_sumabs2!(R::Matrix{Float32}, A::Matrix{Float32}, means::Matrix{Float32}) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:282 [2] varm!(R::Matrix{Float32}, A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:309 [3] _varm(A::Matrix{Float32}, m::Matrix{Float32}, corrected::Bool, region::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:341 [4] varm(A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:339 [inlined] [5] _var(A::Matrix{Float32}, corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:386 [inlined] [6] var(A::Matrix{Float32}; corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:380 [inlined] [7] get_genotypes(file::String, G::Float64; method::String, Pi::Float64, estimatePi::Bool, G_is_marker_variance::Bool, df::Float64, estimate_variance::Bool, estimate_scale::Bool, constraint::Bool, separator::Char, header::Bool, double_precision::Bool, quality_control::Bool, MAF::Float64, missing_value::Float64, center::Bool, starting_value::Bool, annotations::Bool, multi_trait_sampler::Symbol, storage::Symbol) @ JWAS ~/.julia/packages/JWAS/AxFc6/src/1.JWAS/src/markers/readgenotypes.jl:390 [8] top-level scope @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_misc_coverage.jl:54 [9] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [10] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_misc_coverage.jl:54 [inlined] The delimiter in genotypes.txt is ','. The header (marker IDs) is provided in genotypes.txt. Missing values (9.0) are replaced by column means. outputMCMCsamples for multiple terms: Error During Test at /home/pkgeval/.julia/packages/JWAS/AxFc6/test/unit/test_misc_coverage.jl:69 Got exception outside of a @test MethodError: no method matching reducedim1(::Matrix{Float32}, ::Matrix{Float32}) The function `reducedim1` exists, but no method is defined for this combination of argument types. Closest candidates are: reducedim1(::Any) @ Base reducedim.jl:1229 Stacktrace: [1] centralize_sumabs2!(R::Matrix{Float32}, A::Matrix{Float32}, means::Matrix{Float32}) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:282 [2] varm!(R::Matrix{Float32}, A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:309 [3] _varm(A::Matrix{Float32}, m::Matrix{Float32}, corrected::Bool, region::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:341 [4] varm(A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:339 [inlined] [5] _var(A::Matrix{Float32}, corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:386 [inlined] [6] var(A::Matrix{Float32}; corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:380 [inlined] [7] get_genotypes(file::String, G::Float64; method::String, Pi::Float64, estimatePi::Bool, G_is_marker_variance::Bool, df::Float64, estimate_variance::Bool, estimate_scale::Bool, constraint::Bool, separator::Char, header::Bool, double_precision::Bool, quality_control::Bool, MAF::Float64, missing_value::Float64, center::Bool, starting_value::Bool, annotations::Bool, multi_trait_sampler::Symbol, storage::Symbol) @ JWAS ~/.julia/packages/JWAS/AxFc6/src/1.JWAS/src/markers/readgenotypes.jl:390 [8] top-level scope @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_misc_coverage.jl:70 [9] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [10] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_misc_coverage.jl:70 [inlined] A Linear Mixed Model was build using model equations: y1 = intercept + x1 Model Information: Term C/F F/R nLevels intercept factor fixed 0 x1 factor fixed 0 The delimiter in genotypes.txt is ','. The header (marker IDs) is provided in genotypes.txt. Missing values (9.0) are replaced by column means. Multi-trait describe: Error During Test at /home/pkgeval/.julia/packages/JWAS/AxFc6/test/unit/test_misc_coverage.jl:99 Got exception outside of a @test MethodError: no method matching reducedim1(::Matrix{Float32}, ::Matrix{Float32}) The function `reducedim1` exists, but no method is defined for this combination of argument types. Closest candidates are: reducedim1(::Any) @ Base reducedim.jl:1229 Stacktrace: [1] centralize_sumabs2!(R::Matrix{Float32}, A::Matrix{Float32}, means::Matrix{Float32}) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:282 [2] varm!(R::Matrix{Float32}, A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:309 [3] _varm(A::Matrix{Float32}, m::Matrix{Float32}, corrected::Bool, region::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:341 [4] varm(A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:339 [inlined] [5] _var(A::Matrix{Float32}, corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:386 [inlined] [6] var(A::Matrix{Float32}; corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:380 [inlined] [7] get_genotypes(file::String, G::Matrix{Float64}; method::String, Pi::Float64, estimatePi::Bool, G_is_marker_variance::Bool, df::Float64, estimate_variance::Bool, estimate_scale::Bool, constraint::Bool, separator::Char, header::Bool, double_precision::Bool, quality_control::Bool, MAF::Float64, missing_value::Float64, center::Bool, starting_value::Bool, annotations::Bool, multi_trait_sampler::Symbol, storage::Symbol) @ JWAS ~/.julia/packages/JWAS/AxFc6/src/1.JWAS/src/markers/readgenotypes.jl:390 [8] top-level scope @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_misc_coverage.jl:100 [9] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [10] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_misc_coverage.jl:102 [inlined] The delimiter in genotypes.txt is ','. The header (marker IDs) is provided in genotypes.txt. Missing values (9.0) are replaced by column means. Independent blocks API and explicit block starts: Error During Test at /home/pkgeval/.julia/packages/JWAS/AxFc6/test/unit/test_misc_coverage.jl:116 Got exception outside of a @test MethodError: no method matching reducedim1(::Matrix{Float32}, ::Matrix{Float32}) The function `reducedim1` exists, but no method is defined for this combination of argument types. Closest candidates are: reducedim1(::Any) @ Base reducedim.jl:1229 Stacktrace: [1] centralize_sumabs2!(R::Matrix{Float32}, A::Matrix{Float32}, means::Matrix{Float32}) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:282 [2] varm!(R::Matrix{Float32}, A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:309 [3] _varm(A::Matrix{Float32}, m::Matrix{Float32}, corrected::Bool, region::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:341 [4] varm(A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:339 [inlined] [5] _var(A::Matrix{Float32}, corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:386 [inlined] [6] var(A::Matrix{Float32}; corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:380 [inlined] [7] get_genotypes(file::String, G::Float64; method::String, Pi::Float64, estimatePi::Bool, G_is_marker_variance::Bool, df::Float64, estimate_variance::Bool, estimate_scale::Bool, constraint::Bool, separator::Char, header::Bool, double_precision::Bool, quality_control::Bool, MAF::Float64, missing_value::Float64, center::Bool, starting_value::Bool, annotations::Bool, multi_trait_sampler::Symbol, storage::Symbol) @ JWAS ~/.julia/packages/JWAS/AxFc6/src/1.JWAS/src/markers/readgenotypes.jl:390 [8] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_misc_coverage.jl:117 [inlined] [9] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [10] top-level scope @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_misc_coverage.jl:117 The delimiter in genotypes.txt is ','. The header (marker IDs) is provided in genotypes.txt. Missing values (9.0) are replaced by column means. Multi-trait BayesB: Error During Test at /home/pkgeval/.julia/packages/JWAS/AxFc6/test/unit/test_advanced_coverage.jl:13 Got exception outside of a @test MethodError: no method matching reducedim1(::Matrix{Float32}, ::Matrix{Float32}) The function `reducedim1` exists, but no method is defined for this combination of argument types. Closest candidates are: reducedim1(::Any) @ Base reducedim.jl:1229 Stacktrace: [1] centralize_sumabs2!(R::Matrix{Float32}, A::Matrix{Float32}, means::Matrix{Float32}) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:282 [2] varm!(R::Matrix{Float32}, A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:309 [3] _varm(A::Matrix{Float32}, m::Matrix{Float32}, corrected::Bool, region::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:341 [4] varm(A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:339 [inlined] [5] _var(A::Matrix{Float32}, corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:386 [inlined] [6] var(A::Matrix{Float32}; corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:380 [inlined] [7] get_genotypes(file::String, G::Matrix{Float64}; method::String, Pi::Float64, estimatePi::Bool, G_is_marker_variance::Bool, df::Float64, estimate_variance::Bool, estimate_scale::Bool, constraint::Bool, separator::Char, header::Bool, double_precision::Bool, quality_control::Bool, MAF::Float64, missing_value::Float64, center::Bool, starting_value::Bool, annotations::Bool, multi_trait_sampler::Symbol, storage::Symbol) @ JWAS ~/.julia/packages/JWAS/AxFc6/src/1.JWAS/src/markers/readgenotypes.jl:390 [8] top-level scope @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_advanced_coverage.jl:14 [9] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [10] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_advanced_coverage.jl:16 [inlined] The delimiter in genotypes.txt is ','. The header (marker IDs) is provided in genotypes.txt. Missing values (9.0) are replaced by column means. Multi-trait BayesL: Error During Test at /home/pkgeval/.julia/packages/JWAS/AxFc6/test/unit/test_advanced_coverage.jl:35 Got exception outside of a @test MethodError: no method matching reducedim1(::Matrix{Float32}, ::Matrix{Float32}) The function `reducedim1` exists, but no method is defined for this combination of argument types. Closest candidates are: reducedim1(::Any) @ Base reducedim.jl:1229 Stacktrace: [1] centralize_sumabs2!(R::Matrix{Float32}, A::Matrix{Float32}, means::Matrix{Float32}) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:282 [2] varm!(R::Matrix{Float32}, A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:309 [3] _varm(A::Matrix{Float32}, m::Matrix{Float32}, corrected::Bool, region::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:341 [4] varm(A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:339 [inlined] [5] _var(A::Matrix{Float32}, corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:386 [inlined] [6] var(A::Matrix{Float32}; corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:380 [inlined] [7] get_genotypes(file::String, G::Matrix{Float64}; method::String, Pi::Float64, estimatePi::Bool, G_is_marker_variance::Bool, df::Float64, estimate_variance::Bool, estimate_scale::Bool, constraint::Bool, separator::Char, header::Bool, double_precision::Bool, quality_control::Bool, MAF::Float64, missing_value::Float64, center::Bool, starting_value::Bool, annotations::Bool, multi_trait_sampler::Symbol, storage::Symbol) @ JWAS ~/.julia/packages/JWAS/AxFc6/src/1.JWAS/src/markers/readgenotypes.jl:390 [8] top-level scope @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_advanced_coverage.jl:36 [9] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [10] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_advanced_coverage.jl:38 [inlined] The delimiter in genotypes.txt is ','. The header (marker IDs) is provided in genotypes.txt. Missing values (9.0) are replaced by column means. Multi-trait GBLUP: Error During Test at /home/pkgeval/.julia/packages/JWAS/AxFc6/test/unit/test_advanced_coverage.jl:56 Got exception outside of a @test MethodError: no method matching reducedim1(::Matrix{Float32}, ::Matrix{Float32}) The function `reducedim1` exists, but no method is defined for this combination of argument types. Closest candidates are: reducedim1(::Any) @ Base reducedim.jl:1229 Stacktrace: [1] centralize_sumabs2!(R::Matrix{Float32}, A::Matrix{Float32}, means::Matrix{Float32}) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:282 [2] varm!(R::Matrix{Float32}, A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:309 [3] _varm(A::Matrix{Float32}, m::Matrix{Float32}, corrected::Bool, region::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:341 [4] varm(A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:339 [inlined] [5] _var(A::Matrix{Float32}, corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:386 [inlined] [6] var(A::Matrix{Float32}; corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:380 [inlined] [7] get_genotypes(file::String, G::Matrix{Float64}; method::String, Pi::Float64, estimatePi::Bool, G_is_marker_variance::Bool, df::Float64, estimate_variance::Bool, estimate_scale::Bool, constraint::Bool, separator::Char, header::Bool, double_precision::Bool, quality_control::Bool, MAF::Float64, missing_value::Float64, center::Bool, starting_value::Bool, annotations::Bool, multi_trait_sampler::Symbol, storage::Symbol) @ JWAS ~/.julia/packages/JWAS/AxFc6/src/1.JWAS/src/markers/readgenotypes.jl:390 [8] top-level scope @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_advanced_coverage.jl:57 [9] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [10] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_advanced_coverage.jl:59 [inlined] The delimiter in genotypes.txt is ','. The header (marker IDs) is provided in genotypes.txt. Missing values (9.0) are replaced by column means. Multi-trait BayesC with G constraint (mega-trait): Error During Test at /home/pkgeval/.julia/packages/JWAS/AxFc6/test/unit/test_advanced_coverage.jl:77 Got exception outside of a @test MethodError: no method matching reducedim1(::Matrix{Float32}, ::Matrix{Float32}) The function `reducedim1` exists, but no method is defined for this combination of argument types. Closest candidates are: reducedim1(::Any) @ Base reducedim.jl:1229 Stacktrace: [1] centralize_sumabs2!(R::Matrix{Float32}, A::Matrix{Float32}, means::Matrix{Float32}) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:282 [2] varm!(R::Matrix{Float32}, A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:309 [3] _varm(A::Matrix{Float32}, m::Matrix{Float32}, corrected::Bool, region::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:341 [4] varm(A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:339 [inlined] [5] _var(A::Matrix{Float32}, corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:386 [inlined] [6] var(A::Matrix{Float32}; corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:380 [inlined] [7] get_genotypes(file::String, G::Matrix{Float64}; method::String, Pi::Float64, estimatePi::Bool, G_is_marker_variance::Bool, df::Float64, estimate_variance::Bool, estimate_scale::Bool, constraint::Bool, separator::Char, header::Bool, double_precision::Bool, quality_control::Bool, MAF::Float64, missing_value::Float64, center::Bool, starting_value::Bool, annotations::Bool, multi_trait_sampler::Symbol, storage::Symbol) @ JWAS ~/.julia/packages/JWAS/AxFc6/src/1.JWAS/src/markers/readgenotypes.jl:390 [8] top-level scope @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_advanced_coverage.jl:78 [9] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [10] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_advanced_coverage.jl:80 [inlined] The delimiter in genotypes.txt is ','. The header (marker IDs) is provided in genotypes.txt. Missing values (9.0) are replaced by column means. Multi-trait with missing phenotypes: Error During Test at /home/pkgeval/.julia/packages/JWAS/AxFc6/test/unit/test_advanced_coverage.jl:99 Got exception outside of a @test MethodError: no method matching reducedim1(::Matrix{Float32}, ::Matrix{Float32}) The function `reducedim1` exists, but no method is defined for this combination of argument types. Closest candidates are: reducedim1(::Any) @ Base reducedim.jl:1229 Stacktrace: [1] centralize_sumabs2!(R::Matrix{Float32}, A::Matrix{Float32}, means::Matrix{Float32}) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:282 [2] varm!(R::Matrix{Float32}, A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:309 [3] _varm(A::Matrix{Float32}, m::Matrix{Float32}, corrected::Bool, region::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:341 [4] varm(A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:339 [inlined] [5] _var(A::Matrix{Float32}, corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:386 [inlined] [6] var(A::Matrix{Float32}; corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:380 [inlined] [7] get_genotypes(file::String, G::Matrix{Float64}; method::String, Pi::Float64, estimatePi::Bool, G_is_marker_variance::Bool, df::Float64, estimate_variance::Bool, estimate_scale::Bool, constraint::Bool, separator::Char, header::Bool, double_precision::Bool, quality_control::Bool, MAF::Float64, missing_value::Float64, center::Bool, starting_value::Bool, annotations::Bool, multi_trait_sampler::Symbol, storage::Symbol) @ JWAS ~/.julia/packages/JWAS/AxFc6/src/1.JWAS/src/markers/readgenotypes.jl:390 [8] top-level scope @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_advanced_coverage.jl:100 [9] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [10] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_advanced_coverage.jl:102 [inlined] The delimiter in genotypes.txt is ','. The header (marker IDs) is provided in genotypes.txt. Missing values (9.0) are replaced by column means. Multi-trait BayesC with Pi estimation: Error During Test at /home/pkgeval/.julia/packages/JWAS/AxFc6/test/unit/test_advanced_coverage.jl:122 Got exception outside of a @test MethodError: no method matching reducedim1(::Matrix{Float32}, ::Matrix{Float32}) The function `reducedim1` exists, but no method is defined for this combination of argument types. Closest candidates are: reducedim1(::Any) @ Base reducedim.jl:1229 Stacktrace: [1] centralize_sumabs2!(R::Matrix{Float32}, A::Matrix{Float32}, means::Matrix{Float32}) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:282 [2] varm!(R::Matrix{Float32}, A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:309 [3] _varm(A::Matrix{Float32}, m::Matrix{Float32}, corrected::Bool, region::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:341 [4] varm(A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:339 [inlined] [5] _var(A::Matrix{Float32}, corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:386 [inlined] [6] var(A::Matrix{Float32}; corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:380 [inlined] [7] get_genotypes(file::String, G::Matrix{Float64}; method::String, Pi::Float64, estimatePi::Bool, G_is_marker_variance::Bool, df::Float64, estimate_variance::Bool, estimate_scale::Bool, constraint::Bool, separator::Char, header::Bool, double_precision::Bool, quality_control::Bool, MAF::Float64, missing_value::Float64, center::Bool, starting_value::Bool, annotations::Bool, multi_trait_sampler::Symbol, storage::Symbol) @ JWAS ~/.julia/packages/JWAS/AxFc6/src/1.JWAS/src/markers/readgenotypes.jl:390 [8] top-level scope @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_advanced_coverage.jl:123 [9] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [10] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_advanced_coverage.jl:125 [inlined] The delimiter in genotypes.txt is ','. The header (marker IDs) is provided in genotypes.txt. Missing values (9.0) are replaced by column means. Single-trait BayesC with estimate_scale: Error During Test at /home/pkgeval/.julia/packages/JWAS/AxFc6/test/unit/test_advanced_coverage.jl:144 Got exception outside of a @test MethodError: no method matching reducedim1(::Matrix{Float32}, ::Matrix{Float32}) The function `reducedim1` exists, but no method is defined for this combination of argument types. Closest candidates are: reducedim1(::Any) @ Base reducedim.jl:1229 Stacktrace: [1] centralize_sumabs2!(R::Matrix{Float32}, A::Matrix{Float32}, means::Matrix{Float32}) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:282 [2] varm!(R::Matrix{Float32}, A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:309 [3] _varm(A::Matrix{Float32}, m::Matrix{Float32}, corrected::Bool, region::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:341 [4] varm(A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:339 [inlined] [5] _var(A::Matrix{Float32}, corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:386 [inlined] [6] var(A::Matrix{Float32}; corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:380 [inlined] [7] get_genotypes(file::String, G::Float64; method::String, Pi::Float64, estimatePi::Bool, G_is_marker_variance::Bool, df::Float64, estimate_variance::Bool, estimate_scale::Bool, constraint::Bool, separator::Char, header::Bool, double_precision::Bool, quality_control::Bool, MAF::Float64, missing_value::Float64, center::Bool, starting_value::Bool, annotations::Bool, multi_trait_sampler::Symbol, storage::Symbol) @ JWAS ~/.julia/packages/JWAS/AxFc6/src/1.JWAS/src/markers/readgenotypes.jl:390 [8] top-level scope @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_advanced_coverage.jl:145 [9] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [10] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_advanced_coverage.jl:145 [inlined] The delimiter in genotypes.txt is ','. The header (marker IDs) is provided in genotypes.txt. Missing values (9.0) are replaced by column means. Multi-trait EBV output: Error During Test at /home/pkgeval/.julia/packages/JWAS/AxFc6/test/unit/test_advanced_coverage.jl:163 Got exception outside of a @test MethodError: no method matching reducedim1(::Matrix{Float32}, ::Matrix{Float32}) The function `reducedim1` exists, but no method is defined for this combination of argument types. Closest candidates are: reducedim1(::Any) @ Base reducedim.jl:1229 Stacktrace: [1] centralize_sumabs2!(R::Matrix{Float32}, A::Matrix{Float32}, means::Matrix{Float32}) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:282 [2] varm!(R::Matrix{Float32}, A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:309 [3] _varm(A::Matrix{Float32}, m::Matrix{Float32}, corrected::Bool, region::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:341 [4] varm(A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:339 [inlined] [5] _var(A::Matrix{Float32}, corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:386 [inlined] [6] var(A::Matrix{Float32}; corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:380 [inlined] [7] get_genotypes(file::String, G::Matrix{Float64}; method::String, Pi::Float64, estimatePi::Bool, G_is_marker_variance::Bool, df::Float64, estimate_variance::Bool, estimate_scale::Bool, constraint::Bool, separator::Char, header::Bool, double_precision::Bool, quality_control::Bool, MAF::Float64, missing_value::Float64, center::Bool, starting_value::Bool, annotations::Bool, multi_trait_sampler::Symbol, storage::Symbol) @ JWAS ~/.julia/packages/JWAS/AxFc6/src/1.JWAS/src/markers/readgenotypes.jl:390 [8] top-level scope @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_advanced_coverage.jl:164 [9] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [10] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_advanced_coverage.jl:166 [inlined] The delimiter in genotypes.txt is ','. The header (marker IDs) is provided in genotypes.txt. Missing values (9.0) are replaced by column means. Single-trait with weights (heterogeneous residuals): Error During Test at /home/pkgeval/.julia/packages/JWAS/AxFc6/test/unit/test_advanced_coverage.jl:189 Got exception outside of a @test MethodError: no method matching reducedim1(::Matrix{Float32}, ::Matrix{Float32}) The function `reducedim1` exists, but no method is defined for this combination of argument types. Closest candidates are: reducedim1(::Any) @ Base reducedim.jl:1229 Stacktrace: [1] centralize_sumabs2!(R::Matrix{Float32}, A::Matrix{Float32}, means::Matrix{Float32}) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:282 [2] varm!(R::Matrix{Float32}, A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:309 [3] _varm(A::Matrix{Float32}, m::Matrix{Float32}, corrected::Bool, region::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:341 [4] varm(A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:339 [inlined] [5] _var(A::Matrix{Float32}, corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:386 [inlined] [6] var(A::Matrix{Float32}; corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:380 [inlined] [7] get_genotypes(file::String, G::Float64; method::String, Pi::Float64, estimatePi::Bool, G_is_marker_variance::Bool, df::Float64, estimate_variance::Bool, estimate_scale::Bool, constraint::Bool, separator::Char, header::Bool, double_precision::Bool, quality_control::Bool, MAF::Float64, missing_value::Float64, center::Bool, starting_value::Bool, annotations::Bool, multi_trait_sampler::Symbol, storage::Symbol) @ JWAS ~/.julia/packages/JWAS/AxFc6/src/1.JWAS/src/markers/readgenotypes.jl:390 [8] top-level scope @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_advanced_coverage.jl:190 [9] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [10] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_advanced_coverage.jl:190 [inlined] The delimiter in genotypes.txt is ','. The header (marker IDs) is provided in genotypes.txt. Missing values (9.0) are replaced by column means. Double precision MCMC: Error During Test at /home/pkgeval/.julia/packages/JWAS/AxFc6/test/unit/test_advanced_coverage.jl:208 Got exception outside of a @test MethodError: no method matching reducedim1(::Matrix{Float64}, ::Matrix{Float64}) The function `reducedim1` exists, but no method is defined for this combination of argument types. Closest candidates are: reducedim1(::Any) @ Base reducedim.jl:1229 Stacktrace: [1] centralize_sumabs2!(R::Matrix{Float64}, A::Matrix{Float64}, means::Matrix{Float64}) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:282 [2] varm!(R::Matrix{Float64}, A::Matrix{Float64}, m::Matrix{Float64}; corrected::Bool) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:309 [3] _varm(A::Matrix{Float64}, m::Matrix{Float64}, corrected::Bool, region::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:341 [4] varm(A::Matrix{Float64}, m::Matrix{Float64}; corrected::Bool, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:339 [inlined] [5] _var(A::Matrix{Float64}, corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:386 [inlined] [6] var(A::Matrix{Float64}; corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:380 [inlined] [7] get_genotypes(file::String, G::Float64; method::String, Pi::Float64, estimatePi::Bool, G_is_marker_variance::Bool, df::Float64, estimate_variance::Bool, estimate_scale::Bool, constraint::Bool, separator::Char, header::Bool, double_precision::Bool, quality_control::Bool, MAF::Float64, missing_value::Float64, center::Bool, starting_value::Bool, annotations::Bool, multi_trait_sampler::Symbol, storage::Symbol) @ JWAS ~/.julia/packages/JWAS/AxFc6/src/1.JWAS/src/markers/readgenotypes.jl:390 [8] top-level scope @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_advanced_coverage.jl:209 [9] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [10] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_advanced_coverage.jl:209 [inlined] The delimiter in genotypes.txt is ','. The header (marker IDs) is provided in genotypes.txt. Missing values (9.0) are replaced by column means. SEM causal_structure regression (issue #162): Error During Test at /home/pkgeval/.julia/packages/JWAS/AxFc6/test/unit/test_sem_issue162.jl:3 Got exception outside of a @test MethodError: no method matching reducedim1(::Matrix{Float32}, ::Matrix{Float32}) The function `reducedim1` exists, but no method is defined for this combination of argument types. Closest candidates are: reducedim1(::Any) @ Base reducedim.jl:1229 Stacktrace: [1] centralize_sumabs2!(R::Matrix{Float32}, A::Matrix{Float32}, means::Matrix{Float32}) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:282 [2] varm!(R::Matrix{Float32}, A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:309 [3] _varm(A::Matrix{Float32}, m::Matrix{Float32}, corrected::Bool, region::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:341 [4] varm(A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:339 [inlined] [5] _var(A::Matrix{Float32}, corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:386 [inlined] [6] var(A::Matrix{Float32}; corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:380 [inlined] [7] get_genotypes(file::String, G::Matrix{Float64}; method::String, Pi::Float64, estimatePi::Bool, G_is_marker_variance::Bool, df::Float64, estimate_variance::Bool, estimate_scale::Bool, constraint::Bool, separator::Char, header::Bool, double_precision::Bool, quality_control::Bool, MAF::Float64, missing_value::Float64, center::Bool, starting_value::Bool, annotations::Bool, multi_trait_sampler::Symbol, storage::Symbol) @ JWAS ~/.julia/packages/JWAS/AxFc6/src/1.JWAS/src/markers/readgenotypes.jl:390 [8] top-level scope @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_sem_issue162.jl:4 [9] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [10] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_sem_issue162.jl:11 [inlined] The delimiter in genotypes.txt is ','. The header (marker IDs) is provided in genotypes.txt. Missing values (9.0) are replaced by column means. non-lower-triangular errors: Error During Test at /home/pkgeval/.julia/packages/JWAS/AxFc6/test/unit/test_sem_comprehensive.jl:271 Got exception outside of a @test MethodError: no method matching reducedim1(::Matrix{Float32}, ::Matrix{Float32}) The function `reducedim1` exists, but no method is defined for this combination of argument types. Closest candidates are: reducedim1(::Any) @ Base reducedim.jl:1229 Stacktrace: [1] centralize_sumabs2!(R::Matrix{Float32}, A::Matrix{Float32}, means::Matrix{Float32}) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:282 [2] varm!(R::Matrix{Float32}, A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:309 [3] _varm(A::Matrix{Float32}, m::Matrix{Float32}, corrected::Bool, region::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:341 [4] varm(A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:339 [inlined] [5] _var(A::Matrix{Float32}, corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:386 [inlined] [6] var(A::Matrix{Float32}; corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:380 [inlined] [7] get_genotypes(file::String, G::Matrix{Float64}; method::String, Pi::Float64, estimatePi::Bool, G_is_marker_variance::Bool, df::Float64, estimate_variance::Bool, estimate_scale::Bool, constraint::Bool, separator::Char, header::Bool, double_precision::Bool, quality_control::Bool, MAF::Float64, missing_value::Float64, center::Bool, starting_value::Bool, annotations::Bool, multi_trait_sampler::Symbol, storage::Symbol) @ JWAS ~/.julia/packages/JWAS/AxFc6/src/1.JWAS/src/markers/readgenotypes.jl:390 [8] top-level scope @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_sem_comprehensive.jl:266 [9] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [10] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_sem_comprehensive.jl:272 [inlined] [11] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [12] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_sem_comprehensive.jl:274 [inlined] The delimiter in genotypes.txt is ','. The header (marker IDs) is provided in genotypes.txt. Missing values (9.0) are replaced by column means. single-trait with causal_structure errors: Error During Test at /home/pkgeval/.julia/packages/JWAS/AxFc6/test/unit/test_sem_comprehensive.jl:287 Got exception outside of a @test MethodError: no method matching reducedim1(::Matrix{Float32}, ::Matrix{Float32}) The function `reducedim1` exists, but no method is defined for this combination of argument types. Closest candidates are: reducedim1(::Any) @ Base reducedim.jl:1229 Stacktrace: [1] centralize_sumabs2!(R::Matrix{Float32}, A::Matrix{Float32}, means::Matrix{Float32}) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:282 [2] varm!(R::Matrix{Float32}, A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:309 [3] _varm(A::Matrix{Float32}, m::Matrix{Float32}, corrected::Bool, region::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:341 [4] varm(A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:339 [inlined] [5] _var(A::Matrix{Float32}, corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:386 [inlined] [6] var(A::Matrix{Float32}; corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:380 [inlined] [7] get_genotypes(file::String, G::Float64; method::String, Pi::Float64, estimatePi::Bool, G_is_marker_variance::Bool, df::Float64, estimate_variance::Bool, estimate_scale::Bool, constraint::Bool, separator::Char, header::Bool, double_precision::Bool, quality_control::Bool, MAF::Float64, missing_value::Float64, center::Bool, starting_value::Bool, annotations::Bool, multi_trait_sampler::Symbol, storage::Symbol) @ JWAS ~/.julia/packages/JWAS/AxFc6/src/1.JWAS/src/markers/readgenotypes.jl:390 [8] top-level scope @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_sem_comprehensive.jl:266 [9] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [10] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_sem_comprehensive.jl:288 [inlined] [11] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [12] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_sem_comprehensive.jl:288 [inlined] The delimiter in genotypes.txt is ','. The header (marker IDs) is provided in genotypes.txt. Missing values (9.0) are replaced by column means. constraints are set correctly: Error During Test at /home/pkgeval/.julia/packages/JWAS/AxFc6/test/unit/test_sem_comprehensive.jl:300 Got exception outside of a @test MethodError: no method matching reducedim1(::Matrix{Float32}, ::Matrix{Float32}) The function `reducedim1` exists, but no method is defined for this combination of argument types. Closest candidates are: reducedim1(::Any) @ Base reducedim.jl:1229 Stacktrace: [1] centralize_sumabs2!(R::Matrix{Float32}, A::Matrix{Float32}, means::Matrix{Float32}) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:282 [2] varm!(R::Matrix{Float32}, A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:309 [3] _varm(A::Matrix{Float32}, m::Matrix{Float32}, corrected::Bool, region::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:341 [4] varm(A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:339 [inlined] [5] _var(A::Matrix{Float32}, corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:386 [inlined] [6] var(A::Matrix{Float32}; corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:380 [inlined] [7] get_genotypes(file::String, G::Matrix{Float64}; method::String, Pi::Float64, estimatePi::Bool, G_is_marker_variance::Bool, df::Float64, estimate_variance::Bool, estimate_scale::Bool, constraint::Bool, separator::Char, header::Bool, double_precision::Bool, quality_control::Bool, MAF::Float64, missing_value::Float64, center::Bool, starting_value::Bool, annotations::Bool, multi_trait_sampler::Symbol, storage::Symbol) @ JWAS ~/.julia/packages/JWAS/AxFc6/src/1.JWAS/src/markers/readgenotypes.jl:390 [8] top-level scope @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_sem_comprehensive.jl:266 [9] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [10] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_sem_comprehensive.jl:301 [inlined] [11] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [12] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_sem_comprehensive.jl:303 [inlined] The delimiter in genotypes.txt is ','. The header (marker IDs) is provided in genotypes.txt. Missing values (9.0) are replaced by column means. SEM 2-trait integration with output verification: Error During Test at /home/pkgeval/.julia/packages/JWAS/AxFc6/test/unit/test_sem_comprehensive.jl:328 Got exception outside of a @test MethodError: no method matching reducedim1(::Matrix{Float32}, ::Matrix{Float32}) The function `reducedim1` exists, but no method is defined for this combination of argument types. Closest candidates are: reducedim1(::Any) @ Base reducedim.jl:1229 Stacktrace: [1] centralize_sumabs2!(R::Matrix{Float32}, A::Matrix{Float32}, means::Matrix{Float32}) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:282 [2] varm!(R::Matrix{Float32}, A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:309 [3] _varm(A::Matrix{Float32}, m::Matrix{Float32}, corrected::Bool, region::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:341 [4] varm(A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:339 [inlined] [5] _var(A::Matrix{Float32}, corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:386 [inlined] [6] var(A::Matrix{Float32}; corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:380 [inlined] [7] get_genotypes(file::String, G::Matrix{Float64}; method::String, Pi::Float64, estimatePi::Bool, G_is_marker_variance::Bool, df::Float64, estimate_variance::Bool, estimate_scale::Bool, constraint::Bool, separator::Char, header::Bool, double_precision::Bool, quality_control::Bool, MAF::Float64, missing_value::Float64, center::Bool, starting_value::Bool, annotations::Bool, multi_trait_sampler::Symbol, storage::Symbol) @ JWAS ~/.julia/packages/JWAS/AxFc6/src/1.JWAS/src/markers/readgenotypes.jl:390 [8] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_sem_comprehensive.jl:336 [inlined] [9] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [10] top-level scope @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_sem_comprehensive.jl:329 The delimiter in genotypes.txt is ','. The header (marker IDs) is provided in genotypes.txt. Missing values (9.0) are replaced by column means. SEM 3-trait integration: Error During Test at /home/pkgeval/.julia/packages/JWAS/AxFc6/test/unit/test_sem_comprehensive.jl:414 Got exception outside of a @test MethodError: no method matching reducedim1(::Matrix{Float32}, ::Matrix{Float32}) The function `reducedim1` exists, but no method is defined for this combination of argument types. Closest candidates are: reducedim1(::Any) @ Base reducedim.jl:1229 Stacktrace: [1] centralize_sumabs2!(R::Matrix{Float32}, A::Matrix{Float32}, means::Matrix{Float32}) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:282 [2] varm!(R::Matrix{Float32}, A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:309 [3] _varm(A::Matrix{Float32}, m::Matrix{Float32}, corrected::Bool, region::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:341 [4] varm(A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:339 [inlined] [5] _var(A::Matrix{Float32}, corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:386 [inlined] [6] var(A::Matrix{Float32}; corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:380 [inlined] [7] get_genotypes(file::String, G::Matrix{Float64}; method::String, Pi::Float64, estimatePi::Bool, G_is_marker_variance::Bool, df::Float64, estimate_variance::Bool, estimate_scale::Bool, constraint::Bool, separator::Char, header::Bool, double_precision::Bool, quality_control::Bool, MAF::Float64, missing_value::Float64, center::Bool, starting_value::Bool, annotations::Bool, multi_trait_sampler::Symbol, storage::Symbol) @ JWAS ~/.julia/packages/JWAS/AxFc6/src/1.JWAS/src/markers/readgenotypes.jl:390 [8] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_sem_comprehensive.jl:422 [inlined] [9] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [10] top-level scope @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_sem_comprehensive.jl:415 The delimiter in genotypes.txt is ','. The header (marker IDs) is provided in genotypes.txt. Missing values (9.0) are replaced by column means. SEM reproducibility with seed: Error During Test at /home/pkgeval/.julia/packages/JWAS/AxFc6/test/unit/test_sem_comprehensive.jl:474 Got exception outside of a @test MethodError: no method matching reducedim1(::Matrix{Float32}, ::Matrix{Float32}) The function `reducedim1` exists, but no method is defined for this combination of argument types. Closest candidates are: reducedim1(::Any) @ Base reducedim.jl:1229 Stacktrace: [1] centralize_sumabs2!(R::Matrix{Float32}, A::Matrix{Float32}, means::Matrix{Float32}) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:282 [2] varm!(R::Matrix{Float32}, A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:309 [3] _varm(A::Matrix{Float32}, m::Matrix{Float32}, corrected::Bool, region::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:341 [4] varm(A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:339 [inlined] [5] _var(A::Matrix{Float32}, corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:386 [inlined] [6] var(A::Matrix{Float32}; corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:380 [inlined] [7] get_genotypes(file::String, G::Matrix{Float64}; method::String, Pi::Float64, estimatePi::Bool, G_is_marker_variance::Bool, df::Float64, estimate_variance::Bool, estimate_scale::Bool, constraint::Bool, separator::Char, header::Bool, double_precision::Bool, quality_control::Bool, MAF::Float64, missing_value::Float64, center::Bool, starting_value::Bool, annotations::Bool, multi_trait_sampler::Symbol, storage::Symbol) @ JWAS ~/.julia/packages/JWAS/AxFc6/src/1.JWAS/src/markers/readgenotypes.jl:390 [8] (::var"#run_sem_with_seed#run_sem_with_seed##0"{DataFrame, String})(seed::Int64, folder::String) @ Main ~/.julia/packages/JWAS/AxFc6/test/unit/test_sem_comprehensive.jl:483 [9] top-level scope @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_sem_comprehensive.jl:475 [10] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [11] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/unit/test_sem_comprehensive.jl:500 [inlined] The delimiter in genotypes.txt is ','. The header (marker IDs) is provided in genotypes.txt. Missing values (9.0) are replaced by column means. Load from file with header: Error During Test at /home/pkgeval/.julia/packages/JWAS/AxFc6/test/runtests.jl:201 Got exception outside of a @test MethodError: no method matching reducedim1(::Matrix{Float32}, ::Matrix{Float32}) The function `reducedim1` exists, but no method is defined for this combination of argument types. Closest candidates are: reducedim1(::Any) @ Base reducedim.jl:1229 Stacktrace: [1] centralize_sumabs2!(R::Matrix{Float32}, A::Matrix{Float32}, means::Matrix{Float32}) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:282 [2] varm!(R::Matrix{Float32}, A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:309 [3] _varm(A::Matrix{Float32}, m::Matrix{Float32}, corrected::Bool, region::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:341 [4] varm(A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:339 [inlined] [5] _var(A::Matrix{Float32}, corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:386 [inlined] [6] var(A::Matrix{Float32}; corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:380 [inlined] [7] get_genotypes(file::String, G::Float64; method::String, Pi::Float64, estimatePi::Bool, G_is_marker_variance::Bool, df::Float64, estimate_variance::Bool, estimate_scale::Bool, constraint::Bool, separator::Char, header::Bool, double_precision::Bool, quality_control::Bool, MAF::Float64, missing_value::Float64, center::Bool, starting_value::Bool, annotations::Bool, multi_trait_sampler::Symbol, storage::Symbol) @ JWAS ~/.julia/packages/JWAS/AxFc6/src/1.JWAS/src/markers/readgenotypes.jl:390 [8] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/runtests.jl:202 [inlined] [9] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [10] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/runtests.jl:202 [inlined] [11] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [12] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/runtests.jl:199 [inlined] [13] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [14] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/runtests.jl:71 [inlined] [15] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [16] top-level scope @ ~/.julia/packages/JWAS/AxFc6/test/runtests.jl:70 The delimiter in genotypes.txt is ','. The header (marker IDs) is provided in genotypes.txt. Missing values (9.0) are replaced by column means. Load with different methods: Error During Test at /home/pkgeval/.julia/packages/JWAS/AxFc6/test/runtests.jl:212 Got exception outside of a @test MethodError: no method matching reducedim1(::Matrix{Float32}, ::Matrix{Float32}) The function `reducedim1` exists, but no method is defined for this combination of argument types. Closest candidates are: reducedim1(::Any) @ Base reducedim.jl:1229 Stacktrace: [1] centralize_sumabs2!(R::Matrix{Float32}, A::Matrix{Float32}, means::Matrix{Float32}) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:282 [2] varm!(R::Matrix{Float32}, A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:309 [3] _varm(A::Matrix{Float32}, m::Matrix{Float32}, corrected::Bool, region::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:341 [4] varm(A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:339 [inlined] [5] _var(A::Matrix{Float32}, corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:386 [inlined] [6] var(A::Matrix{Float32}; corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:380 [inlined] [7] get_genotypes(file::String, G::Float64; method::String, Pi::Float64, estimatePi::Bool, G_is_marker_variance::Bool, df::Float64, estimate_variance::Bool, estimate_scale::Bool, constraint::Bool, separator::Char, header::Bool, double_precision::Bool, quality_control::Bool, MAF::Float64, missing_value::Float64, center::Bool, starting_value::Bool, annotations::Bool, multi_trait_sampler::Symbol, storage::Symbol) @ JWAS ~/.julia/packages/JWAS/AxFc6/src/1.JWAS/src/markers/readgenotypes.jl:390 [8] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/runtests.jl:215 [inlined] [9] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [10] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/runtests.jl:213 [inlined] [11] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [12] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/runtests.jl:199 [inlined] [13] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [14] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/runtests.jl:71 [inlined] [15] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [16] top-level scope @ ~/.julia/packages/JWAS/AxFc6/test/runtests.jl:70 The delimiter in genotypes.txt is ','. The header (marker IDs) is provided in genotypes.txt. Missing values (9.0) are replaced by column means. Quality control: Error During Test at /home/pkgeval/.julia/packages/JWAS/AxFc6/test/runtests.jl:222 Got exception outside of a @test MethodError: no method matching reducedim1(::Matrix{Float32}, ::Matrix{Float32}) The function `reducedim1` exists, but no method is defined for this combination of argument types. Closest candidates are: reducedim1(::Any) @ Base reducedim.jl:1229 Stacktrace: [1] centralize_sumabs2!(R::Matrix{Float32}, A::Matrix{Float32}, means::Matrix{Float32}) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:282 [2] varm!(R::Matrix{Float32}, A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:309 [3] _varm(A::Matrix{Float32}, m::Matrix{Float32}, corrected::Bool, region::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:341 [4] varm(A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:339 [inlined] [5] _var(A::Matrix{Float32}, corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:386 [inlined] [6] var(A::Matrix{Float32}; corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:380 [inlined] [7] get_genotypes(file::String, G::Float64; method::String, Pi::Float64, estimatePi::Bool, G_is_marker_variance::Bool, df::Float64, estimate_variance::Bool, estimate_scale::Bool, constraint::Bool, separator::Char, header::Bool, double_precision::Bool, quality_control::Bool, MAF::Float64, missing_value::Float64, center::Bool, starting_value::Bool, annotations::Bool, multi_trait_sampler::Symbol, storage::Symbol) @ JWAS ~/.julia/packages/JWAS/AxFc6/src/1.JWAS/src/markers/readgenotypes.jl:390 [8] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/runtests.jl:223 [inlined] [9] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [10] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/runtests.jl:223 [inlined] [11] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [12] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/runtests.jl:199 [inlined] [13] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [14] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/runtests.jl:71 [inlined] [15] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [16] top-level scope @ ~/.julia/packages/JWAS/AxFc6/test/runtests.jl:70 The delimiter in pedigree.txt is ','. Pedigree information: #individuals: 12 #sires: 4 #dams: 5 #founders: 3 The delimiter in pedigree.txt is ','. Pedigree information: #individuals: 12 #sires: 4 #dams: 5 #founders: 3 The delimiter in genotypes.txt is ','. The header (marker IDs) is provided in genotypes.txt. Missing values (9.0) are replaced by column means. Single-trait BayesC: Error During Test at /home/pkgeval/.julia/packages/JWAS/AxFc6/test/runtests.jl:265 Got exception outside of a @test MethodError: no method matching reducedim1(::Matrix{Float32}, ::Matrix{Float32}) The function `reducedim1` exists, but no method is defined for this combination of argument types. Closest candidates are: reducedim1(::Any) @ Base reducedim.jl:1229 Stacktrace: [1] centralize_sumabs2!(R::Matrix{Float32}, A::Matrix{Float32}, means::Matrix{Float32}) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:282 [2] varm!(R::Matrix{Float32}, A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:309 [3] _varm(A::Matrix{Float32}, m::Matrix{Float32}, corrected::Bool, region::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:341 [4] varm(A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:339 [inlined] [5] _var(A::Matrix{Float32}, corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:386 [inlined] [6] var(A::Matrix{Float32}; corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:380 [inlined] [7] get_genotypes(file::String, G::Float64; method::String, Pi::Float64, estimatePi::Bool, G_is_marker_variance::Bool, df::Float64, estimate_variance::Bool, estimate_scale::Bool, constraint::Bool, separator::Char, header::Bool, double_precision::Bool, quality_control::Bool, MAF::Float64, missing_value::Float64, center::Bool, starting_value::Bool, annotations::Bool, multi_trait_sampler::Symbol, storage::Symbol) @ JWAS ~/.julia/packages/JWAS/AxFc6/src/1.JWAS/src/markers/readgenotypes.jl:390 [8] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/runtests.jl:266 [inlined] [9] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [10] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/runtests.jl:266 [inlined] [11] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [12] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/runtests.jl:260 [inlined] [13] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [14] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/runtests.jl:71 [inlined] [15] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [16] top-level scope @ ~/.julia/packages/JWAS/AxFc6/test/runtests.jl:70 The delimiter in genotypes.txt is ','. The header (marker IDs) is provided in genotypes.txt. Missing values (9.0) are replaced by column means. Output folder creation: Error During Test at /home/pkgeval/.julia/packages/JWAS/AxFc6/test/runtests.jl:285 Got exception outside of a @test MethodError: no method matching reducedim1(::Matrix{Float32}, ::Matrix{Float32}) The function `reducedim1` exists, but no method is defined for this combination of argument types. Closest candidates are: reducedim1(::Any) @ Base reducedim.jl:1229 Stacktrace: [1] centralize_sumabs2!(R::Matrix{Float32}, A::Matrix{Float32}, means::Matrix{Float32}) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:282 [2] varm!(R::Matrix{Float32}, A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:309 [3] _varm(A::Matrix{Float32}, m::Matrix{Float32}, corrected::Bool, region::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:341 [4] varm(A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:339 [inlined] [5] _var(A::Matrix{Float32}, corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:386 [inlined] [6] var(A::Matrix{Float32}; corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:380 [inlined] [7] get_genotypes(file::String, G::Float64; method::String, Pi::Float64, estimatePi::Bool, G_is_marker_variance::Bool, df::Float64, estimate_variance::Bool, estimate_scale::Bool, constraint::Bool, separator::Char, header::Bool, double_precision::Bool, quality_control::Bool, MAF::Float64, missing_value::Float64, center::Bool, starting_value::Bool, annotations::Bool, multi_trait_sampler::Symbol, storage::Symbol) @ JWAS ~/.julia/packages/JWAS/AxFc6/src/1.JWAS/src/markers/readgenotypes.jl:390 [8] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/runtests.jl:286 [inlined] [9] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [10] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/runtests.jl:286 [inlined] [11] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [12] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/runtests.jl:260 [inlined] [13] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [14] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/runtests.jl:71 [inlined] [15] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [16] top-level scope @ ~/.julia/packages/JWAS/AxFc6/test/runtests.jl:70 The delimiter in genotypes.txt is ','. The header (marker IDs) is provided in genotypes.txt. Missing values (9.0) are replaced by column means. Reproducibility with seed: Error During Test at /home/pkgeval/.julia/packages/JWAS/AxFc6/test/runtests.jl:302 Got exception outside of a @test MethodError: no method matching reducedim1(::Matrix{Float32}, ::Matrix{Float32}) The function `reducedim1` exists, but no method is defined for this combination of argument types. Closest candidates are: reducedim1(::Any) @ Base reducedim.jl:1229 Stacktrace: [1] centralize_sumabs2!(R::Matrix{Float32}, A::Matrix{Float32}, means::Matrix{Float32}) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:282 [2] varm!(R::Matrix{Float32}, A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:309 [3] _varm(A::Matrix{Float32}, m::Matrix{Float32}, corrected::Bool, region::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:341 [4] varm(A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:339 [inlined] [5] _var(A::Matrix{Float32}, corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:386 [inlined] [6] var(A::Matrix{Float32}; corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:380 [inlined] [7] get_genotypes(file::String, G::Float64; method::String, Pi::Float64, estimatePi::Bool, G_is_marker_variance::Bool, df::Float64, estimate_variance::Bool, estimate_scale::Bool, constraint::Bool, separator::Char, header::Bool, double_precision::Bool, quality_control::Bool, MAF::Float64, missing_value::Float64, center::Bool, starting_value::Bool, annotations::Bool, multi_trait_sampler::Symbol, storage::Symbol) @ JWAS ~/.julia/packages/JWAS/AxFc6/src/1.JWAS/src/markers/readgenotypes.jl:390 [8] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/runtests.jl:303 [inlined] [9] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [10] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/runtests.jl:303 [inlined] [11] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [12] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/runtests.jl:260 [inlined] [13] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [14] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/runtests.jl:71 [inlined] [15] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [16] top-level scope @ ~/.julia/packages/JWAS/AxFc6/test/runtests.jl:70 The delimiter in genotypes.txt is ','. The header (marker IDs) is provided in genotypes.txt. Missing values (9.0) are replaced by column means. Model frequency calculation: Error During Test at /home/pkgeval/.julia/packages/JWAS/AxFc6/test/runtests.jl:333 Got exception outside of a @test MethodError: no method matching reducedim1(::Matrix{Float32}, ::Matrix{Float32}) The function `reducedim1` exists, but no method is defined for this combination of argument types. Closest candidates are: reducedim1(::Any) @ Base reducedim.jl:1229 Stacktrace: [1] centralize_sumabs2!(R::Matrix{Float32}, A::Matrix{Float32}, means::Matrix{Float32}) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:282 [2] varm!(R::Matrix{Float32}, A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:309 [3] _varm(A::Matrix{Float32}, m::Matrix{Float32}, corrected::Bool, region::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:341 [4] varm(A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:339 [inlined] [5] _var(A::Matrix{Float32}, corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:386 [inlined] [6] var(A::Matrix{Float32}; corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:380 [inlined] [7] get_genotypes(file::String, G::Float64; method::String, Pi::Float64, estimatePi::Bool, G_is_marker_variance::Bool, df::Float64, estimate_variance::Bool, estimate_scale::Bool, constraint::Bool, separator::Char, header::Bool, double_precision::Bool, quality_control::Bool, MAF::Float64, missing_value::Float64, center::Bool, starting_value::Bool, annotations::Bool, multi_trait_sampler::Symbol, storage::Symbol) @ JWAS ~/.julia/packages/JWAS/AxFc6/src/1.JWAS/src/markers/readgenotypes.jl:390 [8] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/runtests.jl:334 [inlined] [9] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [10] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/runtests.jl:334 [inlined] [11] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [12] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/runtests.jl:327 [inlined] [13] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [14] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/runtests.jl:71 [inlined] [15] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [16] top-level scope @ ~/.julia/packages/JWAS/AxFc6/test/runtests.jl:70 The folder missing_test is created to save results. Checking phenotypes... Individual IDs (strings) are provided in the first column of the phenotypic data. Predicted values for individuals of interest will be obtained as the summation of Any[] (Note that genomic data is always included for now).Default or user-defined prediction equation are not available. Phenotypes for 4 observations are used in the analysis.These individual IDs are saved in the file missing_test/IDs_for_individuals_with_phenotypes.txt. A Linear Mixed Model was build using model equations: y1 = intercept Model Information: Term C/F F/R nLevels intercept factor fixed 1 MCMC Information: chain_length 10 burnin 0 starting_value true printout_frequency 11 output_samples_frequency 1 constraint on residual variance false missing_phenotypes true update_priors_frequency 0 seed 123 Hyper-parameters Information: residual variances: 1.000 Genomic Information: Degree of freedom for hyper-parameters: residual variances: 4.000 The file missing_test/MCMC_samples_residual_variance.txt is created to save MCMC samples for residual_variance. The version of Julia and Platform in use: Julia Version 1.14.0-DEV.3055 Build Info: Commit 7e75a8061a* (2026-08-27 09:46 UTC) GC: Built with stock GC Platform Info: OS: Linux (x86_64-unknown-linux-gnu) CPU: 128 × AMD EPYC 7502 32-Core Processor (znver2) WORD_SIZE: 64 LLVM: libLLVM-22.1.8 (ORCJIT, znver2) Threads: 1 default, 0 interactive, 1 GC (on 1 virtual cores) Environment: JULIA_CPU_THREADS = 1 JULIA_NUM_PRECOMPILE_TASKS = 1 JULIA_PKG_PRECOMPILE_AUTO = 0 JULIA_PKGEVAL = true JULIA_DEPOT_PATH = /home/pkgeval/.julia:/usr/local/share/julia: JULIA_NUM_THREADS = 1 JULIA_LOAD_PATH = @:/tmp/jl_g0vHag The analysis has finished. Results are saved in the returned variable and text files. MCMC samples are saved in text files. The delimiter in genotypes.txt is ','. The header (marker IDs) is provided in genotypes.txt. Missing values (9.0) are replaced by column means. Single precision (default): Error During Test at /home/pkgeval/.julia/packages/JWAS/AxFc6/test/runtests.jl:389 Got exception outside of a @test MethodError: no method matching reducedim1(::Matrix{Float32}, ::Matrix{Float32}) The function `reducedim1` exists, but no method is defined for this combination of argument types. Closest candidates are: reducedim1(::Any) @ Base reducedim.jl:1229 Stacktrace: [1] centralize_sumabs2!(R::Matrix{Float32}, A::Matrix{Float32}, means::Matrix{Float32}) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:282 [2] varm!(R::Matrix{Float32}, A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:309 [3] _varm(A::Matrix{Float32}, m::Matrix{Float32}, corrected::Bool, region::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:341 [4] varm(A::Matrix{Float32}, m::Matrix{Float32}; corrected::Bool, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:339 [inlined] [5] _var(A::Matrix{Float32}, corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:386 [inlined] [6] var(A::Matrix{Float32}; corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:380 [inlined] [7] get_genotypes(file::String, G::Float64; method::String, Pi::Float64, estimatePi::Bool, G_is_marker_variance::Bool, df::Float64, estimate_variance::Bool, estimate_scale::Bool, constraint::Bool, separator::Char, header::Bool, double_precision::Bool, quality_control::Bool, MAF::Float64, missing_value::Float64, center::Bool, starting_value::Bool, annotations::Bool, multi_trait_sampler::Symbol, storage::Symbol) @ JWAS ~/.julia/packages/JWAS/AxFc6/src/1.JWAS/src/markers/readgenotypes.jl:390 [8] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/runtests.jl:390 [inlined] [9] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [10] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/runtests.jl:390 [inlined] [11] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [12] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/runtests.jl:387 [inlined] [13] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [14] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/runtests.jl:71 [inlined] [15] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [16] top-level scope @ ~/.julia/packages/JWAS/AxFc6/test/runtests.jl:70 The delimiter in genotypes.txt is ','. The header (marker IDs) is provided in genotypes.txt. Missing values (9.0) are replaced by column means. Double precision: Error During Test at /home/pkgeval/.julia/packages/JWAS/AxFc6/test/runtests.jl:395 Got exception outside of a @test MethodError: no method matching reducedim1(::Matrix{Float64}, ::Matrix{Float64}) The function `reducedim1` exists, but no method is defined for this combination of argument types. Closest candidates are: reducedim1(::Any) @ Base reducedim.jl:1229 Stacktrace: [1] centralize_sumabs2!(R::Matrix{Float64}, A::Matrix{Float64}, means::Matrix{Float64}) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:282 [2] varm!(R::Matrix{Float64}, A::Matrix{Float64}, m::Matrix{Float64}; corrected::Bool) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:309 [3] _varm(A::Matrix{Float64}, m::Matrix{Float64}, corrected::Bool, region::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:341 [4] varm(A::Matrix{Float64}, m::Matrix{Float64}; corrected::Bool, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:339 [inlined] [5] _var(A::Matrix{Float64}, corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:386 [inlined] [6] var(A::Matrix{Float64}; corrected::Bool, mean::Nothing, dims::Int64) @ Statistics ~/.julia/packages/Statistics/gbcbG/src/Statistics.jl:380 [inlined] [7] get_genotypes(file::String, G::Float64; method::String, Pi::Float64, estimatePi::Bool, G_is_marker_variance::Bool, df::Float64, estimate_variance::Bool, estimate_scale::Bool, constraint::Bool, separator::Char, header::Bool, double_precision::Bool, quality_control::Bool, MAF::Float64, missing_value::Float64, center::Bool, starting_value::Bool, annotations::Bool, multi_trait_sampler::Symbol, storage::Symbol) @ JWAS ~/.julia/packages/JWAS/AxFc6/src/1.JWAS/src/markers/readgenotypes.jl:390 [8] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/runtests.jl:396 [inlined] [9] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [10] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/runtests.jl:396 [inlined] [11] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [12] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/runtests.jl:387 [inlined] [13] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [14] macro expansion @ ~/.julia/packages/JWAS/AxFc6/test/runtests.jl:71 [inlined] [15] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2247 [inlined] [16] top-level scope @ ~/.julia/packages/JWAS/AxFc6/test/runtests.jl:70 [ Info: Skipping integration tests (set RUN_INTEGRATION_TESTS=true to run) Test Summary: | Pass Fail Error Total Time JWAS.jl Full Test Suite | 636 10 73 719 24m44.2s Unit Tests | 636 10 73 719 24m44.1s Memory Guardrails | 27 2 2 31 2m13.9s Memory guardrails: estimator and policy | 25 25 13.7s Memory guardrails: runMCMC integration | 2 2 2 6 1m56.8s runMCMC throws early in :error mode when guard threshold is tiny | 1 1 14.2s runMCMC proceeds in :off mode with same threshold | 1 1 0.0s BayesABC Block Memory | 1 1 7.1s Streaming Genotype Codec | 5 1 6 1m40.6s Streaming genotype codec and BayesC equivalence | 5 1 6 1m40.6s prepare + load + decode | 2 1 3 1.5s runMCMC dense vs stream | 3 3 1m29.0s Streaming Constraints | 4 4 6.5s Streaming Prepare (Low Memory) | 19 1 20 8.7s Streaming low-memory prepare behavior | 19 1 20 8.7s QC and decode parity vs dense | 1 1 0.1s xpRinvx parity when center=false | 5 5 0.1s cleanup_temp toggles stage artifact removal | 2 2 0.2s disk guard failure path | 2 2 0.3s auto mode selects dense vs lowmem by threshold | 10 10 0.8s Annotated BayesC | 119 2 121 1m58.4s Annotated BayesC API and validation | 101 1 102 1m36.8s rejects unsupported methods | 2 2 2.6s rejects invalid multi_trait_sampler values | 2 2 0.0s rejects annotation row mismatches | 2 2 0.0s filters annotations with QC and prepends intercept | 1 1 2.0s forces estimatePi for annotations | 4 4 5.5s rejects constant annotation columns | 2 2 0.2s rejects collinear annotation columns | 2 2 0.0s streaming filters raw-marker annotations with backend QC | 5 5 1.5s annotated streaming rejects legacy backends without raw marker mapping | 2 2 0.7s annotated BayesC startup initializes probit intercept from starting Pi | 24 24 4.3s annotation sampler uses standard probit latent variance | 5 5 3.0s single-trait annotated BayesC uses coordinate probit update with shrunken slopes | 5 5 0.3s single-trait annotated BayesC leaves intercept-only annotation variance unchanged | 1 1 0.0s genetic-to-marker variance setup accepts marker-level BayesC priors | 1 1 1.7s BayesABC rejects mismatched pi vector length | 3 3 0.6s initializes dense 2-trait annotated BayesC state from a joint Pi prior | 10 10 6.4s stores explicit multi-trait sampler selection on annotated BayesC genotypes | 1 1 0.0s defaults annotated multi-trait BayesC sampler to I and preserves explicit auto | 2 2 0.0s rejects explicit multi-trait sampler overrides in single-trait BayesC builds | 2 2 0.1s accepts explicit auto on single-trait BayesC builds and runs | 1 1 7.1s rejects annotated multi-trait BayesC models with trait counts other than 2 | 2 2 0.1s rejects annotated 2-trait BayesC startup priors without shared-state mass | 2 2 0.0s rebuilds annotated BayesC state when the same genotype object is reused across trait counts | 11 11 2.1s rejects reusing a joint-Pi annotated BayesC genotype in a single-trait build | 4 4 0.0s rejects unsupported 2-trait annotated BayesC runtime modes explicitly | 6 6 58.5s Standard BayesC preserves scalar pi output | 4 4 0.7s Annotated BayesC dense run | 1 1 4.3s Annotated BayesC fast_blocks run | 4 4 9.0s Annotated BayesC independent fast_blocks run | 6 6 5.3s Annotated BayesC streaming run | 4 4 0.9s Annotated BayesR | 111 111 33.2s set_random (Random Effects) | 14 14 31.4s Solvers (Jacobi, Gauss-Seidel, Gibbs) | 7 7 8.4s Output and EBV | 3 3 0.2s outputEBV and EBV results | 2 2 0.1s EBV output with genotypes | 1 1 0.1s EBV output with heritability | 1 1 0.0s outputMCMCsamples for location parameters | 1 1 0.0s Pedigree Algorithms | 23 23 6.4s Input Validation | 2 3 5 1.7s Input Validation | 2 3 5 0.2s Invalid Bayesian method | 1 1 0.0s Single-step requires genotypes | 1 1 0.0s output_samples_frequency validation | 1 1 0.0s Describe model | 1 1 0.0s Multiple Bayesian methods load correctly | 1 1 0.0s Single-step Analysis | 3 3 22.0s Single-step analysis | 3 3 21.9s BayesC accepts CSV inline-string IDs | 1 1 1.4s BayesC accepts multiple genotype categories | 1 1 0.0s Annotated BayesC and BayesR accept multiple genotype categories | 1 1 20.0s Multi-trait MCMC | 46 11 57 1m51.4s multi-trait BayesR trait class conditionals | 4 4 0.9s Multi-trait BayesC | 1 1 0.1s Multi-trait BayesC sampler default and auto selection | 1 1 0.0s Multi-trait annotated BayesC | 1 1 8.1s Multi-trait annotated BayesR dense run | 5 5 3.9s Multi-trait annotated BayesC sampler II override | 1 1 2 4.4s Multi-trait BayesC dense sampler II run | 1 1 7.8s Multi-trait BayesC fast_blocks run | 1 1 9.9s Multi-trait BayesC fast_blocks sampler II run | 1 1 7.8s Multi-trait annotated BayesC fast_blocks sampler II run | 1 1 7.1s Multi-trait BayesC independent fast_blocks sampler I run | 5 5 11.2s Multi-trait BayesC independent fast_blocks sampler II run | 5 5 8.9s Multi-trait annotated BayesC independent fast_blocks sampler I run | 5 5 9.1s Multi-trait annotated BayesC independent fast_blocks sampler II run | 5 5 7.7s Multi-trait annotated BayesC samplers share the same target posterior | 3 3 6.4s Multi-trait BayesC samplers share the same target posterior | 3 3 4.4s Multi-trait BayesC block sampler II matches dense sampler II on a one-marker case | 4 4 8.4s Multi-trait BayesC block wrapper dispatch | 6 6 0.2s Multi-trait RR-BLUP | 1 1 0.0s Multi-trait with pedigree | 1 1 4.6s Multi-trait with i.i.d. random effect | 1 1 0.0s BayesB/BayesA/BayesL/GBLUP Methods | 4 4 0.2s BayesB single-trait | 1 1 0.0s BayesA single-trait (converted to BayesB with π=0) | 1 1 0.0s BayesL (Lasso) single-trait | 1 1 0.0s GBLUP | 1 1 0.1s BayesR | 14 10 24 8.1s BayesR validation | 2 7 9 4.3s single-trait dense BayesR genotype loads | 1 1 1.7s BayesR rejects bad Pi length | 1 1 0.0s BayesR fast_blocks gets past validation | 1 1 0.0s BayesR fast_blocks=1 means block size 1 | 1 1 0.1s BayesR copies caller Pi input | 1 1 0.0s BayesR still rejects stream, multi-trait, and RRM | 2 2 4 2.4s stream is rejected | 2 2 0.5s unannotated multi-trait is rejected | 1 1 1.8s RRM is rejected | 1 1 0.0s BayesR dense sampler | 2 2 0.9s BayesR block sampler | 2 2 1.8s BayesR fast-block repetition schedule | 5 5 0.0s BayesR variance sufficient statistics | 2 2 0.1s BayesR variance update matches direct ssq formula | 1 1 0.6s BayesR single-trait run | 1 1 0.0s BayesR estimatePi output | 1 1 0.0s BayesR fast_blocks dispatch | 1 1 0.0s BayesR parity helpers | 46 8 2 56 13m08.6s BayesR parity summary helpers | 3 3 5.2s BayesR parity pi labels normalize to class names | 1 1 0.3s BayesR parity dataset export | 3 3 3.5s BayesR parity initial state and trace schema | 4 4 1.5s BayesR parity comparator | 2 2 12.5s BayesR fixed-pi trace comparator | 2 2 1.5s BayesR generic trace comparator | 4 4 0.1s BayesR replay draw export and comparison schema | 4 4 2.0s BayesR multiseed parity summary helper | 3 3 1.1s BayesR fixed-hyperparameter summary helper | 3 3 1.5s BayesR runtime metadata helper | 3 3 0.3s BayesR within-method multiseed summary helper | 3 3 0.2s BayesR debug default-blocks single-rep benchmark mode | 5 5 2m22.8s BayesR long-chain schedule comparison benchmark mode | 5 5 3m32.3s BayesC and BayesR fast-block benchmark mode | 3 1 4 3m35.9s Annotated BayesR production benchmark mode | 1 5 1 7 3m06.0s GWAS Window Analysis | 1 1 0.3s Misc Coverage (describe, priors, datasets) | 100 4 104 1m16.0s Datasets module | 14 14 0.8s Reproducibility across methods | 1 1 0.0s outputMCMCsamples for multiple terms | 1 1 0.0s Covariate in model | 2 2 0.2s showMME | 1 1 0.0s Multi-trait describe | 1 1 0.0s Independent blocks API and explicit block starts | 1 1 0.0s Independent block weighted crossproduct assumption | 4 4 0.2s Simulated annotations multitrait benchmark contract | 79 79 1m13.3s Advanced Coverage (multi-trait methods, constraints, missing) | 10 10 2.8s Multi-trait BayesB | 1 1 0.0s Multi-trait BayesL | 1 1 0.0s Multi-trait GBLUP | 1 1 0.0s Multi-trait BayesC with G constraint (mega-trait) | 1 1 0.1s Multi-trait with missing phenotypes | 1 1 0.0s Multi-trait BayesC with Pi estimation | 1 1 0.1s Single-trait BayesC with estimate_scale | 1 1 0.1s Multi-trait EBV output | 1 1 0.0s Single-trait with weights (heterogeneous residuals) | 1 1 0.0s Double precision MCMC | 1 1 2.3s SEM regression (issue #162) | 1 1 1.2s SEM causal_structure regression (issue #162) | 1 1 1.2s SEM Comprehensive Tests | 65 6 71 16.3s tranform_lambda | 24 24 0.1s compute_indirect_effect | 8 8 1.5s get_sparse_Y_FSM | 6 6 1.3s get_sparse_Y_FRM | 10 10 1.2s get_Λ sampling | 17 17 3.0s SEM input validation | 3 3 0.1s non-lower-triangular errors | 1 1 0.0s single-trait with causal_structure errors | 1 1 0.0s constraints are set correctly | 1 1 0.0s SEM 2-trait integration with output verification | 1 1 0.0s SEM 3-trait integration | 1 1 0.0s SEM reproducibility with seed | 1 1 2.4s Model Building | 14 14 0.2s Genotype Loading | 3 3 0.2s Load from file with header | 1 1 0.1s Load with different methods | 1 1 0.0s Quality control | 1 1 0.1s Pedigree Module | 16 16 0.0s MCMC Functionality | 3 3 0.1s Single-trait BayesC | 1 1 0.0s Output folder creation | 1 1 0.0s Reproducibility with seed | 1 1 0.0s GWAS Module | 1 1 0.0s Model frequency calculation | 1 1 0.0s Edge Cases | 3 3 0.1s Data Types | 2 2 0.1s Single precision (default) | 1 1 0.1s Double precision | 1 1 0.0s RNG of the outermost testset: Xoshiro(0x48ee337bb0d56c5a, 0xffe83bffb11049ac, 0xb1a287a623397079, 0x67d6449d9b0d980f, 0x97af6e08b184a424) ERROR: LoadError: Some tests did not pass: 636 passed, 10 failed, 73 errored, 0 broken. in expression starting at /home/pkgeval/.julia/packages/JWAS/AxFc6/test/runtests.jl:65 Testing failed after 1509.19s ERROR: LoadError: Package JWAS errored during testing Stacktrace: [1] pkgerror(msg::String) @ Pkg.Types /opt/julia/share/julia/stdlib/v1.14/Pkg/src/Types.jl:68 [2] test(ctx::Pkg.Types.Context, pkgs::Vector{PackageSpec}; coverage::Bool, julia_args::Cmd, test_args::Cmd, test_fn::Nothing, force_latest_compatible_version::Bool, allow_earlier_backwards_compatible_versions::Bool, allow_reresolve::Bool) @ Pkg.Operations /opt/julia/share/julia/stdlib/v1.14/Pkg/src/Operations.jl:3283 [3] test(ctx::Pkg.Types.Context, pkgs::Vector{PackageSpec}; coverage::Bool, test_fn::Nothing, julia_args::Cmd, test_args::Cmd, force_latest_compatible_version::Bool, allow_earlier_backwards_compatible_versions::Bool, allow_reresolve::Bool, kwargs::@Kwargs{io::IOContext{IO}}) @ Pkg.API /opt/julia/share/julia/stdlib/v1.14/Pkg/src/API.jl:587 [4] test(pkgs::Vector{PackageSpec}; io::IOContext{IO}, kwargs::@Kwargs{julia_args::Cmd}) @ Pkg.API /opt/julia/share/julia/stdlib/v1.14/Pkg/src/API.jl:172 [5] test(pkgs::Vector{String}; kwargs::@Kwargs{julia_args::Cmd}) @ Pkg.API /opt/julia/share/julia/stdlib/v1.14/Pkg/src/API.jl:160 [6] test(pkg::String; kwargs::@Kwargs{julia_args::Cmd}) @ Pkg.API /opt/julia/share/julia/stdlib/v1.14/Pkg/src/API.jl:159 [inlined] [7] top-level scope @ /PkgEval.jl/scripts/evaluate.jl:223 in expression starting at /PkgEval.jl/scripts/evaluate.jl:214 PkgEval failed after 2329.57s: package fails to precompile