Package evaluation to test CalibrateEmulateSample on Julia 1.14.0-DEV.2311 (d99fded7bf*) started at 2026-06-10T06:14:50.673 ################################################################################ # Set-up # Installing PkgEval dependencies (TestEnv)... Activating project at `~/.julia/environments/v1.14` Set-up completed after 16.39s ################################################################################ # Installation # Installing CalibrateEmulateSample... Resolving package versions... Installed libass_jll ─────────────────────── v0.17.4+0 Installed libaom_jll ─────────────────────── v3.13.3+0 Installed CommonWorldInvalidations ───────── v1.0.0 Installed HarfBuzz_jll ───────────────────── v8.5.1+0 Installed Bzip2_jll ──────────────────────── v1.0.9+0 Installed Libuuid_jll ────────────────────── v2.42.0+0 Installed MKL_jll ────────────────────────── v2025.2.0+0 Installed SIMDTypes ──────────────────────── v0.1.0 Installed OrderedCollections ─────────────── v1.8.2 Installed Functors ───────────────────────── v0.5.2 Installed Cairo_jll ──────────────────────── v1.18.7+0 Installed Glossaries ─────────────────────── v0.1.1 Installed Optim ──────────────────────────── v1.13.3 Installed Nullables ──────────────────────── v1.0.0 Installed Graphite2_jll ──────────────────── v1.3.15+0 Installed SimpleWeightedGraphs ───────────── v1.5.1 Installed Manopt ─────────────────────────── v0.5.39 Installed RandomFeatures ─────────────────── v0.3.5 Installed UnsafePointers ─────────────────── v1.0.0 Installed CondaPkg ───────────────────────── v0.2.36 Installed CpuId ──────────────────────────── v0.3.1 Installed ElasticArrays ──────────────────── v1.2.12 Installed Xorg_libpciaccess_jll ──────────── v0.19.0+0 Installed InitialValues ──────────────────── v0.3.1 Installed ArgCheck ───────────────────────── v2.5.0 Installed Distances ──────────────────────── v0.10.12 Installed Pidfile ────────────────────────── v1.3.0 Installed OpenSpecFun_jll ────────────────── v0.5.6+0 Installed Fontconfig_jll ─────────────────── v2.17.1+0 Installed NaNMath ────────────────────────── v1.1.3 Installed StaticArrayInterface ───────────── v1.10.0 Installed QuadGK ─────────────────────────── v2.11.3 Installed Opus_jll ───────────────────────── v1.6.1+0 Installed ManifoldsBase ──────────────────── v2.4.0 Installed WoodburyMatrices ───────────────── v1.1.0 Installed libva_jll ──────────────────────── v2.23.0+0 Installed Xorg_libxcb_jll ────────────────── v1.17.1+0 Installed Arpack ─────────────────────────── v0.5.4 Installed Tables ─────────────────────────── v1.12.1 Installed EnsembleKalmanProcesses ────────── v2.7.1 Installed Ogg_jll ────────────────────────── v1.3.6+0 Installed NLSolversBase ──────────────────── v7.10.0 Installed InverseFunctions ───────────────── v0.1.17 Installed Reexport ───────────────────────── v1.2.2 Installed EnumX ──────────────────────────── v1.0.7 Installed GaussianRandomFields ───────────── v2.2.7 Installed FFMPEG ─────────────────────────── v0.4.5 Installed Missings ───────────────────────── v1.2.0 Installed Preferences ────────────────────── v1.5.2 Installed TableTraits ────────────────────── v1.0.1 Installed LaTeXStrings ───────────────────── v1.4.0 Installed Crayons ────────────────────────── v4.1.1 Installed SortingAlgorithms ──────────────── v1.2.2 Installed Static ─────────────────────────── v1.4.0 Installed UnPack ─────────────────────────── v1.0.2 Installed LLVMOpenMP_jll ─────────────────── v18.1.8+0 Installed MCMCChains ─────────────────────── v7.7.0 Installed libdrm_jll ─────────────────────── v2.4.125+1 Installed RangeArrays ────────────────────── v0.3.2 Installed NaturalSort ────────────────────── v1.0.0 Installed ADTypes ────────────────────────── v1.22.0 Installed Inflate ────────────────────────── v0.1.5 Installed DiffResults ────────────────────── v1.1.0 Installed ManualMemory ───────────────────── v0.1.8 Installed DataStructures ─────────────────── v0.19.5 Installed FillArrays ─────────────────────── v1.16.0 Installed ElasticPDMats ──────────────────── v0.2.4 Installed MacroTools ─────────────────────── v0.5.16 Installed Quaternions ────────────────────── v0.7.7 Installed AbstractTrees ──────────────────── v0.4.5 Installed ArnoldiMethod ──────────────────── v0.4.0 Installed x264_jll ───────────────────────── v10164.0.1+0 Installed micromamba_jll ─────────────────── v2.3.1+0 Installed CodecZlib ──────────────────────── v0.7.8 Installed VectorizationBase ──────────────── v0.21.74 Installed StatsBase ──────────────────────── v0.34.11 Installed oneTBB_jll ─────────────────────── v2022.3.0+0 Installed ConsoleProgressMonitor ─────────── v0.1.2 Installed HostCPUFeatures ────────────────── v0.1.18 Installed Xorg_libXau_jll ────────────────── v1.0.13+0 Installed IntelOpenMP_jll ────────────────── v2025.2.0+0 Installed DataValueInterfaces ────────────── v1.0.0 Installed LayoutPointers ─────────────────── v0.1.17 Installed CommonSubexpressions ───────────── v0.3.1 Installed ArrayInterface ─────────────────── v7.25.0 Installed MCMCDiagnosticTools ────────────── v0.3.18 Installed Libffi_jll ─────────────────────── v3.4.7+0 Installed RealDot ────────────────────────── v0.1.0 Installed LoggingExtras ──────────────────── v1.2.0 Installed Xorg_libXfixes_jll ─────────────── v6.0.2+0 Installed StructUtils ────────────────────── v2.8.2 Installed AbstractGPs ────────────────────── v0.5.24 Installed Pixman_jll ─────────────────────── v0.46.4+0 Installed Expat_jll ──────────────────────── v2.8.1+0 Installed IntegerMathUtils ───────────────── v0.1.3 Installed TerminalLoggers ────────────────── v0.1.7 Installed ColorVectorSpace ───────────────── v0.11.0 Installed NamedDims ──────────────────────── v1.2.3 Installed SimpleTraits ───────────────────── v0.9.6 Installed IrrationalConstants ────────────── v0.2.6 Installed AdvancedMH ─────────────────────── v0.8.10 Installed libpng_jll ─────────────────────── v1.6.58+0 Installed LeftChildRightSiblingTrees ─────── v0.2.1 Installed StableRNGs ─────────────────────── v1.0.4 Installed libfdk_aac_jll ─────────────────── v2.0.4+0 Installed Scratch ────────────────────────── v1.3.0 Installed Interpolations ─────────────────── v0.16.2 Installed pixi_jll ───────────────────────── v0.63.2+0 Installed MatrixEquations ────────────────── v2.5.8 Installed FFMPEG_jll ─────────────────────── v8.1.0+0 Installed Setfield ───────────────────────── v1.1.2 Installed LowRankApprox ──────────────────── v0.5.5 Installed PDMats ─────────────────────────── v0.11.36 Installed BenchmarkTools ─────────────────── v1.8.0 Installed AxisArrays ─────────────────────── v0.4.8 Installed CompositionsBase ───────────────── v0.1.2 Installed DocStringExtensions ────────────── v0.9.5 Installed ForwardDiff ────────────────────── v1.4.0 Installed Rmath_jll ──────────────────────── v0.5.1+0 Installed PythonCall ─────────────────────── v0.9.35 Installed KernelDensity ──────────────────── v0.6.12 Installed SLEEFPirates ───────────────────── v0.6.46 Installed BitTwiddlingConvenienceFunctions ─ v0.1.6 Installed AliasTables ────────────────────── v1.1.3 Installed IteratorInterfaceExtensions ────── v1.0.0 Installed DifferentiationInterface ───────── v0.7.18 Installed ManifoldDiff ───────────────────── v0.4.5 Installed LDLFactorizations ──────────────── v0.10.2 Installed RecipesBase ────────────────────── v1.3.4 Installed DataAPI ────────────────────────── v1.16.0 Installed MathOptInterface ───────────────── v1.51.1 Installed Colors ─────────────────────────── v0.13.1 Installed ReverseDiff ────────────────────── v1.16.2 Installed AbstractFFTs ───────────────────── v1.5.0 Installed FastGaussQuadrature ────────────── v1.3.0 Installed StaticArraysCore ───────────────── v1.4.4 Installed StaticArrays ───────────────────── v1.9.18 Installed BangBang ───────────────────────── v0.4.9 Installed AxisAlgorithms ─────────────────── v1.1.0 Installed SciMLPublic ────────────────────── v1.0.1 Installed Glib_jll ───────────────────────── v2.86.3+0 Installed FunctionWrappers ───────────────── v1.1.3 Installed ColorTypes ─────────────────────── v0.12.1 Installed StringManipulation ─────────────── v0.4.4 Installed Requires ───────────────────────── v1.3.1 Installed Tullio ─────────────────────────── v0.3.9 Installed LogExpFunctions ────────────────── v0.3.29 Installed DiffRules ──────────────────────── v1.16.0 Installed Arpack_jll ─────────────────────── v3.5.2+0 Installed Distributions ──────────────────── v0.25.126 Installed Parsers ────────────────────────── v2.8.5 Installed OpenBLAS32_jll ─────────────────── v0.3.33+1 Installed Rmath ──────────────────────────── v0.9.0 Installed JSON ───────────────────────────── v1.6.1 Installed PrettyTables ───────────────────── v3.3.2 Installed CloseOpenIntervals ─────────────── v0.1.13 Installed ZygoteRules ────────────────────── v0.2.7 Installed Xorg_libXdmcp_jll ──────────────── v1.1.6+0 Installed MutableArithmetics ─────────────── v1.8.0 Installed JLLWrappers ────────────────────── v1.8.0 Installed StatsFuns ──────────────────────── v1.5.2 Installed FiniteDiff ─────────────────────── v2.31.0 Installed x265_jll ───────────────────────── v4.1.0+0 Installed IterTools ──────────────────────── v1.10.0 Installed ProgressBars ───────────────────── v1.5.1 Installed Primes ─────────────────────────── v0.5.7 Installed ThreadingUtilities ─────────────── v0.5.6 Installed SCS_jll ────────────────────────── v300.200.1100+0 Installed Convex ─────────────────────────── v0.16.6 Installed ColorSchemes ───────────────────── v3.31.0 Installed StatisticalTraits ──────────────── v3.5.0 Installed Accessors ──────────────────────── v0.1.44 Installed Graphs ─────────────────────────── v1.14.0 Installed FFTA ───────────────────────────── v0.3.1 Installed Adapt ──────────────────────────── v4.6.0 Installed Xorg_xtrans_jll ────────────────── v1.6.0+0 Installed ConstructionBase ───────────────── v1.6.0 Installed LowRankMatrices ────────────────── v1.0.2 Installed Libmount_jll ───────────────────── v2.42.0+0 Installed HypergeometricFunctions ────────── v0.3.28 Installed LinearMaps ─────────────────────── v3.11.4 Installed ChunkSplitters ─────────────────── v3.2.0 Installed TranscodingStreams ─────────────── v0.11.3 Installed ProgressLogging ────────────────── v0.1.6 Installed Xorg_libX11_jll ────────────────── v1.8.13+0 Installed TensorCore ─────────────────────── v0.1.1 Installed Compat ─────────────────────────── v4.18.1 Installed TSVD ───────────────────────────── v0.4.4 Installed LoopVectorization ──────────────── v0.12.174 Installed PositiveFactorizations ─────────── v0.2.4 Installed Statistics ─────────────────────── v1.11.1 Installed StatsAPI ───────────────────────── v1.8.0 Installed ProgressMeter ──────────────────── v1.11.0 Installed OffsetArrays ───────────────────── v1.17.0 Installed MicroMamba ─────────────────────── v0.1.15 Installed LogDensityProblems ─────────────── v2.2.0 Installed Manifolds ──────────────────────── v0.11.27 Installed PrecompileTools ────────────────── v1.3.4 Installed ChainRulesCore ─────────────────── v1.26.1 Installed CalibrateEmulateSample ─────────── v1.1.0 Installed CodecBzip2 ─────────────────────── v0.8.5 Installed GettextRuntime_jll ─────────────── v0.22.4+0 Installed Ratios ─────────────────────────── v0.4.5 Installed CPUSummary ─────────────────────── v0.2.7 Installed AMD ────────────────────────────── v0.5.3 Installed LAME_jll ───────────────────────── v3.100.3+0 Installed IfElse ─────────────────────────── v0.1.1 Installed FriBidi_jll ────────────────────── v1.0.17+0 Installed SCS ────────────────────────────── v2.6.3 Installed libvorbis_jll ──────────────────── v1.3.8+0 Installed Xorg_libXrender_jll ────────────── v0.9.12+0 Installed MuladdMacro ────────────────────── v0.2.4 Installed ScikitLearnBase ────────────────── v0.5.0 Installed KernelFunctions ────────────────── v0.10.67 Installed FixedPointNumbers ──────────────── v0.8.6 Installed SpecialFunctions ───────────────── v2.8.0 Installed PtrArrays ──────────────────────── v1.4.0 Installed ScientificTypesBase ────────────── v3.1.0 Installed FreeType2_jll ──────────────────── v2.14.3+1 Installed IntervalSets ───────────────────── v0.7.14 Installed AbstractMCMC ───────────────────── v5.15.1 Installed Libiconv_jll ───────────────────── v1.18.0+0 Installed LineSearches ───────────────────── v7.5.1 Installed FFTW_jll ───────────────────────── v3.3.12+0 Installed PolyesterWeave ─────────────────── v0.2.2 Installed FFTW ───────────────────────────── v1.10.0 Installed GaussianProcesses ──────────────── v0.12.6 Installed Kronecker ──────────────────────── v0.5.5 Installed MLJModelInterface ──────────────── v1.12.1 Installed Xorg_libXext_jll ───────────────── v1.3.8+0 Installing 44 artifacts Installed artifact Graphite2 120.2 KiB Installed artifact libass 427.8 KiB Installed artifact OpenSpecFun 194.9 KiB Installed artifact Xorg_libpciaccess 26.2 KiB Installed artifact Xorg_libXfixes 59.0 KiB Installed artifact HarfBuzz 1.7 MiB Installed artifact LLVMOpenMP 661.6 KiB Installed artifact Fontconfig 984.8 KiB Installed artifact FFTW 2.2 MiB Installed artifact Xorg_libXext 286.6 KiB Installed artifact LAME 292.5 KiB Installed artifact Libffi 44.2 KiB Installed artifact Arpack 138.3 KiB Installed artifact Xorg_libXrender 435.9 KiB Installed artifact Glib 7.7 MiB Installed artifact Cairo 2.2 MiB Installed artifact libva 235.7 KiB Installed artifact Expat 288.6 KiB Installed artifact Ogg 250.3 KiB Installed artifact SCS 543.6 KiB Installed artifact libdrm 368.0 KiB Installed artifact Libiconv 1.9 MiB Installed artifact Xorg_libxcb 2.1 MiB Installed artifact x264 2.1 MiB Installed artifact GettextRuntime 543.0 KiB Installed artifact Xorg_libX11 4.8 MiB Installed artifact Xorg_libXdmcp 67.7 KiB Installed artifact libpng 329.4 KiB Installed artifact Xorg_xtrans 48.2 KiB Installed artifact Xorg_libXau 36.6 KiB Installed artifact Bzip2 503.5 KiB Installed artifact Rmath 121.9 KiB Installed artifact FreeType2 1.5 MiB Installed artifact libfdk_aac 2.8 MiB Installed artifact FFMPEG 11.9 MiB Installed artifact FriBidi 78.9 KiB Installed artifact Libuuid 3.9 MiB Installed artifact Opus 960.9 KiB Installed artifact libvorbis 271.0 KiB Installed artifact Pixman 390.8 KiB Installed artifact x265 1.4 MiB Installed artifact OpenBLAS32 10.2 MiB Installed artifact Libmount 6.9 MiB Installed artifact libaom 6.4 MiB Updating `~/.julia/environments/v1.14/Project.toml` [95e48a1f] + CalibrateEmulateSample v1.1.0 Updating `~/.julia/environments/v1.14/Manifest.toml` [47edcb42] + ADTypes v1.22.0 [14f7f29c] + AMD v0.5.3 [621f4979] + AbstractFFTs v1.5.0 [99985d1d] + AbstractGPs v0.5.24 [80f14c24] + AbstractMCMC v5.15.1 [1520ce14] + AbstractTrees v0.4.5 [7d9f7c33] + Accessors v0.1.44 [79e6a3ab] + Adapt v4.6.0 [5b7e9947] + AdvancedMH v0.8.10 [66dad0bd] + AliasTables v1.1.3 [dce04be8] + ArgCheck v2.5.0 [ec485272] + ArnoldiMethod v0.4.0 [7d9fca2a] + Arpack v0.5.4 [4fba245c] + ArrayInterface v7.25.0 [13072b0f] + AxisAlgorithms v1.1.0 [39de3d68] + AxisArrays v0.4.8 [198e06fe] + BangBang v0.4.9 [6e4b80f9] + BenchmarkTools v1.8.0 [62783981] + BitTwiddlingConvenienceFunctions v0.1.6 [2a0fbf3d] + CPUSummary v0.2.7 [95e48a1f] + CalibrateEmulateSample v1.1.0 [d360d2e6] + ChainRulesCore v1.26.1 [ae650224] + ChunkSplitters v3.2.0 [fb6a15b2] + CloseOpenIntervals v0.1.13 [523fee87] + CodecBzip2 v0.8.5 [944b1d66] + CodecZlib v0.7.8 [35d6a980] + ColorSchemes v3.31.0 [3da002f7] + ColorTypes v0.12.1 [c3611d14] + ColorVectorSpace v0.11.0 [5ae59095] + Colors v0.13.1 [bbf7d656] + CommonSubexpressions v0.3.1 [f70d9fcc] + CommonWorldInvalidations v1.0.0 [34da2185] + Compat v4.18.1 [a33af91c] + CompositionsBase v0.1.2 [992eb4ea] + CondaPkg v0.2.36 [88cd18e8] + ConsoleProgressMonitor v0.1.2 [187b0558] + ConstructionBase v1.6.0 [f65535da] + Convex v0.16.6 [adafc99b] + CpuId v0.3.1 [a8cc5b0e] + Crayons v4.1.1 [9a962f9c] + DataAPI v1.16.0 [864edb3b] + DataStructures v0.19.5 [e2d170a0] + DataValueInterfaces v1.0.0 [163ba53b] + DiffResults v1.1.0 [b552c78f] + DiffRules v1.16.0 [a0c0ee7d] + DifferentiationInterface v0.7.18 [b4f34e82] + Distances v0.10.12 [31c24e10] + Distributions v0.25.126 [ffbed154] + DocStringExtensions v0.9.5 [fdbdab4c] + ElasticArrays v1.2.12 [2904ab23] + ElasticPDMats v0.2.4 [aa8a2aa5] + EnsembleKalmanProcesses v2.7.1 [4e289a0a] + EnumX v1.0.7 [c87230d0] + FFMPEG v0.4.5 [b86e33f2] + FFTA v0.3.1 [7a1cc6ca] + FFTW v1.10.0 [442a2c76] + FastGaussQuadrature v1.3.0 [1a297f60] + FillArrays v1.16.0 [6a86dc24] + FiniteDiff v2.31.0 ⌅ [53c48c17] + FixedPointNumbers v0.8.6 [f6369f11] + ForwardDiff v1.4.0 [069b7b12] + FunctionWrappers v1.1.3 [d9f16b24] + Functors v0.5.2 [891a1506] + GaussianProcesses v0.12.6 [e4b2fa32] + GaussianRandomFields v2.2.7 [8f48dd54] + Glossaries v0.1.1 [86223c79] + Graphs v1.14.0 [3e5b6fbb] + HostCPUFeatures v0.1.18 [34004b35] + HypergeometricFunctions v0.3.28 [615f187c] + IfElse v0.1.1 [d25df0c9] + Inflate v0.1.5 [22cec73e] + InitialValues v0.3.1 [18e54dd8] + IntegerMathUtils v0.1.3 [a98d9a8b] + Interpolations v0.16.2 [8197267c] + IntervalSets v0.7.14 [3587e190] + InverseFunctions v0.1.17 [92d709cd] + IrrationalConstants v0.2.6 [c8e1da08] + IterTools v1.10.0 [82899510] + IteratorInterfaceExtensions v1.0.0 [692b3bcd] + JLLWrappers v1.8.0 [682c06a0] + JSON v1.6.1 [5ab0869b] + KernelDensity v0.6.12 ⌅ [ec8451be] + KernelFunctions v0.10.67 [2c470bb0] + Kronecker v0.5.5 [40e66cde] + LDLFactorizations v0.10.2 [b964fa9f] + LaTeXStrings v1.4.0 [10f19ff3] + LayoutPointers v0.1.17 ⌅ [1d6d02ad] + LeftChildRightSiblingTrees v0.2.1 ⌃ [d3d80556] + LineSearches v7.5.1 [7a12625a] + LinearMaps v3.11.4 [6fdf6af0] + LogDensityProblems v2.2.0 ⌅ [2ab3a3ac] + LogExpFunctions v0.3.29 [e6f89c97] + LoggingExtras v1.2.0 [bdcacae8] + LoopVectorization v0.12.174 [898213cb] + LowRankApprox v0.5.5 [e65ccdef] + LowRankMatrices v1.0.2 [c7f686f2] + MCMCChains v7.7.0 [be115224] + MCMCDiagnosticTools v0.3.18 [e80e1ace] + MLJModelInterface v1.12.1 [1914dd2f] + MacroTools v0.5.16 [af67fdf4] + ManifoldDiff v0.4.5 [1cead3c2] + Manifolds v0.11.27 [3362f125] + ManifoldsBase v2.4.0 [0fc0a36d] + Manopt v0.5.39 [d125e4d3] + ManualMemory v0.1.8 [b8f27783] + MathOptInterface v1.51.1 [99c1a7ee] + MatrixEquations v2.5.8 [0b3b1443] + MicroMamba v0.1.15 [e1d29d7a] + Missings v1.2.0 [46d2c3a1] + MuladdMacro v0.2.4 [d8a4904e] + MutableArithmetics v1.8.0 ⌅ [d41bc354] + NLSolversBase v7.10.0 [77ba4419] + NaNMath v1.1.3 [356022a1] + NamedDims v1.2.3 [c020b1a1] + NaturalSort v1.0.0 [4d1e1d77] + Nullables v1.0.0 [6fe1bfb0] + OffsetArrays v1.17.0 ⌅ [429524aa] + Optim v1.13.3 ⌅ [bac558e1] + OrderedCollections v1.8.2 ⌅ [90014a1f] + PDMats v0.11.36 [69de0a69] + Parsers v2.8.5 [fa939f87] + Pidfile v1.3.0 [1d0040c9] + PolyesterWeave v0.2.2 [85a6dd25] + PositiveFactorizations v0.2.4 [aea7be01] + PrecompileTools v1.3.4 [21216c6a] + Preferences v1.5.2 [08abe8d2] + PrettyTables v3.3.2 [27ebfcd6] + Primes v0.5.7 [49802e3a] + ProgressBars v1.5.1 [33c8b6b6] + ProgressLogging v0.1.6 [92933f4c] + ProgressMeter v1.11.0 [43287f4e] + PtrArrays v1.4.0 [6099a3de] + PythonCall v0.9.35 [1fd47b50] + QuadGK v2.11.3 [94ee1d12] + Quaternions v0.7.7 [36c3bae2] + RandomFeatures v0.3.5 [b3c3ace0] + RangeArrays v0.3.2 [c84ed2f1] + Ratios v0.4.5 [c1ae055f] + RealDot v0.1.0 [3cdcf5f2] + RecipesBase v1.3.4 [189a3867] + Reexport v1.2.2 [ae029012] + Requires v1.3.1 [37e2e3b7] + ReverseDiff v1.16.2 [79098fc4] + Rmath v0.9.0 [c946c3f1] + SCS v2.6.3 [94e857df] + SIMDTypes v0.1.0 [476501e8] + SLEEFPirates v0.6.46 [431bcebd] + SciMLPublic v1.0.1 [30f210dd] + ScientificTypesBase v3.1.0 [6e75b9c4] + ScikitLearnBase v0.5.0 [6c6a2e73] + Scratch v1.3.0 [efcf1570] + Setfield v1.1.2 [699a6c99] + SimpleTraits v0.9.6 [47aef6b3] + SimpleWeightedGraphs v1.5.1 [a2af1166] + SortingAlgorithms v1.2.2 [276daf66] + SpecialFunctions v2.8.0 [860ef19b] + StableRNGs v1.0.4 [aedffcd0] + Static v1.4.0 [0d7ed370] + StaticArrayInterface v1.10.0 [90137ffa] + StaticArrays v1.9.18 [1e83bf80] + StaticArraysCore v1.4.4 [64bff920] + StatisticalTraits v3.5.0 [10745b16] + Statistics v1.11.1 [82ae8749] + StatsAPI v1.8.0 [2913bbd2] + StatsBase v0.34.11 ⌅ [4c63d2b9] + StatsFuns v1.5.2 [892a3eda] + StringManipulation v0.4.4 [ec057cc2] + StructUtils v2.8.2 [9449cd9e] + TSVD v0.4.4 [3783bdb8] + TableTraits v1.0.1 [bd369af6] + Tables v1.12.1 [62fd8b95] + TensorCore v0.1.1 [5d786b92] + TerminalLoggers v0.1.7 [8290d209] + ThreadingUtilities v0.5.6 [3bb67fe8] + TranscodingStreams v0.11.3 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v0.3.33+1 [efe28fd5] + OpenSpecFun_jll v0.5.6+0 [91d4177d] + Opus_jll v1.6.1+0 [30392449] + Pixman_jll v0.46.4+0 [f50d1b31] + Rmath_jll v0.5.1+0 [f4f2fc5b] + SCS_jll v300.200.1100+0 [4f6342f7] + Xorg_libX11_jll v1.8.13+0 [0c0b7dd1] + Xorg_libXau_jll v1.0.13+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 [ea2f1a96] + Xorg_libXrender_jll v0.9.12+0 [a65dc6b1] + Xorg_libpciaccess_jll v0.19.0+0 [c7cfdc94] + Xorg_libxcb_jll v1.17.1+0 [c5fb5394] + Xorg_xtrans_jll v1.6.0+0 [a4ae2306] + libaom_jll v3.13.3+0 [0ac62f75] + libass_jll v0.17.4+0 [8e53e030] + libdrm_jll v2.4.125+1 [f638f0a6] + libfdk_aac_jll v2.0.4+0 [b53b4c65] + libpng_jll v1.6.58+0 [9a156e7d] + libva_jll v2.23.0+0 [f27f6e37] + libvorbis_jll v1.3.8+0 [f8abcde7] + micromamba_jll v2.3.1+0 [1317d2d5] + oneTBB_jll v2022.3.0+0 [4d7b5844] + pixi_jll v0.63.2+0 ⌅ [1270edf5] + x264_jll v10164.0.1+0 [dfaa095f] + x265_jll v4.1.0+0 [0dad84c5] + ArgTools v1.1.2 [56f22d72] + Artifacts v1.11.0 [2a0f44e3] + Base64 v1.11.0 [ade2ca70] + Dates v1.11.0 [8ba89e20] + Distributed v1.11.0 [f43a241f] + Downloads v1.7.0 [7b1f6079] + FileWatching v1.11.0 [9fa8497b] + Future v1.11.0 [b77e0a4c] + InteractiveUtils v1.11.0 [ac6e5ff7] + JuliaSyntaxHighlighting v1.13.0 [4af54fe1] + LazyArtifacts v1.11.0 [b27032c2] + LibCURL v1.0.0 [76f85450] + LibGit2 v1.11.0 [8f399da3] + Libdl v1.11.0 [37e2e46d] + LinearAlgebra v1.14.0 [56ddb016] + Logging v1.11.0 [d6f4376e] + Markdown v1.11.0 [a63ad114] + Mmap v1.11.0 [ca575930] + NetworkOptions v1.3.0 [44cfe95a] + Pkg v1.14.0 [de0858da] + Printf v1.11.0 [9abbd945] + Profile v1.11.0 [3fa0cd96] + REPL v1.11.0 [9a3f8284] + Random v1.11.0 [ea8e919c] + SHA v1.13.0 [9e88b42a] + Serialization v1.11.0 [1a1011a3] + SharedArrays v1.11.0 [6462fe0b] + Sockets v1.11.0 [2f01184e] + SparseArrays v1.13.0 [f489334b] + StyledStrings v1.13.0 [4607b0f0] + SuiteSparse [fa267f1f] + TOML v1.0.3 [a4e569a6] + Tar v1.10.0 [8dfed614] + Test v1.11.0 [cf7118a7] + UUIDs v1.11.0 [4ec0a83e] + Unicode v1.11.0 [e66e0078] + CompilerSupportLibraries_jll v1.5.2+0 [deac9b47] + LibCURL_jll v8.20.0+1 [e37daf67] + LibGit2_jll v1.9.4+0 [29816b5a] + LibSSH2_jll v1.11.101+0 [14a3606d] + MozillaCACerts_jll v2026.5.14 [4536629a] + OpenBLAS_jll v0.3.33+0 [05823500] + OpenLibm_jll v0.8.7+0 [458c3c95] + OpenSSL_jll v3.5.6+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 v1.69.0+0 [3f19e933] + p7zip_jll v17.8.0+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 25.05s ################################################################################ # Precompilation # Precompiling PkgEval dependencies... Precompiling project... 5.0 s ✓ TestEnv 1 dependency successfully precompiled in 5 seconds. 27 already precompiled. Precompiling package dependencies... Precompiling project... 4.0 s ✓ MacroTools 0.9 s ✓ Glossaries 0.5 s ✓ Reexport 0.6 s ✓ TensorCore 0.9 s ✓ ConstructionBase 1.9 s ✓ IrrationalConstants 0.5 s ✓ DataValueInterfaces 0.6 s ✓ StatsAPI 2.7 s ✓ LinearMaps 0.9 s ✓ IterTools 0.8 s ✓ IntervalSets 0.7 s ✓ Inflate 0.6 s ✓ ArgCheck 1.0 s ✓ TranscodingStreams 0.6 s ✓ LaTeXStrings 0.8 s ✓ Statistics 0.7 s ✓ StaticArraysCore 0.6 s ✓ ChunkSplitters 0.6 s ✓ StableRNGs 0.5 s ✓ IfElse 0.5 s ✓ PtrArrays 0.4 s ✓ NaturalSort 0.6 s ✓ ManualMemory 0.6 s ✓ Adapt 0.7 s ✓ PositiveFactorizations 0.6 s ✓ DataAPI 0.6 s ✓ SciMLPublic 0.5 s ✓ RealDot 0.5 s ✓ CommonWorldInvalidations 0.6 s ✓ LowRankMatrices 0.6 s ✓ InverseFunctions 0.5 s ✓ CompositionsBase 0.9 s ✓ AbstractTrees 1.5 s ✓ InitialValues 0.5 s ✓ MuladdMacro 0.8 s ✓ AbstractFFTs 0.6 s ✓ EnumX 2.3 s ✓ FillArrays 0.5 s ✓ IntegerMathUtils 0.5 s ✓ UnPack 0.6 s ✓ UnsafePointers 0.6 s ✓ RangeArrays 0.8 s ✓ Nullables 1.2 s ✓ OrderedCollections 1.1 s ✓ FunctionWrappers 1.1 s ✓ ADTypes 0.8 s ✓ DocStringExtensions 1.5 s ✓ OffsetArrays 0.4 s ✓ SIMDTypes 0.5 s ✓ IteratorInterfaceExtensions 1.9 s ✓ Crayons 0.9 s ✓ ProgressLogging 0.7 s ✓ NaNMath 0.9 s ✓ Requires 0.9 s ✓ ProgressBars 2.4 s ✓ ProgressMeter 2.2 s ✓ WoodburyMatrices 2.5 s ✓ AMD 1.1 s ✓ Scratch 1.3 s ✓ LoggingExtras 1.7 s ✓ StructUtils 1.6 s ✓ CpuId 2.6 s ✓ PDMats 0.9 s ✓ Compat 1.4 s ✓ Preferences 1.1 s ✓ ScientificTypesBase 0.8 s ✓ Pidfile 15.7 s ✓ MutableArithmetics 1.4 s ✓ CommonSubexpressions 2.9 s ✓ SimpleTraits 0.5 s ✓ ConstructionBase → ConstructionBaseLinearAlgebraExt 4.1 s ✓ MatrixEquations 2.6 s ✓ LinearMaps → LinearMapsSparseArraysExt 0.5 s ✓ IntervalSets → IntervalSetsRandomExt 0.5 s ✓ ConstructionBase → ConstructionBaseIntervalSetsExt 0.7 s ✓ CodecZlib 1.9 s ✓ Statistics → SparseArraysExt 4.3 s ✓ FixedPointNumbers 0.7 s ✓ ScikitLearnBase 2.2 s ✓ NamedDims 1.2 s ✓ Distances 0.5 s ✓ LinearMaps → LinearMapsStatisticsExt 0.5 s ✓ IntervalSets → IntervalSetsStatisticsExt 0.6 s ✓ DiffResults 0.7 s ✓ AliasTables 1.8 s ✓ ThreadingUtilities 0.8 s ✓ ArrayInterface 2.0 s ✓ Adapt → AdaptSparseArraysExt 0.6 s ✓ ElasticArrays 0.6 s ✓ TSVD 0.7 s ✓ Missings 0.8 s ✓ Quaternions 1.1 s ✓ InverseFunctions → InverseFunctionsDatesExt 1.6 s ✓ InverseFunctions → InverseFunctionsTestExt 0.5 s ✓ CompositionsBase → CompositionsBaseInverseFunctionsExt 0.6 s ✓ LeftChildRightSiblingTrees 4.9 s ✓ AbstractFFTs → AbstractFFTsTestExt 2.4 s ✓ FillArrays → FillArraysSparseArraysExt 1.0 s ✓ FillArrays → FillArraysStatisticsExt 0.9 s ✓ LowRankMatrices → LowRankMatricesFillArraysExt 0.9 s ✓ Primes 3.3 s ✓ DataStructures 0.5 s ✓ ADTypes → ADTypesConstructionBaseExt 1.6 s ✓ DifferentiationInterface 1.3 s ✓ LogExpFunctions 1.8 s ✓ LogDensityProblems 0.5 s ✓ OffsetArrays → OffsetArraysAdaptExt 0.4 s ✓ TableTraits 0.5 s ✓ Ratios 1.3 s ✓ ConsoleProgressMonitor 2.1 s ✓ AxisAlgorithms 2.3 s ✓ LDLFactorizations 1.0 s ✓ StructUtils → StructUtilsStaticArraysCoreExt 3.6 s ✓ ElasticPDMats 2.3 s ✓ FillArrays → FillArraysPDMatsExt 0.5 s ✓ Compat → CompatLinearAlgebraExt 1.9 s ✓ PrecompileTools 2.3 s ✓ JLLWrappers 7.9 s ✓ ManifoldsBase 1.0 s ✓ StatisticalTraits 2.6 s ✓ Setfield 1.8 s ✓ AxisArrays 2.8 s ✓ ColorTypes 0.8 s ✓ NamedDims → AbstractFFTsExt 2.0 s ✓ Distances → DistancesSparseArraysExt 0.5 s ✓ ArrayInterface → ArrayInterfaceStaticArraysCoreExt 2.0 s ✓ ArrayInterface → ArrayInterfaceSparseArraysExt 5.3 s ✓ Accessors 1.6 s ✓ TerminalLoggers 2.4 s ✓ FFTA 1.0 s ✓ SortingAlgorithms 2.2 s ✓ QuadGK 2.0 s ✓ DifferentiationInterface → DifferentiationInterfaceSparseArraysExt 0.6 s ✓ LogExpFunctions → LogExpFunctionsInverseFunctionsExt 1.7 s ✓ Tables 0.8 s ✓ Ratios → RatiosFixedPointNumbersExt 2.5 s ✓ ChainRulesCore 1.0 s ✓ Functors 4.1 s ✓ StringManipulation 16.8 s ✓ StaticArrays 3.8 s ✓ RecipesBase 9.4 s ✓ Parsers 11.4 s ✓ Static 1.7 s ✓ Libffi_jll 1.9 s ✓ OpenBLAS32_jll 2.1 s ✓ Bzip2_jll 2.3 s ✓ Rmath_jll 2.3 s ✓ OpenSpecFun_jll 1.5 s ✓ Xorg_xtrans_jll 2.3 s ✓ Opus_jll 5.7 s ✓ IntelOpenMP_jll 2.3 s ✓ x265_jll 2.3 s ✓ libpng_jll 5.6 s ✓ micromamba_jll 5.6 s ✓ oneTBB_jll 2.2 s ✓ Arpack_jll 2.1 s ✓ Libmount_jll 2.3 s ✓ libfdk_aac_jll 2.4 s ✓ Libuuid_jll 2.3 s ✓ FriBidi_jll 2.3 s ✓ Xorg_libXau_jll 2.3 s ✓ Ogg_jll 2.4 s ✓ FFTW_jll 2.4 s ✓ LAME_jll 2.2 s ✓ Graphite2_jll 2.2 s ✓ x264_jll 2.3 s ✓ Xorg_libpciaccess_jll 2.2 s ✓ LLVMOpenMP_jll 5.3 s ✓ pixi_jll 2.2 s ✓ Libiconv_jll 2.3 s ✓ libaom_jll 2.3 s ✓ Xorg_libXdmcp_jll 2.3 s ✓ Expat_jll 1.6 s ✓ ManifoldsBase → ManifoldsBaseStatisticsExt 1.5 s ✓ ManifoldsBase → ManifoldsBaseQuaternionsExt 2.1 s ✓ ManifoldDiff 3.5 s ✓ MLJModelInterface 1.2 s ✓ ColorTypes → StyledStringsExt 9.8 s ✓ Colors 5.0 s ✓ ColorVectorSpace 1.0 s ✓ FiniteDiff 2.1 s ✓ Accessors → TestExt 2.5 s ✓ Accessors → IntervalSetsExt 2.4 s ✓ Accessors → LinearAlgebraExt 5.5 s ✓ StatsBase 1.1 s ✓ StructUtils → StructUtilsTablesExt 2.1 s ✓ ChainRulesCore → ChainRulesCoreSparseArraysExt 2.2 s ✓ ZygoteRules 0.6 s ✓ LinearMaps → LinearMapsChainRulesCoreExt 0.7 s ✓ AbstractFFTs → AbstractFFTsChainRulesCoreExt 0.6 s ✓ ADTypes → ADTypesChainRulesCoreExt 0.8 s ✓ NamedDims → ChainRulesCoreExt 0.6 s ✓ Distances → DistancesChainRulesCoreExt 0.6 s ✓ ArrayInterface → ArrayInterfaceChainRulesCoreExt 0.6 s ✓ DifferentiationInterface → DifferentiationInterfaceChainRulesCoreExt 3.6 s ✓ LogExpFunctions → LogExpFunctionsChainRulesCoreExt 53.7 s ✓ PrettyTables 3.8 s ✓ ArnoldiMethod 1.9 s ✓ StaticArrays → StaticArraysStatisticsExt 2.1 s ✓ StaticArrays → StaticArraysChainRulesCoreExt 2.1 s ✓ ConstructionBase → ConstructionBaseStaticArraysExt 2.0 s ✓ Adapt → AdaptStaticArraysExt 2.5 s ✓ FillArrays → FillArraysStaticArraysExt 2.2 s ✓ DifferentiationInterface → DifferentiationInterfaceStaticArraysExt 2.2 s ✓ Accessors → StaticArraysExt 1.5 s ✓ IntervalSets → IntervalSetsRecipesBaseExt 7.8 s ✓ JSON 1.1 s ✓ BitTwiddlingConvenienceFunctions 3.2 s ✓ CPUSummary 17.4 s ✓ StaticArrayInterface 1.2 s ✓ CodecBzip2 2.3 s ✓ FreeType2_jll 1.8 s ✓ Rmath 5.9 s ✓ SpecialFunctions  Downloading artifact: micromamba 6.0 s ✓ MicroMamba  Downloading artifact: IntelOpenMP  Downloading artifact: oneTBB 10.6 s ✓ MKL_jll 1.6 s ✓ Arpack 2.1 s ✓ libvorbis_jll 2.0 s ✓ libdrm_jll 2.2 s ✓ SCS_jll 2.3 s ✓ Pixman_jll 2.2 s ✓ GettextRuntime_jll 2.2 s ✓ Xorg_libxcb_jll 9.4 s ✓ ColorSchemes 2.0 s ✓ FiniteDiff → FiniteDiffStaticArraysExt 1.9 s ✓ FiniteDiff → FiniteDiffSparseArraysExt 0.7 s ✓ DifferentiationInterface → DifferentiationInterfaceFiniteDiffExt 1.9 s ✓ BangBang 2.4 s ✓ PDMats → StatsBaseExt 4.3 s ✓ Kronecker 12.2 s ✓ Graphs 6.0 s ✓ Interpolations 13.4 s ✓ BenchmarkTools 3.0 s ✓ HostCPUFeatures 1.9 s ✓ PolyesterWeave 1.3 s ✓ StaticArrayInterface → StaticArrayInterfaceOffsetArraysExt 2.4 s ✓ StaticArrayInterface → StaticArrayInterfaceStaticArraysExt 1.4 s ✓ CloseOpenIntervals 1.6 s ✓ LayoutPointers 2.5 s ✓ Fontconfig_jll 4.9 s ✓ SpecialFunctions → SpecialFunctionsChainRulesCoreExt 5.2 s ✓ FastGaussQuadrature 2.7 s ✓ HypergeometricFunctions 1.1 s ✓ DiffRules 1.9 s ✓ ColorVectorSpace → SpecialFunctionsExt  Downloading artifact: pixi 10.6 s ✓ CondaPkg 11.3 s ✓ FFTW 2.4 s ✓ Glib_jll 2.4 s ✓ Xorg_libX11_jll 21.0 s ✓ Manopt 5.6 s ✓ AbstractMCMC 1.4 s ✓ BangBang → BangBangChainRulesCoreExt 1.5 s ✓ BangBang → BangBangTablesExt 2.5 s ✓ BangBang → BangBangStaticArraysExt 4.9 s ✓ SimpleWeightedGraphs 5.3 s ✓ Graphs → GraphsSharedArraysExt 20.1 s ✓ VectorizationBase 13.2 s ✓ KernelFunctions 3.1 s ✓ StatsFuns 16.5 s ✓ Tullio 8.2 s ✓ ForwardDiff 25.8 s ✓ PythonCall WARNING: Constructor for type "Array" was extended in `LowRankApprox` without explicit qualification or import.  NOTE: Assumed "Array" refers to `Base.Array`. This behavior is deprecated and may differ in future versions.  NOTE: This behavior may have differed in Julia versions prior to 1.12.  Hint: If you intended to create a new generic function of the same name, use `function Array end`.  Hint: To silence the warning, qualify `Array` as `Base.Array` in the method signature or explicitly `import Base: Array`. 5.8 s ✓ LowRankApprox 7.8 s ✓ GaussianRandomFields 2.3 s ✓ Xorg_libXfixes_jll 2.2 s ✓ Xorg_libXrender_jll 2.3 s ✓ Xorg_libXext_jll 3.7 s ✓ SLEEFPirates 4.3 s ✓ StatsFuns → StatsFunsChainRulesCoreExt 1.3 s ✓ StatsFuns → StatsFunsInverseFunctionsExt 11.2 s ✓ Distributions 1.1 s ✓ Tullio → TullioChainRulesCoreExt 1.5 s ✓ Tullio → TullioFillArraysExt 27.0 s ✓ Manifolds 2.4 s ✓ ForwardDiff → ForwardDiffStaticArraysExt 1.7 s ✓ DifferentiationInterface → DifferentiationInterfaceForwardDiffExt 112.0 s ✓ MathOptInterface 3.9 s ✓ Interpolations → InterpolationsForwardDiffExt 2.4 s ✓ Cairo_jll 2.4 s ✓ libva_jll 44.0 s ✓ LoopVectorization 4.9 s ✓ Distributions → DistributionsTestExt 4.4 s ✓ Distributions → DistributionsChainRulesCoreExt 6.1 s ✓ MCMCDiagnosticTools 6.3 s ✓ AdvancedMH 7.4 s ✓ Manifolds → ManifoldsRecipesBaseExt 10.3 s ✓ Manifolds → ManifoldsTestExt 8.0 s ✓ Manopt → ManoptManifoldsExt 47.4 s ✓ ReverseDiff 2.6 s ✓ NLSolversBase 10.5 s ✓ MathOptInterface → MathOptInterfaceBenchmarkToolsExt 71.8 s ✓ SCS 2.2 s ✓ HarfBuzz_jll 3.6 s ✓ LoopVectorization → SpecialFunctionsExt 3.9 s ✓ LoopVectorization → ForwardDiffExt 6.2 s ✓ KernelDensity 7.3 s ✓ AbstractGPs 5.0 s ✓ AdvancedMH → AdvancedMHForwardDiffExt 20.5 s ✓ ArrayInterface → ArrayInterfaceReverseDiffExt 19.1 s ✓ DifferentiationInterface → DifferentiationInterfaceReverseDiffExt 3.0 s ✓ LineSearches 15.6 s ✓ Convex 2.2 s ✓ libass_jll 11.1 s ✓ MCMCChains 5.2 s ✓ Manopt → ManoptLineSearchesExt 7.6 s ✓ Optim 2.2 s ✓ FFMPEG_jll 9.5 s ✓ AdvancedMH → AdvancedMHMCMCChainsExt 12.0 s ✓ Optim → OptimMOIExt 9.3 s ✓ GaussianProcesses 1.3 s ✓ FFMPEG 24.6 s ✓ EnsembleKalmanProcesses 57.2 s ✓ RandomFeatures  CondaPkg Found dependencies: /home/pkgeval/.julia/packages/CondaPkg/lKlVY/CondaPkg.toml  CondaPkg Found dependencies: /home/pkgeval/.julia/packages/CalibrateEmulateSample/yapkx/CondaPkg.toml  CondaPkg Found dependencies: /home/pkgeval/.julia/packages/PythonCall/5WGSP/CondaPkg.toml  CondaPkg Resolving changes  + openssl  + python  + scikit-learn  + scipy  CondaPkg Initialising pixi  │ /home/pkgeval/.julia/artifacts/4ae17cee0bd922f66b2c72bf2f01c22481a5ec19/bin/pixi  │ init  │ --format pixi  └ /tmp/jl_Vb7XoB/.CondaPkg ✔ Created /tmp/jl_Vb7XoB/.CondaPkg/pixi.toml  CondaPkg Wrote /tmp/jl_Vb7XoB/.CondaPkg/pixi.toml  │ [dependencies]  │ openssl = ">=3, <3.6"  │ scikit-learn = "=1.5.1"  │ scipy = "=1.14.1"  │  │ [dependencies.python]  │ version = ">=3.10,!=3.14.0,!=3.14.1,<4, =3.11"  │ build = "*cp*"  │ channel = "conda-forge"  │  │ [workspace]  │ name = ".CondaPkg"  │ description = "automatically generated by CondaPkg.jl"  │ platforms = ["linux-64"]  │ channel-priority = "strict"  └ channels = ["conda-forge"]  CondaPkg Installing packages  │ /home/pkgeval/.julia/artifacts/4ae17cee0bd922f66b2c72bf2f01c22481a5ec19/bin/pixi  │ install  └ --manifest-path /tmp/jl_Vb7XoB/.CondaPkg/pixi.toml ✔ The default environment has been installed. 112.5 s ✓ CalibrateEmulateSample 314 dependencies successfully precompiled in 1524 seconds. 42 already precompiled. 5 dependencies had output during precompilation: ┌ LowRankApprox │ WARNING: Constructor for type "Array" was extended in `LowRankApprox` without explicit qualification or import. │ NOTE: Assumed "Array" refers to `Base.Array`. This behavior is deprecated and may differ in future versions. │ NOTE: This behavior may have differed in Julia versions prior to 1.12. │ Hint: If you intended to create a new generic function of the same name, use `function Array end`. │ Hint: To silence the warning, qualify `Array` as `Base.Array` in the method signature or explicitly `import Base: Array`. └ ┌ MicroMamba │ Downloading artifact: micromamba └ ┌ MKL_jll │ Downloading artifact: IntelOpenMP │ Downloading artifact: oneTBB └ ┌ CalibrateEmulateSample │ CondaPkg Found dependencies: /home/pkgeval/.julia/packages/CondaPkg/lKlVY/CondaPkg.toml │ CondaPkg Found dependencies: /home/pkgeval/.julia/packages/CalibrateEmulateSample/yapkx/CondaPkg.toml │ CondaPkg Found dependencies: /home/pkgeval/.julia/packages/PythonCall/5WGSP/CondaPkg.toml │ CondaPkg Resolving changes │ + openssl │ + python │ + scikit-learn │ + scipy │ CondaPkg Initialising pixi │ │ /home/pkgeval/.julia/artifacts/4ae17cee0bd922f66b2c72bf2f01c22481a5ec19/bin/pixi │ │ init │ │ --format pixi │ └ /tmp/jl_Vb7XoB/.CondaPkg │ ✔ Created /tmp/jl_Vb7XoB/.CondaPkg/pixi.toml │ CondaPkg Wrote /tmp/jl_Vb7XoB/.CondaPkg/pixi.toml │ │ [dependencies] │ │ openssl = ">=3, <3.6" │ │ scikit-learn = "=1.5.1" │ │ scipy = "=1.14.1" │ │ │ │ [dependencies.python] │ │ version = ">=3.10,!=3.14.0,!=3.14.1,<4, =3.11" │ │ build = "*cp*" │ │ channel = "conda-forge" │ │ │ │ [workspace] │ │ name = ".CondaPkg" │ │ description = "automatically generated by CondaPkg.jl" │ │ platforms = ["linux-64"] │ │ channel-priority = "strict" │ └ channels = ["conda-forge"] │ CondaPkg Installing packages │ │ /home/pkgeval/.julia/artifacts/4ae17cee0bd922f66b2c72bf2f01c22481a5ec19/bin/pixi │ │ install │ └ --manifest-path /tmp/jl_Vb7XoB/.CondaPkg/pixi.toml │ ✔ The default environment has been installed. └ ┌ CondaPkg │ Downloading artifact: pixi └ Precompilation completed after 1553.17s ################################################################################ # Testing # Testing CalibrateEmulateSample Status `/tmp/jl_pNLkSv/Project.toml` [99985d1d] AbstractGPs v0.5.24 [80f14c24] AbstractMCMC v5.15.1 [5b7e9947] AdvancedMH v0.8.10 [95e48a1f] CalibrateEmulateSample v1.1.0 [ae650224] ChunkSplitters v3.2.0 [992eb4ea] CondaPkg v0.2.36 [31c24e10] Distributions v0.25.126 [ffbed154] DocStringExtensions v0.9.5 [aa8a2aa5] EnsembleKalmanProcesses v2.7.1 [f6369f11] ForwardDiff v1.4.0 [891a1506] GaussianProcesses v0.12.6 ⌅ [ec8451be] KernelFunctions v0.10.67 [7a12625a] LinearMaps v3.11.4 [898213cb] LowRankApprox v0.5.5 [c7f686f2] MCMCChains v7.7.0 [1cead3c2] Manifolds v0.11.27 [0fc0a36d] Manopt v0.5.39 ⌅ [90014a1f] PDMats v0.11.36 [49802e3a] ProgressBars v1.5.1 [6099a3de] PythonCall v0.9.35 [36c3bae2] RandomFeatures v0.3.5 [37e2e3b7] ReverseDiff v1.16.2 [860ef19b] StableRNGs v1.0.4 [10745b16] Statistics v1.11.1 [2913bbd2] StatsBase v0.34.11 [9449cd9e] TSVD v0.4.4 [37e2e46d] LinearAlgebra v1.14.0 [44cfe95a] Pkg v1.14.0 [de0858da] Printf v1.11.0 [9a3f8284] Random v1.11.0 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[3f19e933] p7zip_jll v17.8.0+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... [ Info: [in test/runtest.jl], create plots? CES_TEST_PLOT_OUTPUT: false Starting tests for Emulator CondaPkg Found dependencies: /home/pkgeval/.julia/packages/CondaPkg/lKlVY/CondaPkg.toml CondaPkg Found dependencies: /home/pkgeval/.julia/packages/CalibrateEmulateSample/yapkx/CondaPkg.toml CondaPkg Found dependencies: /home/pkgeval/.julia/packages/PythonCall/5WGSP/CondaPkg.toml CondaPkg Resolving changes + openssl + python + scikit-learn + scipy CondaPkg Initialising pixi │ /home/pkgeval/.julia/artifacts/4ae17cee0bd922f66b2c72bf2f01c22481a5ec19/bin/pixi │ init │ --format pixi └ /tmp/jl_pNLkSv/.CondaPkg ✔ Created /tmp/jl_pNLkSv/.CondaPkg/pixi.toml CondaPkg Wrote /tmp/jl_pNLkSv/.CondaPkg/pixi.toml │ [dependencies] │ openssl = ">=3, <3.6" │ scikit-learn = "=1.5.1" │ scipy = "=1.14.1" │ │ [dependencies.python] │ version = ">=3.10,!=3.14.0,!=3.14.1,<4, =3.11" │ build = "*cp*" │ channel = "conda-forge" │ │ [workspace] │ name = ".CondaPkg" │ description = "automatically generated by CondaPkg.jl" │ platforms = ["linux-64"] │ channel-priority = "strict" └ channels = ["conda-forge"] CondaPkg Installing packages │ /home/pkgeval/.julia/artifacts/4ae17cee0bd922f66b2c72bf2f01c22481a5ec19/bin/pixi │ install └ --manifest-path /tmp/jl_pNLkSv/.CondaPkg/pixi.toml ✔ The default environment has been installed. [ Info: fit successful [ Info: Initialize encoding of data: "in" with Decorrelator: decorrelate_with=sample_cov ┌ Warning: SVD representation is efficient when estimating high-dimensional covariance with few samples. │ here # samples is 50, while the space dimension is 10, and representation will be inefficient. └ @ EnsembleKalmanProcesses ~/.julia/packages/EnsembleKalmanProcesses/1ArOR/src/Observations.jl:203 [ Info: Initialize encoding of data: "out" with Decorrelator: decorrelate_with=sample_cov ┌ Warning: SVD representation is efficient when estimating high-dimensional covariance with few samples. │ here # samples is 50, while the space dimension is 6, and representation will be inefficient. └ @ EnsembleKalmanProcesses ~/.julia/packages/EnsembleKalmanProcesses/1ArOR/src/Observations.jl:203 [ Info: Initialize encoding of data: "in" with Decorrelator: decorrelate_with=sample_cov ┌ Warning: SVD representation is efficient when estimating high-dimensional covariance with few samples. │ here # samples is 50, while the space dimension is 10, and representation will be inefficient. └ @ EnsembleKalmanProcesses ~/.julia/packages/EnsembleKalmanProcesses/1ArOR/src/Observations.jl:203 [ Info: Initialize encoding of data: "out" with Decorrelator: decorrelate_with=sample_cov ┌ Warning: SVD representation is efficient when estimating high-dimensional covariance with few samples. │ here # samples is 50, while the space dimension is 6, and representation will be inefficient. └ @ EnsembleKalmanProcesses ~/.julia/packages/EnsembleKalmanProcesses/1ArOR/src/Observations.jl:203 Using default squared exponential kernel, learning length scale and variance parameters Using default squared exponential kernel: Type: GaussianProcesses.SEArd{Float64}, Params: [-0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, 0.0] Learning additive white noise kernel in GaussianProcess: Type: GaussianProcesses.SumKernel{GaussianProcesses.SEArd{Float64}, GaussianProcesses.Noise{Float64}} Type: GaussianProcesses.SEArd{Float64}, Params: [-0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, 0.0] Type: GaussianProcesses.Noise{Float64}, Params: [0.0] created GP: 1 kernel in GaussianProcess: Type: GaussianProcesses.SumKernel{GaussianProcesses.SEArd{Float64}, GaussianProcesses.Noise{Float64}} Type: GaussianProcesses.SEArd{Float64}, Params: [-0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, 0.0] Type: GaussianProcesses.Noise{Float64}, Params: [0.0] created GP: 2 kernel in GaussianProcess: Type: GaussianProcesses.SumKernel{GaussianProcesses.SEArd{Float64}, GaussianProcesses.Noise{Float64}} Type: GaussianProcesses.SEArd{Float64}, Params: [-0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, 0.0] Type: GaussianProcesses.Noise{Float64}, Params: [0.0] created GP: 3 kernel in GaussianProcess: Type: GaussianProcesses.SumKernel{GaussianProcesses.SEArd{Float64}, GaussianProcesses.Noise{Float64}} Type: GaussianProcesses.SEArd{Float64}, Params: [-0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, 0.0] Type: GaussianProcesses.Noise{Float64}, Params: [0.0] created GP: 4 kernel in GaussianProcess: Type: GaussianProcesses.SumKernel{GaussianProcesses.SEArd{Float64}, GaussianProcesses.Noise{Float64}} Type: GaussianProcesses.SEArd{Float64}, Params: [-0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, 0.0] Type: GaussianProcesses.Noise{Float64}, Params: [0.0] created GP: 5 kernel in GaussianProcess: Type: GaussianProcesses.SumKernel{GaussianProcesses.SEArd{Float64}, GaussianProcesses.Noise{Float64}} Type: GaussianProcesses.SEArd{Float64}, Params: [-0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, 0.0] Type: GaussianProcesses.Noise{Float64}, Params: [0.0] created GP: 6 [ Info: Initialize encoding of data: "in" with Decorrelator: decorrelate_with=sample_cov ┌ Warning: SVD representation is efficient when estimating high-dimensional covariance with few samples. │ here # samples is 50, while the space dimension is 10, and representation will be inefficient. └ @ EnsembleKalmanProcesses ~/.julia/packages/EnsembleKalmanProcesses/1ArOR/src/Observations.jl:203 [ Info: Initialize encoding of data: "out" with Decorrelator: decorrelate_with=sample_cov ┌ Warning: SVD representation is efficient when estimating high-dimensional covariance with few samples. │ here # samples is 50, while the space dimension is 6, and representation will be inefficient. └ @ EnsembleKalmanProcesses ~/.julia/packages/EnsembleKalmanProcesses/1ArOR/src/Observations.jl:203 [ Info: Initialize encoding of data: "in" with Decorrelator: decorrelate_with=sample_cov ┌ Warning: SVD representation is efficient when estimating high-dimensional covariance with few samples. │ here # samples is 50, while the space dimension is 10, and representation will be inefficient. └ @ EnsembleKalmanProcesses ~/.julia/packages/EnsembleKalmanProcesses/1ArOR/src/Observations.jl:203 [ Info: Initialize encoding of data: "out" with Decorrelator: decorrelate_with=structure_mat ┌ Warning: GaussianProcess already built. skipping... └ @ CalibrateEmulateSample.Emulators ~/.julia/packages/CalibrateEmulateSample/yapkx/src/MachineLearningTools/GaussianProcess.jl:188 [ Info: Initialize encoding of data: "in" with Decorrelator: decorrelate_with=sample_cov ┌ Warning: SVD representation is efficient when estimating high-dimensional covariance with few samples. │ here # samples is 50, while the space dimension is 10, and representation will be inefficient. └ @ EnsembleKalmanProcesses ~/.julia/packages/EnsembleKalmanProcesses/1ArOR/src/Observations.jl:203 [ Info: Initialize encoding of data: "out" with Decorrelator: decorrelate_with=structure_mat [ Info: Initialize encoding of data: "in" with Decorrelator: decorrelate_with=sample_cov ┌ Warning: SVD representation is efficient when estimating high-dimensional covariance with few samples. │ here # samples is 50, while the space dimension is 10, and representation will be inefficient. └ @ EnsembleKalmanProcesses ~/.julia/packages/EnsembleKalmanProcesses/1ArOR/src/Observations.jl:203 [ Info: Initialize encoding of data: "out" with Decorrelator: decorrelate_with=sample_cov ┌ Warning: SVD representation is efficient when estimating high-dimensional covariance with few samples. │ here # samples is 50, while the space dimension is 6, and representation will be inefficient. └ @ EnsembleKalmanProcesses ~/.julia/packages/EnsembleKalmanProcesses/1ArOR/src/Observations.jl:203 [ Info: Initialize encoding of data: "in" with Decorrelator: decorrelate_with=sample_cov ┌ Warning: SVD representation is efficient when estimating high-dimensional covariance with few samples. │ here # samples is 50, while the space dimension is 10, and representation will be inefficient. └ @ EnsembleKalmanProcesses ~/.julia/packages/EnsembleKalmanProcesses/1ArOR/src/Observations.jl:203 [ Info: Initialize encoding of data: "out" with Decorrelator: decorrelate_with=sample_cov ┌ Warning: SVD representation is efficient when estimating high-dimensional covariance with few samples. │ here # samples is 50, while the space dimension is 6, and representation will be inefficient. └ @ EnsembleKalmanProcesses ~/.julia/packages/EnsembleKalmanProcesses/1ArOR/src/Observations.jl:203 [ Info: Initialize encoding of data: "in" with Decorrelator: decorrelate_with=sample_cov ┌ Warning: SVD representation is efficient when estimating high-dimensional covariance with few samples. │ here # samples is 50, while the space dimension is 10, and representation will be inefficient. └ @ EnsembleKalmanProcesses ~/.julia/packages/EnsembleKalmanProcesses/1ArOR/src/Observations.jl:203 [ Info: Initialize encoding of data: "out" with Decorrelator: decorrelate_with=structure_mat [ Info: Initialize encoding of data: "in" with Decorrelator: decorrelate_with=sample_cov ┌ Warning: SVD representation is efficient when estimating high-dimensional covariance with few samples. │ here # samples is 50, while the space dimension is 10, and representation will be inefficient. └ @ EnsembleKalmanProcesses ~/.julia/packages/EnsembleKalmanProcesses/1ArOR/src/Observations.jl:203 Completed tests for Emulator, 295 seconds elapsed Starting tests for GaussianProcess Using user-defined kernelType: SEIso{Float64}, Params: [0.0, 0.0] Learning additive white noise kernel in GaussianProcess: Type: SumKernel{SEIso{Float64}, Noise{Float64}} Type: SEIso{Float64}, Params: [0.0, 0.0] Type: Noise{Float64}, Params: [0.0] created GP: 1 ┌ Warning: GaussianProcess already built. skipping... └ @ CalibrateEmulateSample.Emulators ~/.julia/packages/CalibrateEmulateSample/yapkx/src/MachineLearningTools/GaussianProcess.jl:188 optimized hyperparameters of GP: 1 Type: SumKernel{SEIso{Float64}, Noise{Float64}} Type: SEIso{Float64}, Params: [0.4671112501513754, -0.11637219099834126] Type: Noise{Float64}, Params: [-2.779564795897494] optimised GP: 1 Sum of 2 kernels: Squared Exponential Kernel (metric = Distances.Euclidean(0.0)) - ARD Transform (dims: 1) - σ² = 0.7923560881211849 White Kernel - σ² = 0.0038521278625259676 [ Info: AbstractGP already built. Continuing... Using user-defined kernelType: SEIso{Float64}, Params: [0.0, 0.0] Learning additive white noise kernel in GaussianProcess: Type: SumKernel{SEIso{Float64}, Noise{Float64}} Type: SEIso{Float64}, Params: [0.0, 0.0] Type: Noise{Float64}, Params: [0.0] created GP: 1 optimized hyperparameters of GP: 1 Type: SumKernel{SEIso{Float64}, Noise{Float64}} Type: SEIso{Float64}, Params: [0.46711125015097044, -0.11637219099977898] Type: Noise{Float64}, Params: [-2.9126145296277137] Using user-defined kernel1**2 * RBF(length_scale=1) Learning additive white noise [ Info: Training kernel 1, [ Info: 1**2 * RBF(length_scale=1) + WhiteKernel(noise_level=1) ┌ Warning: GaussianProcess already built. skipping... └ @ CalibrateEmulateSample.Emulators ~/.julia/packages/CalibrateEmulateSample/yapkx/src/MachineLearningTools/GaussianProcess.jl:334 SKlearn, already trained. continuing... Using user-defined kernel1**2 * RBF(length_scale=1) Learning additive white noise [ Info: Training kernel 1, [ Info: 1**2 * RBF(length_scale=1) + WhiteKernel(noise_level=1) ┌ Warning: `SKLJL` is deprecated, use `SKLPy` instead. │ caller = top-level scope at runtests.jl:20 └ @ Core ~/.julia/packages/CalibrateEmulateSample/yapkx/test/GaussianProcess/runtests.jl:20 [ Info: Initialize encoding of data: "in" with Decorrelator: decorrelate_with=sample_cov ┌ Warning: SVD representation is efficient when estimating high-dimensional covariance with few samples. │ here # samples is 100, while the space dimension is 2, and representation will be inefficient. └ @ EnsembleKalmanProcesses ~/.julia/packages/EnsembleKalmanProcesses/1ArOR/src/Observations.jl:203 [ Info: Initialize encoding of data: "out" with Decorrelator: decorrelate_with=structure_mat Using default squared exponential kernel, learning length scale and variance parameters Using default squared exponential kernel: Type: SEArd{Float64}, Params: [-0.0, -0.0, 0.0] Learning additive white noise kernel in GaussianProcess: Type: SumKernel{SEArd{Float64}, Noise{Float64}} Type: SEArd{Float64}, Params: [-0.0, -0.0, 0.0] Type: Noise{Float64}, Params: [0.0] created GP: 1 kernel in GaussianProcess: Type: SumKernel{SEArd{Float64}, Noise{Float64}} Type: SEArd{Float64}, Params: [-0.0, -0.0, 0.0] Type: Noise{Float64}, Params: [0.0] created GP: 2 [ Info: Initialize encoding of data: "in" with Decorrelator: decorrelate_with=sample_cov ┌ Warning: SVD representation is efficient when estimating high-dimensional covariance with few samples. │ here # samples is 100, while the space dimension is 2, and representation will be inefficient. └ @ EnsembleKalmanProcesses ~/.julia/packages/EnsembleKalmanProcesses/1ArOR/src/Observations.jl:203 [ Info: Initialize encoding of data: "out" with Decorrelator: decorrelate_with=structure_mat Using default squared exponential kernel, learning length scale and variance parameters Using default squared exponential kernel: Type: SEArd{Float64}, Params: [-0.0, -0.0, 0.0] kernel in GaussianProcess: Type: SEArd{Float64}, Params: [-0.0, -0.0, 0.0] created GP: 1 kernel in GaussianProcess: Type: SEArd{Float64}, Params: [-0.0, -0.0, 0.0] created GP: 2 optimized hyperparameters of GP: 1 Type: SEArd{Float64}, Params: [-0.08095883666729817, 0.6591588380894285, 2.0163237790280433] optimized hyperparameters of GP: 2 Type: SEArd{Float64}, Params: [0.48546387823260384, 0.08009132351645844, 2.348678772768728] optimized hyperparameters of GP: 1 Type: SumKernel{SEArd{Float64}, Noise{Float64}} Type: SEArd{Float64}, Params: [-0.06076669570339724, 0.6629187475773616, 2.0713964932483395] Type: Noise{Float64}, Params: [-0.22010761514599403] optimized hyperparameters of GP: 2 Type: SumKernel{SEArd{Float64}, Noise{Float64}} Type: SEArd{Float64}, Params: [0.4806217980287883, 0.07991481116088309, 2.344620786302477] Type: Noise{Float64}, Params: [-0.09161176738899532] ┌ Warning: `transform_to_real` keyword is deprecated. Please use the `encode` and `add_obs_noise_cov` keywords instead. │ │ Recommended usage for users is now set by default as: │ - `encode=nothing`, `add_obs_noise_cov=false` │ This behaviour takes in non-encoded inputs, and returns non-encoded outputs. It gives only the uncertainty from the Machine Learning Tool (not inflated by observational noise) │ │ This simulation will continue with the old behavior: │ - `transform_to_real=true` replaced with `encode=nothing, add_obs_noise_cov=true` │ - `transform_to_real=false` replaced with `encode="out", add_obs_noise_cov=true` │ └ @ CalibrateEmulateSample.Emulators ~/.julia/packages/CalibrateEmulateSample/yapkx/src/Emulator.jl:600 [ Info: Initialize encoding of data: "in" with Decorrelator: decorrelate_with=sample_cov ┌ Warning: SVD representation is efficient when estimating high-dimensional covariance with few samples. │ here # samples is 100, while the space dimension is 2, and representation will be inefficient. └ @ EnsembleKalmanProcesses ~/.julia/packages/EnsembleKalmanProcesses/1ArOR/src/Observations.jl:203 [ Info: Initialize encoding of data: "out" with Decorrelator: decorrelate_with=structure_mat optimised GP: 1 Sum of 2 kernels: Squared Exponential Kernel (metric = Distances.Euclidean(0.0)) - ARD Transform (dims: 2) - σ² = 62.9784740649691 White Kernel - σ² = 0.6438978198523074 optimised GP: 2 Sum of 2 kernels: Squared Exponential Kernel (metric = Distances.Euclidean(0.0)) - ARD Transform (dims: 2) - σ² = 108.7706538727328 White Kernel - σ² = 0.8325820238965255 Completed tests for GaussianProcess, 100 seconds elapsed Starting tests for RandomFeature ┌ Info: Shrinkage scale: 0.968506416130151, (0 = none, 1 = revert to scaled Identity) └ shrinkage covariance condition number: 1.1701319834501513 [ Info: NICE-adjusted covariance condition number: 2.807519296696305 [ Info: Initialize encoding of data: "in" with Decorrelator: decorrelate_with=sample_cov ┌ Warning: SVD representation is efficient when estimating high-dimensional covariance with few samples. │ here # samples is 50, while the space dimension is 1, and representation will be inefficient. └ @ EnsembleKalmanProcesses ~/.julia/packages/EnsembleKalmanProcesses/1ArOR/src/Observations.jl:203 [ Info: Initialize encoding of data: "out" with Decorrelator: decorrelate_with=structure_mat [ Info: hyperparameter learning for 1 models using 50 training points, 50 validation points and 100 features estimating covariances with 520 iterations... [ Info: Initialize encoding of data: "in" with Decorrelator: decorrelate_with=sample_cov ┌ Warning: SVD representation is efficient when estimating high-dimensional covariance with few samples. │ here # samples is 50, while the space dimension is 1, and representation will be inefficient. └ @ EnsembleKalmanProcesses ~/.julia/packages/EnsembleKalmanProcesses/1ArOR/src/Observations.jl:203 [ Info: Initialize encoding of data: "out" with Decorrelator: decorrelate_with=structure_mat [ Info: hyperparameter learning using 50 training points, 50 validation points and 100 features estimating covariances with 520 iterations... [ Info: Initialize encoding of data: "in" with Decorrelator: decorrelate_with=sample_cov ┌ Warning: SVD representation is efficient when estimating high-dimensional covariance with few samples. │ here # samples is 50, while the space dimension is 1, and representation will be inefficient. └ @ EnsembleKalmanProcesses ~/.julia/packages/EnsembleKalmanProcesses/1ArOR/src/Observations.jl:203 [ Info: Initialize encoding of data: "out" with Decorrelator: decorrelate_with=sample_cov ┌ Warning: SVD representation is efficient when estimating high-dimensional covariance with few samples. │ here # samples is 50, while the space dimension is 1, and representation will be inefficient. └ @ EnsembleKalmanProcesses ~/.julia/packages/EnsembleKalmanProcesses/1ArOR/src/Observations.jl:203 [ Info: hyperparameter learning for 1 models using 40 training points, 10 validation points and 100 features [ Info: Initialize encoding of data: "in" with Decorrelator: decorrelate_with=sample_cov ┌ Warning: SVD representation is efficient when estimating high-dimensional covariance with few samples. │ here # samples is 50, while the space dimension is 1, and representation will be inefficient. └ @ EnsembleKalmanProcesses ~/.julia/packages/EnsembleKalmanProcesses/1ArOR/src/Observations.jl:203 [ Info: Initialize encoding of data: "out" with Decorrelator: decorrelate_with=sample_cov ┌ Warning: SVD representation is efficient when estimating high-dimensional covariance with few samples. │ here # samples is 50, while the space dimension is 1, and representation will be inefficient. └ @ EnsembleKalmanProcesses ~/.julia/packages/EnsembleKalmanProcesses/1ArOR/src/Observations.jl:203 [ Info: Initialize encoding of data: "in" with Decorrelator: decorrelate_with=sample_cov ┌ Warning: SVD representation is efficient when estimating high-dimensional covariance with few samples. │ here # samples is 50, while the space dimension is 1, and representation will be inefficient. └ @ EnsembleKalmanProcesses ~/.julia/packages/EnsembleKalmanProcesses/1ArOR/src/Observations.jl:203 [ Info: Initialize encoding of data: "out" with Decorrelator: decorrelate_with=sample_cov ┌ Warning: SVD representation is efficient when estimating high-dimensional covariance with few samples. │ here # samples is 50, while the space dimension is 1, and representation will be inefficient. └ @ EnsembleKalmanProcesses ~/.julia/packages/EnsembleKalmanProcesses/1ArOR/src/Observations.jl:203 [ Info: Initialize encoding of data: "in" with Decorrelator: decorrelate_with=sample_cov ┌ Warning: SVD representation is efficient when estimating high-dimensional covariance with few samples. │ here # samples is 50, while the space dimension is 1, and representation will be inefficient. └ @ EnsembleKalmanProcesses ~/.julia/packages/EnsembleKalmanProcesses/1ArOR/src/Observations.jl:203 [ Info: Initialize encoding of data: "out" with Decorrelator: decorrelate_with=structure_mat ┌ Warning: ScalarRandomFeatureInterface already built. skipping... └ @ CalibrateEmulateSample.Emulators ~/.julia/packages/CalibrateEmulateSample/yapkx/src/MachineLearningTools/ScalarRandomFeature.jl:356 [ Info: Initialize encoding of data: "in" with Decorrelator: decorrelate_with=sample_cov ┌ Warning: SVD representation is efficient when estimating high-dimensional covariance with few samples. │ here # samples is 50, while the space dimension is 1, and representation will be inefficient. └ @ EnsembleKalmanProcesses ~/.julia/packages/EnsembleKalmanProcesses/1ArOR/src/Observations.jl:203 [ Info: Initialize encoding of data: "out" with Decorrelator: decorrelate_with=structure_mat ┌ Warning: VectorRandomFeatureInterface already built. skipping... └ @ CalibrateEmulateSample.Emulators ~/.julia/packages/CalibrateEmulateSample/yapkx/src/MachineLearningTools/VectorRandomFeature.jl:383 [ Info: hyperparameter optimization with EKI configured with Dict{Any, Any}("n_features_opt" => 100, "n_cross_val_sets" => 2, "n_iteration" => 10, "cov_sample_multiplier" => 10.0, "inflation" => 0.0001, "n_ensemble" => 30, "train_fraction" => 0.8, "overfit" => 1.0, "cov_correction" => "nice", "scheduler" => DataMisfitController (T=1000.0, "stop"), "localization" => EnsembleKalmanProcesses.Localizers.NoLocalization(), "verbose" => true, "multithread" => "ensemble", "accelerator" => NesterovAccelerator (θ_prev=1.0)) [ Info: hyperparameter optimization with EKI configured with Dict{Any, Any}("n_features_opt" => 100, "n_cross_val_sets" => 2, "n_iteration" => 10, "cov_sample_multiplier" => 10.0, "inflation" => 0.0001, "n_ensemble" => 70, "train_fraction" => 0.8, "overfit" => 1.0, "cov_correction" => "shrinkage", "scheduler" => DataMisfitController (T=1000.0, "stop"), "localization" => EnsembleKalmanProcesses.Localizers.NoLocalization(), "verbose" => true, "multithread" => "ensemble", "accelerator" => NesterovAccelerator (θ_prev=1.0)) [ Info: hyperparameter optimization with EKI configured with Dict{Any, Any}("n_features_opt" => 100, "n_cross_val_sets" => 2, "n_iteration" => 10, "cov_sample_multiplier" => 10.0, "inflation" => 0.0001, "n_ensemble" => 100, "train_fraction" => 0.8, "overfit" => 1.0, "cov_correction" => "nice", "scheduler" => DataMisfitController (T=1000.0, "stop"), "localization" => EnsembleKalmanProcesses.Localizers.NoLocalization(), "verbose" => true, "multithread" => "ensemble", "accelerator" => NesterovAccelerator (θ_prev=1.0)) [ Info: Initialize encoding of data: "in" with Decorrelator: decorrelate_with=sample_cov ┌ Warning: SVD representation is efficient when estimating high-dimensional covariance with few samples. │ here # samples is 100, while the space dimension is 2, and representation will be inefficient. └ @ EnsembleKalmanProcesses ~/.julia/packages/EnsembleKalmanProcesses/1ArOR/src/Observations.jl:203 [ Info: Initialize encoding of data: "out" with Decorrelator: decorrelate_with=structure_mat [ Info: hyperparameter learning for 2 models using 80 training points, 20 validation points and 100 features estimating covariances with 220 iterations... estimating covariances with 220 iterations... [ Info: Initialize encoding of data: "in" with Decorrelator: decorrelate_with=sample_cov ┌ Warning: SVD representation is efficient when estimating high-dimensional covariance with few samples. │ here # samples is 100, while the space dimension is 2, and representation will be inefficient. └ @ EnsembleKalmanProcesses ~/.julia/packages/EnsembleKalmanProcesses/1ArOR/src/Observations.jl:203 [ Info: Initialize encoding of data: "out" with Decorrelator: decorrelate_with=structure_mat [ Info: hyperparameter learning for 2 models using 80 training points, 20 validation points and 100 features [ Info: training model 1 / 2 estimating covariances with 220 iterations... estimate cov with 220 iterations... [ Info: NICE-adjusted covariance condition number: 834655.6931085319 estimate cov with 220 iterations... [ Info: NICE-adjusted covariance condition number: 925662.4258513964 ┌ Info: Initializing ensemble Kalman process of type TransformInversion │ Number of ensemble members: 30 │ Localization: NoLocalization │ Failure handler: SampleSuccGauss │ Scheduler: DataMisfitController └ Accelerator: NesterovAccelerator [ Info: Iteration 0 (prior) [ Info: Covariance trace: 0.0037326842632157504 [ Info: Iteration 1 (T=0.06209958765370388) ┌ Info: Covariance-weighted error: 6.251668214087118 │ Covariance trace: 0.0031881695794346745 └ Covariance trace ratio (current/previous): 0.8541224905768027 [ Info: Iteration 2 (T=0.12850891632570557) ┌ Info: Covariance-weighted error: 6.384248191457677 │ Covariance trace: 0.0021546987664638195 └ Covariance trace ratio (current/previous): 0.6758419565768174 [ Info: Iteration 3 (T=0.21017787453887876) ┌ Info: Covariance-weighted error: 5.05227387168111 │ Covariance trace: 0.001326044182689095 └ Covariance trace ratio (current/previous): 0.6154197530197366 [ Info: Iteration 4 (T=0.4022422241860386) ┌ Info: Covariance-weighted error: 4.445401513417017 │ Covariance trace: 0.0007806611593116556 └ Covariance trace ratio (current/previous): 0.5887142898425504 [ Info: Iteration 5 (T=0.915578088071746) ┌ Info: Covariance-weighted error: 3.9539743135140872 │ Covariance trace: 0.00045273513710151206 └ Covariance trace ratio (current/previous): 0.5799380841499905 [ Info: Iteration 6 (T=2.330261648422027) ┌ Info: Covariance-weighted error: 3.8654138347259224 │ Covariance trace: 0.0001795846739188243 └ Covariance trace ratio (current/previous): 0.39666608399020264 [ Info: Iteration 7 (T=3.9441099461461064) ┌ Info: Covariance-weighted error: 3.823731450617741 │ Covariance trace: 8.563671194120617e-5 └ Covariance trace ratio (current/previous): 0.4768598014099778 [ Info: Iteration 8 (T=5.667160826768557) ┌ Info: Covariance-weighted error: 3.7942627125341977 │ Covariance trace: 5.566393947821595e-5 └ Covariance trace ratio (current/previous): 0.6500008958357951 [ Info: Iteration 9 (T=7.389319028008509) ┌ Info: Covariance-weighted error: 3.7619415842400024 │ Covariance trace: 4.447993237151296e-5 └ Covariance trace ratio (current/previous): 0.7990798493326214 [ Info: Iteration 10 (T=9.663808472958841) ┌ Info: Covariance-weighted error: 3.748127758214559 │ Covariance trace: 3.917143636251976e-5 └ Covariance trace ratio (current/previous): 0.8806541348881859 [ Info: EKI Optimization result: 2×4 Matrix{Any}: "name" "number of hyperparameters" "optimized value range" "99% prior mass" "input_cholesky" 3 (-0.00567582, 0.166886) (-0.1, 0.1) nothing [ Info: training model 2 / 2 estimating covariances with 220 iterations... estimate cov with 220 iterations... [ Info: NICE-adjusted covariance condition number: 16779.816862367294 estimate cov with 220 iterations... [ Info: NICE-adjusted covariance condition number: 39181.50874947761 ┌ Info: Initializing ensemble Kalman process of type TransformInversion │ Number of ensemble members: 30 │ Localization: NoLocalization │ Failure handler: SampleSuccGauss │ Scheduler: DataMisfitController └ Accelerator: NesterovAccelerator [ Info: Iteration 0 (prior) [ Info: Covariance trace: 0.00269964860789342 [ Info: Iteration 1 (T=0.06626555202375176) ┌ Info: Covariance-weighted error: 19.03741426909178 │ Covariance trace: 0.00228495083115847 └ Covariance trace ratio (current/previous): 0.8463882390017621 [ Info: Iteration 2 (T=0.13748439170794408) ┌ Info: Covariance-weighted error: 19.05593078334063 │ Covariance trace: 0.0016785745117801562 └ Covariance trace ratio (current/previous): 0.7346217209099063 [ Info: Iteration 3 (T=0.19947559206951523) ┌ Info: Covariance-weighted error: 19.27690054422326 │ Covariance trace: 0.0010235316105951732 └ Covariance trace ratio (current/previous): 0.6097623926802636 [ Info: Iteration 4 (T=0.28669955670589387) ┌ Info: Covariance-weighted error: 19.508803237216455 │ Covariance trace: 0.0006351493479431267 └ Covariance trace ratio (current/previous): 0.6205468803975617 [ Info: Iteration 5 (T=0.7274708042965776) ┌ Info: Covariance-weighted error: 18.92543488746707 │ Covariance trace: 0.0004032378891877524 └ Covariance trace ratio (current/previous): 0.6348709803349426 [ Info: Iteration 6 (T=0.8603943245376496) ┌ Info: Covariance-weighted error: 19.092859504210224 │ Covariance trace: 0.0003442041785734377 └ Covariance trace ratio (current/previous): 0.8536007845561658 [ Info: Iteration 7 (T=1.064512852020232) ┌ Info: Covariance-weighted error: 18.80788122903049 │ Covariance trace: 0.00039834830607126987 └ Covariance trace ratio (current/previous): 1.1573023538593685 [ Info: Iteration 8 (T=1.1165677547572257) ┌ Info: Covariance-weighted error: 18.631745795418148 │ Covariance trace: 0.0001866715639911529 └ Covariance trace ratio (current/previous): 0.4686139269229247 [ Info: Iteration 9 (T=1.198196717010798) ┌ Info: Covariance-weighted error: 18.36014083364775 │ Covariance trace: 0.0001895853298227459 └ Covariance trace ratio (current/previous): 1.0156090502982613 [ Info: Iteration 10 (T=1.265361939847843) ┌ Info: Covariance-weighted error: 14.740429139588246 │ Covariance trace: 0.00019050003407371124 └ Covariance trace ratio (current/previous): 1.0048247628222107 [ Info: EKI Optimization result: 2×4 Matrix{Any}: "name" "number of hyperparameters" "optimized value range" "99% prior mass" "input_cholesky" 3 (-0.161159, 0.247392) (-0.1, 0.1) nothing [ Info: Initialize encoding of data: "in" with Decorrelator: decorrelate_with=sample_cov ┌ Warning: SVD representation is efficient when estimating high-dimensional covariance with few samples. │ here # samples is 100, while the space dimension is 2, and representation will be inefficient. └ @ EnsembleKalmanProcesses ~/.julia/packages/EnsembleKalmanProcesses/1ArOR/src/Observations.jl:203 [ Info: Initialize encoding of data: "out" with Decorrelator: decorrelate_with=structure_mat [ Info: hyperparameter learning using 80 training points, 20 validation points and 100 features RF output structure matrix is not positive definite, correcting for use as a regularizer estimating covariances with 220 iterations... approx_σ2 not posdef approx_σ2 not posdef blockcovmat not posdef blockcovmat not posdef blockcovmat not posdef blockcovmat not posdef blockcovmat not posdef blockcovmat not posdef blockcovmat not posdef blockcovmat not posdef blockcovmat not posdef blockcovmat not posdef blockcovmat not posdef blockcovmat not posdef blockcovmat not posdef blockcovmat not posdef blockcovmat not posdef blockcovmat not posdef blockcovmat not posdef blockcovmat not posdef blockcovmat not posdef blockcovmat not posdef [ Info: Initialize encoding of data: "in" with Decorrelator: decorrelate_with=sample_cov ┌ Warning: SVD representation is efficient when estimating high-dimensional covariance with few samples. │ here # samples is 100, while the space dimension is 2, and representation will be inefficient. └ @ EnsembleKalmanProcesses ~/.julia/packages/EnsembleKalmanProcesses/1ArOR/src/Observations.jl:203 [ Info: Initialize encoding of data: "out" with Decorrelator: decorrelate_with=structure_mat [ Info: hyperparameter learning using 80 training points, 20 validation points and 100 features RF output structure matrix is not positive definite, correcting for use as a regularizer estimating covariances with 420 iterations... estimate cov with 420 iterations... ┌ Info: Shrinkage scale: 0.01857584493943915, (0 = none, 1 = revert to scaled Identity) └ shrinkage covariance condition number: 767.3504707403432 approx_σ2 not posdef estimate cov with 420 iterations... ┌ Info: Shrinkage scale: 0.017780753618457636, (0 = none, 1 = revert to scaled Identity) └ shrinkage covariance condition number: 827.2410056133164 approx_σ2 not posdef ┌ Info: Initializing ensemble Kalman process of type TransformInversion │ Number of ensemble members: 70 │ Localization: NoLocalization │ Failure handler: SampleSuccGauss │ Scheduler: DataMisfitController └ Accelerator: NesterovAccelerator blockcovmat not posdef blockcovmat not posdef [ Info: Iteration 0 (prior) [ Info: Covariance trace: 10.81173932420858 [ Info: Iteration 1 (T=0.08679496046383514) ┌ Info: Covariance-weighted error: 0.9173956801810156 │ Covariance trace: 4.247229724333537 └ Covariance trace ratio (current/previous): 0.3928350098881463 blockcovmat not posdef blockcovmat not posdef [ Info: Iteration 2 (T=0.2711306505206037) ┌ Info: Covariance-weighted error: 0.7002610862910758 │ Covariance trace: 2.558328663131475 └ Covariance trace ratio (current/previous): 0.6023523164932927 blockcovmat not posdef blockcovmat not posdef [ Info: Iteration 3 (T=0.46946096589713227) ┌ Info: Covariance-weighted error: 0.6741317734564375 │ Covariance trace: 1.83108152887422 └ Covariance trace ratio (current/previous): 0.7157335002582969 blockcovmat not posdef blockcovmat not posdef [ Info: Iteration 4 (T=1.1898481651388164) ┌ Info: Covariance-weighted error: 0.6375087303172222 │ Covariance trace: 0.9982164773103122 └ Covariance trace ratio (current/previous): 0.5451513007856251 blockcovmat not posdef blockcovmat not posdef [ Info: Iteration 5 (T=2.11515572169757) ┌ Info: Covariance-weighted error: 0.6351615720444429 │ Covariance trace: 0.46173345075934663 └ Covariance trace ratio (current/previous): 0.4625584342220882 blockcovmat not posdef blockcovmat not posdef [ Info: Iteration 6 (T=3.233164425737371) ┌ Info: Covariance-weighted error: 0.6351901926950994 │ Covariance trace: 0.24862253575955107 └ Covariance trace ratio (current/previous): 0.5384546762871031 blockcovmat not posdef blockcovmat not posdef [ Info: Iteration 7 (T=4.057009925222695) ┌ Info: Covariance-weighted error: 0.6473199489653049 │ Covariance trace: 0.18214111689849125 └ Covariance trace ratio (current/previous): 0.7326009942825311 blockcovmat not posdef blockcovmat not posdef [ Info: Iteration 8 (T=5.002775054187507) ┌ Info: Covariance-weighted error: 0.6395485969903829 │ Covariance trace: 0.15258557453065405 └ Covariance trace ratio (current/previous): 0.8377327268487722 blockcovmat not posdef blockcovmat not posdef [ Info: Iteration 9 (T=5.913184635856128) ┌ Info: Covariance-weighted error: 0.6379424226346915 │ Covariance trace: 0.13297015952591104 └ Covariance trace ratio (current/previous): 0.8714464649421868 blockcovmat not posdef blockcovmat not posdef [ Info: Iteration 10 (T=6.945500992823229) ┌ Info: Covariance-weighted error: 0.6355243822963963 │ Covariance trace: 0.11130377749544366 └ Covariance trace ratio (current/previous): 0.837058313626785 [ Info: EKI Optimization result: 5×4 Matrix{Any}: "name" "number of hyperparameters" "optimized value range" "99% prior mass" "input_lowrank_Kchol" 1 (0.157558, 0.157558) (-3.0, 3.0) "input_lowrank_U" 2 (-0.056766, 0.151481) (-0.67082, 0.67082) "output_lowrank_diagonal" 2 (0.0177428, 0.224772) (0.000554271, 90.2094) "output_lowrank_U" 2 (-0.213122, 0.00839033) (-0.67082, 0.67082) nothing [ Info: hyperparameter learning using 80 training points, 20 validation points and 100 features RF output structure matrix is not positive definite, correcting for use as a regularizer estimating covariances with 420 iterations... estimate cov with 420 iterations... ┌ Info: Shrinkage scale: 0.007484214226829029, (0 = none, 1 = revert to scaled Identity) └ shrinkage covariance condition number: 4331.738207970455 approx_σ2 not posdef estimate cov with 420 iterations... ┌ Info: Shrinkage scale: 0.008464829652387762, (0 = none, 1 = revert to scaled Identity) └ shrinkage covariance condition number: 3211.1859701324547 approx_σ2 not posdef ┌ Info: Initializing ensemble Kalman process of type TransformInversion │ Number of ensemble members: 70 │ Localization: NoLocalization │ Failure handler: SampleSuccGauss │ Scheduler: DataMisfitController └ Accelerator: NesterovAccelerator blockcovmat not posdef blockcovmat not posdef [ Info: Iteration 0 (prior) [ Info: Covariance trace: 10.81173932420858 [ Info: Iteration 1 (T=0.07740547903500797) ┌ Info: Covariance-weighted error: 1.2062739814540129 │ Covariance trace: 4.125667498071416 └ Covariance trace ratio (current/previous): 0.3815914696383429 blockcovmat not posdef blockcovmat not posdef [ Info: Iteration 2 (T=0.20552723221763072) ┌ Info: Covariance-weighted error: 1.0122563413844714 │ Covariance trace: 1.8867184254117566 └ Covariance trace ratio (current/previous): 0.4573122837198397 blockcovmat not posdef blockcovmat not posdef [ Info: Iteration 3 (T=0.3375753552595866) ┌ Info: Covariance-weighted error: 1.0363645108856803 │ Covariance trace: 1.0859099908775938 └ Covariance trace ratio (current/previous): 0.575554876791223 blockcovmat not posdef blockcovmat not posdef [ Info: Iteration 4 (T=0.5586219027512959) ┌ Info: Covariance-weighted error: 0.8966860324815066 │ Covariance trace: 0.7332611882922273 └ Covariance trace ratio (current/previous): 0.6752504300099788 blockcovmat not posdef blockcovmat not posdef [ Info: Iteration 5 (T=0.9219557326620711) ┌ Info: Covariance-weighted error: 0.7967966751914715 │ Covariance trace: 0.4592985572400971 └ Covariance trace ratio (current/previous): 0.6263778372203336 blockcovmat not posdef blockcovmat not posdef [ Info: Iteration 6 (T=1.477312575411997) ┌ Info: Covariance-weighted error: 0.7883230899852272 │ Covariance trace: 0.28442079986781715 └ Covariance trace ratio (current/previous): 0.6192503664215452 blockcovmat not posdef blockcovmat not posdef [ Info: Iteration 7 (T=2.1646533719324235) ┌ Info: Covariance-weighted error: 0.788961163456646 │ Covariance trace: 0.17548679821596533 └ Covariance trace ratio (current/previous): 0.6169970631455989 blockcovmat not posdef blockcovmat not posdef [ Info: Iteration 8 (T=3.028987079448933) ┌ Info: Covariance-weighted error: 0.7770534240506382 │ Covariance trace: 0.100408541989898 └ Covariance trace ratio (current/previous): 0.5721714853235216 blockcovmat not posdef blockcovmat not posdef [ Info: Iteration 9 (T=3.6600239572669224) ┌ Info: Covariance-weighted error: 0.7697300873137097 │ Covariance trace: 0.06285454738364428 └ Covariance trace ratio (current/previous): 0.625988049801261 blockcovmat not posdef blockcovmat not posdef [ Info: Iteration 10 (T=4.406719592720875) ┌ Info: Covariance-weighted error: 0.7706112504832463 │ Covariance trace: 0.04440369171087189 └ Covariance trace ratio (current/previous): 0.7064515386587036 [ Info: EKI Optimization result: 5×4 Matrix{Any}: "name" "number of hyperparameters" "optimized value range" "99% prior mass" "input_lowrank_Kchol" 1 (-0.92416, -0.92416) (-3.0, 3.0) "input_lowrank_U" 2 (-0.248896, 0.0373287) (-0.67082, 0.67082) "output_lowrank_diagonal" 2 (0.595257, 0.673462) (0.000554271, 90.2094) "output_lowrank_U" 2 (-0.142638, 0.479389) (-0.67082, 0.67082) nothing [ Info: hyperparameter learning using 80 training points, 20 validation points and 100 features RF output structure matrix is not positive definite, correcting for use as a regularizer estimating covariances with 420 iterations... estimate cov with 420 iterations... [ Info: NICE-adjusted covariance condition number: 59990.81837855801 approx_σ2 not posdef estimate cov with 420 iterations... [ Info: NICE-adjusted covariance condition number: 22530.6821947885 approx_σ2 not posdef ┌ Info: Initializing ensemble Kalman process of type TransformInversion │ Number of ensemble members: 100 │ Localization: NoLocalization │ Failure handler: SampleSuccGauss │ Scheduler: DataMisfitController └ Accelerator: NesterovAccelerator blockcovmat not posdef blockcovmat not posdef [ Info: Iteration 0 (prior) [ Info: Covariance trace: 17.20122191075149 [ Info: Iteration 1 (T=0.09250967197984093) ┌ Info: Covariance-weighted error: 0.6489701908440738 │ Covariance trace: 6.518523187872928 └ Covariance trace ratio (current/previous): 0.3789569846662217 blockcovmat not posdef blockcovmat not posdef [ Info: Iteration 2 (T=0.2307720959212926) ┌ Info: Covariance-weighted error: 0.5731448373902662 │ Covariance trace: 2.587215063596509 └ Covariance trace ratio (current/previous): 0.39690202658322493 blockcovmat not posdef blockcovmat not posdef [ Info: Iteration 3 (T=0.5124150315411042) ┌ Info: Covariance-weighted error: 0.5387772433161341 │ Covariance trace: 0.7829469251751785 └ Covariance trace ratio (current/previous): 0.3026215084287572 blockcovmat not posdef blockcovmat not posdef [ Info: Iteration 4 (T=0.881328049082305) ┌ Info: Covariance-weighted error: 0.5499049526211599 │ Covariance trace: 0.24543191598314032 └ Covariance trace ratio (current/previous): 0.313471971204468 blockcovmat not posdef blockcovmat not posdef [ Info: Iteration 5 (T=1.4042427136623408) ┌ Info: Covariance-weighted error: 0.5343280254498948 │ Covariance trace: 0.11144335539896073 └ Covariance trace ratio (current/previous): 0.454070347585178 blockcovmat not posdef blockcovmat not posdef [ Info: Iteration 6 (T=2.066853896105787) ┌ Info: Covariance-weighted error: 0.5145919595646994 │ Covariance trace: 0.0770117575230786 └ Covariance trace ratio (current/previous): 0.6910394724511029 blockcovmat not posdef blockcovmat not posdef [ Info: Iteration 7 (T=2.6613185021261803) ┌ Info: Covariance-weighted error: 0.5116128716597823 │ Covariance trace: 0.07467391027779806 └ Covariance trace ratio (current/previous): 0.9696429828318106 blockcovmat not posdef blockcovmat not posdef [ Info: Iteration 8 (T=3.2332199691730112) ┌ Info: Covariance-weighted error: 0.501460923511586 │ Covariance trace: 0.07237174373909402 └ Covariance trace ratio (current/previous): 0.969170403288918 blockcovmat not posdef blockcovmat not posdef [ Info: Iteration 9 (T=3.674447378401807) ┌ Info: Covariance-weighted error: 0.47239916662600423 │ Covariance trace: 0.07258283955531118 └ Covariance trace ratio (current/previous): 1.002916826447877 blockcovmat not posdef blockcovmat not posdef [ Info: Iteration 10 (T=4.181165262686504) ┌ Info: Covariance-weighted error: 0.43451119540669303 │ Covariance trace: 0.07117932094653981 └ Covariance trace ratio (current/previous): 0.9806632171272132 [ Info: EKI Optimization result: 3×4 Matrix{Any}: "name" "number of hyperparameters" "optimized value range" "99% prior mass" "full_lowrank_diagonal" 4 (0.373721, 0.709124) (0.000391928, 63.7877) "full_lowrank_U" 8 (-0.054207, 0.094652) (-0.237171, 0.237171) nothing [ Info: [0.031166062330643916, 0.013127605386072307, 0.009982479294303123, 0.028154349374682804, 0.0754734064894127, 0.06899620052871262] [ Info: Initialize encoding of data: "in" with Decorrelator: decorrelate_with=sample_cov ┌ Warning: SVD representation is efficient when estimating high-dimensional covariance with few samples. │ here # samples is 100, while the space dimension is 2, and representation will be inefficient. └ @ EnsembleKalmanProcesses ~/.julia/packages/EnsembleKalmanProcesses/1ArOR/src/Observations.jl:203 [ Info: Initialize encoding of data: "out" with Decorrelator: decorrelate_with=structure_mat [ Info: hyperparameter learning using 80 training points, 20 validation points and 100 features RF output structure matrix is not positive definite, correcting for use as a regularizer estimating covariances with 420 iterations... 0.0%┣ ┫ 0/420 [00:00<00:00, -0s/it]  0.2%┣ ┫ 1/420 [00:04 0.15 [ Info: Injecting nullspace noise: 0.20000000000184537 > 0.0 [ Info: Initialize encoding of data: "in" with ElementwiseScaler: MinMaxScaling Test the encode-decode for posterior samples: Error During Test at /home/pkgeval/.julia/packages/CalibrateEmulateSample/yapkx/test/MarkovChainMonteCarlo/runtests.jl:556 Got exception outside of a @test MethodError: no method matching +(::Vector{Float64}, ::Float64) For element-wise addition, use broadcasting with dot syntax: array .+ scalar The function `+` exists, but no method is defined for this combination of argument types. Closest candidates are: +(::Any, ::Any, !Matched::Any, !Matched::Any...) @ Base operators.jl:653 +(!Matched::ChainRulesCore.ZeroTangent, ::Any) @ ChainRulesCore ~/.julia/packages/ChainRulesCore/IZ7FD/src/tangent_arithmetic.jl:99 +(!Matched::Missing, ::Number) @ Base missing.jl:120 ... Stacktrace: [1] (::Base.Splat{typeof(+)})(args::Tuple{Vector{Float64}, Float64}) @ Base operators.jl:1366 [2] iterate(::Base.Generator{Base.Iterators.Zip{Tuple{Matrix{Vector{Float64}}, Matrix{Float64}}}, Base.Splat{typeof(+)}}) @ Base generator.jl:48 [inlined] [3] collect(itr::Base.Generator{Base.Iterators.Zip{Tuple{Matrix{Vector{Float64}}, Matrix{Float64}}}, Base.Splat{typeof(+)}}) @ Base array.jl:833 [inlined] [4] map(f::typeof(+), it::Matrix{Vector{Float64}}, iters::Matrix{Float64}) @ Base abstractarray.jl:3622 [inlined] [5] _broadcast_preserving_zero_d(::typeof(+), ::Matrix{Vector{Float64}}, ::Matrix{Float64}) @ Base arraymath.jl:13 [inlined] [6] +(::Matrix{Vector{Float64}}, ::Matrix{Float64}) @ Base arraymath.jl:49 [7] create_noise_injector(encoder_schedule::Vector{Any}, prior::ParameterDistribution{Parameterized, Constraint{BoundedAbove}, String}, noise_injector_threshold::Float64, noise_injector_scaling::Float64) @ CalibrateEmulateSample.Utilities ~/.julia/packages/CalibrateEmulateSample/yapkx/src/Utilities.jl:1185 [8] top-level scope @ ~/.julia/packages/CalibrateEmulateSample/yapkx/test/MarkovChainMonteCarlo/runtests.jl:303 [9] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined] [10] macro expansion @ ~/.julia/packages/CalibrateEmulateSample/yapkx/test/MarkovChainMonteCarlo/runtests.jl:559 [inlined] [11] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined] [12] macro expansion @ ~/.julia/packages/CalibrateEmulateSample/yapkx/test/MarkovChainMonteCarlo/runtests.jl:640 [inlined] [13] include(mapexpr::Function, mod::Module, _path::String) @ Base Base.jl:327 [14] macro expansion @ timing.jl:505 [inlined] [15] include_test(_module::String) @ Main ~/.julia/packages/CalibrateEmulateSample/yapkx/test/runtests.jl:15 [16] top-level scope @ ~/.julia/packages/CalibrateEmulateSample/yapkx/test/runtests.jl:21 [17] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined] [18] macro expansion @ ~/.julia/packages/CalibrateEmulateSample/yapkx/test/runtests.jl:33 [inlined] [19] include(mapexpr::Function, mod::Module, _path::String) @ Base Base.jl:327 [20] top-level scope @ none:6 [21] eval(m::Module, e::Any) @ Core boot.jl:521 [22] exec_options(opts::Base.JLOptions) @ Base client.jl:321 [23] _start() @ Base client.jl:596 Autodiff MCMC variants: Test Failed at /home/pkgeval/.julia/packages/CalibrateEmulateSample/yapkx/test/MarkovChainMonteCarlo/runtests.jl:657 Expression: mcmc_test_template(prior, σ2_y, em_1; bad_mcmc_params...) Expected: ArgumentError Thrown: TypeError TypeError: in DataContainer, in FT, expected FT<:Real, got Type{Vector{Float64}} Stacktrace: [1] DataContainer(data::Matrix{Vector{Float64}}; data_are_columns::Bool) @ EnsembleKalmanProcesses.DataContainers ~/.julia/packages/EnsembleKalmanProcesses/1ArOR/src/DataContainers.jl:0 [2] DataContainer(data::Matrix{Vector{Float64}}) @ EnsembleKalmanProcesses.DataContainers ~/.julia/packages/EnsembleKalmanProcesses/1ArOR/src/DataContainers.jl:30 [3] encode_data(encoder_schedule::Vector{Any}, data::Matrix{Vector{Float64}}, in_or_out::String) @ CalibrateEmulateSample.Utilities ~/.julia/packages/CalibrateEmulateSample/yapkx/src/Utilities.jl:822 [4] MCMCWrapper(mcmc_alg::BarkerSampling{GradFreeProtocol}, observation::Vector{Float64}, prior::ParameterDistribution{Parameterized, Constraint{Bounded}, String}, em_or_fmw::Emulator{Float64, Vector{Any}}; init_params::Vector{Any}, burnin::Int64, kwargs::@Kwargs{}) @ CalibrateEmulateSample.MarkovChainMonteCarlo ~/.julia/packages/CalibrateEmulateSample/yapkx/src/MarkovChainMonteCarlo.jl:603 [5] MCMCWrapper(mcmc_alg::BarkerSampling{GradFreeProtocol}, observation::Vector{Float64}, prior::ParameterDistribution{Parameterized, Constraint{Bounded}, String}, em_or_fmw::Emulator{Float64, Vector{Any}}) @ CalibrateEmulateSample.MarkovChainMonteCarlo ~/.julia/packages/CalibrateEmulateSample/yapkx/src/MarkovChainMonteCarlo.jl:571 [inlined] [6] MCMCWrapper(mcmc_alg::BarkerSampling{GradFreeProtocol}, observation::Observation{Vector{Vector{Float64}}, Vector{Diagonal{Float64, Vector{Float64}}}, Vector{Diagonal{Float64, Vector{Float64}}}, Vector{String}, Vector{UnitRange{Int64}}, Nothing}, prior::ParameterDistribution{Parameterized, Constraint{Bounded}, String}, em_or_fmw::Emulator{Float64, Vector{Any}}; kwargs::@Kwargs{}) @ CalibrateEmulateSample.MarkovChainMonteCarlo ~/.julia/packages/CalibrateEmulateSample/yapkx/src/MarkovChainMonteCarlo.jl:655 [inlined] [7] MCMCWrapper(mcmc_alg::BarkerSampling{GradFreeProtocol}, observation::Observation{Vector{Vector{Float64}}, Vector{Diagonal{Float64, Vector{Float64}}}, Vector{Diagonal{Float64, Vector{Float64}}}, Vector{String}, Vector{UnitRange{Int64}}, Nothing}, prior::ParameterDistribution{Parameterized, Constraint{Bounded}, String}, em_or_fmw::Emulator{Float64, Vector{Any}}) @ CalibrateEmulateSample.MarkovChainMonteCarlo ~/.julia/packages/CalibrateEmulateSample/yapkx/src/MarkovChainMonteCarlo.jl:648 [inlined] [8] mcmc_test_template(prior::ParameterDistribution{Parameterized, Constraint{Bounded}, String}, σ2_y::UniformScaling{Float64}, em::Emulator{Float64, Vector{Any}}; exp_name::String, mcmc_alg::BarkerSampling{GradFreeProtocol}, obs_sample::Observation{Vector{Vector{Float64}}, Vector{Diagonal{Float64, Vector{Float64}}}, Vector{Diagonal{Float64, Vector{Float64}}}, Vector{String}, Vector{UnitRange{Int64}}, Nothing}, init_params::Vector{Float64}, step::Float64, rng::MersenneTwister, target_acc::Float64, return_samples::Bool) @ Main ~/.julia/packages/CalibrateEmulateSample/yapkx/test/MarkovChainMonteCarlo/runtests.jl:260 [9] top-level scope @ ~/.julia/packages/CalibrateEmulateSample/yapkx/test/MarkovChainMonteCarlo/runtests.jl:303 [10] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined] [11] macro expansion @ ~/.julia/packages/CalibrateEmulateSample/yapkx/test/MarkovChainMonteCarlo/runtests.jl:647 [inlined] [12] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined] [13] macro expansion @ ~/.julia/packages/CalibrateEmulateSample/yapkx/test/MarkovChainMonteCarlo/runtests.jl:657 [inlined] [14] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:980 [inlined] [15] macro expansion @ ~/.julia/packages/CalibrateEmulateSample/yapkx/test/MarkovChainMonteCarlo/runtests.jl:657 [inlined] Stacktrace: [1] top-level scope @ ~/.julia/packages/CalibrateEmulateSample/yapkx/test/MarkovChainMonteCarlo/runtests.jl:303 [2] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined] [3] macro expansion @ ~/.julia/packages/CalibrateEmulateSample/yapkx/test/MarkovChainMonteCarlo/runtests.jl:647 [inlined] [4] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined] [5] macro expansion @ ~/.julia/packages/CalibrateEmulateSample/yapkx/test/MarkovChainMonteCarlo/runtests.jl:657 [inlined] ====================================================================================== Information request received. A stacktrace will print followed by a 1.0 second profile. --trace-compile is enabled during profile collection. ====================================================================================== cmd: /opt/julia/bin/julia 1311 running 1 of 1 signal (10): User defined signal 1 _ZN12_GLOBAL__N_18Verifier11visitMDNodeERKN4llvm6MDNodeENS0_19AreDebugLocsAllowedE at /opt/julia/bin/../lib/julia/libLLVM.so.21.1jl (unknown line) _ZN12_GLOBAL__N_18Verifier16visitInstructionERN4llvm11InstructionE at /opt/julia/bin/../lib/julia/libLLVM.so.21.1jl (unknown line) _ZN12_GLOBAL__N_18Verifier6verifyERKN4llvm8FunctionE at /opt/julia/bin/../lib/julia/libLLVM.so.21.1jl (unknown line) _ZN4llvm12verifyModuleERKNS_6ModuleEPNS_11raw_ostreamEPb at /opt/julia/bin/../lib/julia/libLLVM.so.21.1jl (unknown line) verifyLLVMIR at /source/src/pipeline.cpp:1072:21 run at /source/src/llvm-remove-addrspaces.cpp:432:5 run at /source/src/llvm-remove-addrspaces.cpp:456:65 run at /source/usr/include/llvm/IR/PassManagerInternal.h:91:41 _ZN4llvm11PassManagerINS_6ModuleENS_15AnalysisManagerIS1_JEEEJEE3runERS1_RS3_ at /opt/julia/bin/../lib/julia/libLLVM.so.21.1jl (unknown line) run at /source/src/pipeline.cpp:982:12 operator() at /source/src/jitlayers.cpp:1298:17 operator() at /source/src/jitlayers.cpp:1435:12 [inlined] optimizeModule at /source/src/jitlayers.cpp:2382:18 materialize at /source/src/jitlayers.cpp:905:31 _ZN4llvm3orc19MaterializationTask3runEv at /opt/julia/bin/../lib/julia/libLLVM.so.21.1jl (unknown line) dispatch at /source/src/julia-task-dispatcher.h:353:11 _ZN4llvm3orc16ExecutionSession22dispatchOutstandingMUsEv at /opt/julia/bin/../lib/julia/libLLVM.so.21.1jl (unknown line) _ZN4llvm3orc16ExecutionSession17OL_completeLookupESt10unique_ptrINS0_21InProgressLookupStateESt14default_deleteIS3_EESt10shared_ptrINS0_23AsynchronousSymbolQueryEESt8functionIFvRKNS_8DenseMapIPNS0_8JITDylibENS_8DenseSetINS0_15SymbolStringPtrENS_12DenseMapInfoISF_vEEEENSG_ISD_vEENS_6detail12DenseMapPairISD_SI_EEEEEE at /opt/julia/bin/../lib/julia/libLLVM.so.21.1jl (unknown line) _ZN4llvm3orc25InProgressFullLookupState8completeESt10unique_ptrINS0_21InProgressLookupStateESt14default_deleteIS3_EE at /opt/julia/bin/../lib/julia/libLLVM.so.21.1jl (unknown line) _ZN4llvm3orc16ExecutionSession19OL_applyQueryPhase1ESt10unique_ptrINS0_21InProgressLookupStateESt14default_deleteIS3_EENS_5ErrorE at /opt/julia/bin/../lib/julia/libLLVM.so.21.1jl (unknown line) _ZN4llvm3orc16ExecutionSession6lookupENS0_10LookupKindERKSt6vectorISt4pairIPNS0_8JITDylibENS0_19JITDylibLookupFlagsEESaIS8_EENS0_15SymbolLookupSetENS0_11SymbolStateENS_15unique_functionIFvNS_8ExpectedINS_8DenseMapINS0_15SymbolStringPtrENS0_17ExecutorSymbolDefENS_12DenseMapInfoISI_vEENS_6detail12DenseMapPairISI_SJ_EEEEEEEEESt8functionIFvRKNSH_IS6_NS_8DenseSetISI_SL_EENSK_IS6_vEENSN_IS6_SV_EEEEEE at /opt/julia/bin/../lib/julia/libLLVM.so.21.1jl (unknown line) publishCIs at /source/src/jitlayers.cpp:2085:14 jl_compile_codeinst_impl at /source/src/jitlayers.cpp:510:39 jl_compile_method_internal at /source/src/gf.c:3704:27 _jl_invoke at /source/src/gf.c:4159:16 [inlined] ijl_apply_generic at /source/src/gf.c:4393:12 jl_apply at /source/src/julia.h:2388:12 [inlined] do_call at /source/src/interpreter.c:123:26 eval_value at /source/src/interpreter.c:243:16 eval_stmt_value at /source/src/interpreter.c:194:23 [inlined] eval_body at /source/src/interpreter.c:706:13 eval_body at /source/src/interpreter.c:571:21 eval_body at /source/src/interpreter.c:563:21 eval_body at /source/src/interpreter.c:571:21 eval_body at /source/src/interpreter.c:571:21 eval_body at /source/src/interpreter.c:571:21 eval_body at /source/src/interpreter.c:563:21 eval_body at /source/src/interpreter.c:571:21 eval_body at /source/src/interpreter.c:571:21 eval_body at /source/src/interpreter.c:571:21 jl_interpret_toplevel_thunk at /source/src/interpreter.c:897:21 ijl_eval_thunk at /source/src/toplevel.c:768:18 jl_toplevel_eval_flex at /source/src/toplevel.c:712:26 jl_eval_toplevel_stmts at /source/src/toplevel.c:602:15 jl_toplevel_eval_flex at /source/src/toplevel.c:684:27 ijl_toplevel_eval at /source/src/toplevel.c:782:12 ijl_toplevel_eval_in at /source/src/toplevel.c:827:13 eval at ./boot.jl:521:0 (pc: 1) include_string at ./loading.jl:3132:0 (pc: 207) _jl_invoke at /source/src/gf.c:4167:23 [inlined] ijl_apply_generic at /source/src/gf.c:4393:12 _include at ./loading.jl:3192:0 (pc: 122) include at ./Base.jl:327:0 (pc: 1) IncludeInto at ./Base.jl:328:0 [inlined] macro expansion at ./timing.jl:505:0 [inlined] include_test at /home/pkgeval/.julia/packages/CalibrateEmulateSample/yapkx/test/runtests.jl:15:0 (pc: 6) unknown function (ip: 0x717cbf505fe2) at (unknown file) _jl_invoke at /source/src/gf.c:4167:23 [inlined] ijl_apply_generic at /source/src/gf.c:4393:12 jl_apply at /source/src/julia.h:2388:12 [inlined] do_call at /source/src/interpreter.c:123:26 eval_value at /source/src/interpreter.c:243:16 eval_stmt_value at /source/src/interpreter.c:194:23 [inlined] eval_body at /source/src/interpreter.c:706:13 eval_body at /source/src/interpreter.c:563:21 eval_body at /source/src/interpreter.c:571:21 eval_body at /source/src/interpreter.c:571:21 eval_body at /source/src/interpreter.c:571:21 jl_interpret_toplevel_thunk at /source/src/interpreter.c:897:21 ijl_eval_thunk at /source/src/toplevel.c:768:18 jl_toplevel_eval_flex at /source/src/toplevel.c:712:26 jl_eval_toplevel_stmts at /source/src/toplevel.c:602:15 jl_toplevel_eval_flex at /source/src/toplevel.c:684:27 ijl_toplevel_eval at /source/src/toplevel.c:782:12 ijl_toplevel_eval_in at /source/src/toplevel.c:827:13 eval at ./boot.jl:521:0 (pc: 1) include_string at ./loading.jl:3132:0 (pc: 207) _jl_invoke at /source/src/gf.c:4167:23 [inlined] ijl_apply_generic at /source/src/gf.c:4393:12 _include at ./loading.jl:3192:0 (pc: 122) include at ./Base.jl:327:0 (pc: 1) IncludeInto at ./Base.jl:328:0 (pc: 2) jfptr_IncludeInto_1.1 at /opt/julia/lib/julia/sys.so (unknown line) _jl_invoke at /source/src/gf.c:4167:23 [inlined] ijl_apply_generic at /source/src/gf.c:4393:12 jl_apply at /source/src/julia.h:2388:12 [inlined] do_call at /source/src/interpreter.c:123:26 eval_value at /source/src/interpreter.c:243:16 eval_stmt_value at /source/src/interpreter.c:194:23 [inlined] eval_body at /source/src/interpreter.c:706:13 jl_interpret_toplevel_thunk at /source/src/interpreter.c:897:21 ijl_eval_thunk at /source/src/toplevel.c:768:18 jl_toplevel_eval_flex at /source/src/toplevel.c:712:26 jl_eval_toplevel_stmts at /source/src/toplevel.c:602:15 jl_toplevel_eval_flex at /source/src/toplevel.c:684:27 ijl_toplevel_eval at /source/src/toplevel.c:782:12 ijl_toplevel_eval_in at /source/src/toplevel.c:827:13 eval at ./boot.jl:521:0 (pc: 1) exec_options at ./client.jl:321:0 (pc: 425) _start at ./client.jl:596:0 (pc: 294) jfptr__start_0.1 at /opt/julia/lib/julia/sys.so (unknown line) _jl_invoke at /source/src/gf.c:4167:23 [inlined] ijl_apply_generic at /source/src/gf.c:4393:12 jl_apply at /source/src/julia.h:2388:12 [inlined] true_main at /source/src/jlapi.c:971:29 jl_repl_entrypoint at /source/src/jlapi.c:1138:15 main at /source/cli/loader_exe.c:58:15 unknown function (ip: 0x717cd9b77249) at /lib/x86_64-linux-gnu/libc.so.6 __libc_start_main at /lib/x86_64-linux-gnu/libc.so.6 (unknown line) unknown function (ip: 0x4010b8) at /workspace/srcdir/glibc-2.17/csu/../sysdeps/x86_64/start.S unknown function (ip: (nil)) at (unknown file) #= 113.6 ms =# precompile(Tuple{typeof(Core.kwcall), NamedTuple{(:backtrace,), Tuple{Bool}}, typeof(Base.showerror), Base.IOContext{Base.GenericIOBuffer{Memory{UInt8}}}, FieldError, Array{Union{Ptr{Nothing}, Base.InterpreterIP}, 1}}) #= 202.4 ms =# precompile(Tuple{typeof(Base.fielderror_listfields_hint_handler), Base.IOContext{Base.GenericIOBuffer{Memory{UInt8}}}, FieldError}) #= 39.8 ms =# precompile(Tuple{typeof(Core.kwcall), NamedTuple{(:context,), Tuple{Pair{Symbol, Bool}}}, typeof(Base.sprint), Function, FieldError}) #= 77.7 ms =# precompile(Tuple{Base.var"##sprint#440", Pair{Symbol, Bool}, Int64, typeof(Base.sprint), typeof(Base.show), FieldError}) Autodiff MCMC variants: Error During Test at /home/pkgeval/.julia/packages/CalibrateEmulateSample/yapkx/test/MarkovChainMonteCarlo/runtests.jl:658 Test threw exception #= 25.0 ms =# precompile(Tuple{typeof(Base.println), Base.PipeEndpoint, String, String}) Expression: contains(thrown.value.msg, "autodiff_gradient") ============================================================== Profile collected. A report will print at the next yield point. Disabling --trace-compile ============================================================== FieldError: type String has no field `msg`; String has no fields at all. Stacktrace: ┌ Warning: There were no samples collected in one or more groups. │ This may be due to idle threads, or you may need to run your │ program longer (perhaps by running it multiple times), │ or adjust the delay between samples with `Profile.init()`. └ @ Profile /opt/julia/share/julia/stdlib/v1.14/Profile/src/Profile.jl:1361 [1] getproperty(x::String, f::Symbol)Overhead ╎ [+additional indent] Count File:Line Function ========================================================= Thread 1 (default) Task 0x0000717cbf5fc010 Total snapshots: 87. Utilization: 100% ╎87 @Base/client.jl:596 _start() ╎ 87 @Base/client.jl:321 exec_options(opts::Base.JLOptions) ╎ 87 @Base/boot.jl:521 eval(m::Module, e::Any) ╎ 87 @Base/Base.jl:328 (::Base.IncludeInto)(fname::String) ╎ 87 @Base/Base.jl:327 include(mapexpr::Function, mod::Module, _path::Str… ╎ 87 @Base/loading.jl:3192 _include(mapexpr::Function, mod::Module, _pat… ╎ ╎ 87 @Base/loading.jl:3132 include_string(mapexpr::typeof(identity), mo… ╎ ╎ 87 @Base/boot.jl:521 eval(m::Module, e::Any) ╎ ╎ 87 @CalibrateEmulateSample/…:15 include_test(_module::String) ╎ ╎ 87 @Base/timing.jl:505 macro expansion ╎ ╎ 87 @Base/Base.jl:328 (::Base.IncludeInto)(fname::String) ╎ ╎ ╎ 87 @Base/Base.jl:327 include(mapexpr::Function, mod::Module, _pa… ╎ ╎ ╎ 87 @Base/loading.jl:3192 _include(mapexpr::Function, mod::Modul… ╎ ╎ ╎ 87 @Base/loading.jl:3132 include_string(mapexpr::typeof(identi… ╎ ╎ ╎ 87 @Base/boot.jl:521 eval(m::Module, e::Any) ╎ ╎ ╎ 65 @Test/src/Test.jl:848 do_test(result::Test.ExecutionResul… ╎ ╎ ╎ ╎ 46 @Test/src/Test.jl:246 Test.Error(test_type::Symbol, orig… ╎ ╎ ╎ ╎ 46 @Base/…ompiler.jl:268 kwcall(::@NamedTuple{context::Bas… ╎ ╎ ╎ ╎ 46 @Base/…ings/io.jl:102 kwcall(::@NamedTuple{context::Ba… ╎ ╎ ╎ ╎ 46 @Base/…ngs/io.jl:107 sprint(f::typeof(Base.show_excep… 11╎ ╎ ╎ ╎ 46 @Base/…orshow.jl:1331 show_exception_stack(io::IOCon… ╎ ╎ ╎ ╎ ╎ 6 @Compiler/…r.jl:1750 typeinf_ext_toplevel(mi::Core.… ╎ ╎ ╎ ╎ ╎ 6 @Compiler/…r.jl:1741 typeinf_ext_toplevel(interp::… ╎ ╎ ╎ ╎ ╎ 6 @Compiler/….jl:1537 typeinf_ext(interp::Compiler.… ╎ ╎ ╎ ╎ ╎ 2 @Compiler/….jl:4945 typeinf(interp::Compiler.Nat… ╎ ╎ ╎ ╎ ╎ 2 @Compiler/….jl:4667 typeinf_local(interp::Compi… ╎ ╎ ╎ ╎ ╎ ╎ 2 @Compiler/…jl:4083 abstract_eval_basic_stateme… ╎ ╎ ╎ ╎ ╎ ╎ 2 @Compiler/…jl:4126 abstract_eval_basic_statem… ╎ ╎ ╎ ╎ ╎ ╎ 2 @Compiler/…l:3670 abstract_eval_statement_ex… ╎ ╎ ╎ ╎ ╎ ╎ 2 @Compiler/…l:3300 abstract_eval_call(interp… ╎ ╎ ╎ ╎ ╎ ╎ 2 @Compiler/…l:3282 abstract_call(interp::Co… ╎ ╎ ╎ ╎ ╎ ╎ ╎ 2 @Compiler/…l:3131 abstract_call(interp::C… ╎ ╎ ╎ ╎ ╎ ╎ ╎ 2 @Compiler/…l:3138 abstract_call(interp::… ╎ ╎ ╎ ╎ ╎ ╎ ╎ 2 @Compiler/…l:3030 abstract_call_known(i… ╎ ╎ ╎ ╎ ╎ ╎ ╎ 2 @Compiler/…l:339 abstract_call_gf_by_t… ╎ ╎ ╎ ╎ ╎ ╎ ╎ 1 @Compiler/…l:178 (::Compiler.var"#inf… ╎ ╎ ╎ ╎ ╎ ╎ ╎ ╎ 1 @Compiler/…l:767 abstract_call_metho… ╎ ╎ ╎ ╎ ╎ ╎ ╎ ╎ 1 @Compiler/…l:1164 typeinf_edge(inte… ╎ ╎ ╎ ╎ ╎ ╎ ╎ ╎ 1 @Compiler/…l:1462 ci_get_source(in… 1╎ ╎ ╎ ╎ ╎ ╎ ╎ ╎ 1 @Base/…ls.jl:1658 _uncompressed_i… ╎ ╎ ╎ ╎ ╎ ╎ ╎ 1 @Compiler/…l:259 (::Compiler.var"#inf… ╎ ╎ ╎ ╎ ╎ ╎ ╎ ╎ 1 @Compiler/…l:189 (::Compiler.var"#ha… ╎ ╎ ╎ ╎ ╎ ╎ ╎ ╎ 1 @Compiler/…l:919 abstract_call_meth… ╎ ╎ ╎ ╎ ╎ ╎ ╎ ╎ 1 @Compiler/…l:937 abstract_call_met… ╎ ╎ ╎ ╎ ╎ ╎ ╎ ╎ 1 @Compiler/…l:1138 maybe_get_const… ╎ ╎ ╎ ╎ ╎ ╎ ╎ ╎ 1 @Compiler/…l:1263 force_const_pr… ╎ ╎ ╎ ╎ ╎ 4 @Compiler/….jl:4952 typeinf(interp::Compiler.Nat… ╎ ╎ ╎ ╎ ╎ 3 @Compiler/….jl:278 finish_nocycle(interp::Compi… ╎ ╎ ╎ ╎ ╎ ╎ 3 @Compiler/…jl:1034 optimize(interp::Compiler.N… ╎ ╎ ╎ ╎ ╎ ╎ 3 @Compiler/…jl:1061 run_passes_ipo_safe(ci::Co… ╎ ╎ ╎ ╎ ╎ ╎ 3 @Compiler/…l:1048 run_passes_ipo_safe(ci::Co… ╎ ╎ ╎ ╎ ╎ ╎ 1 @Compiler/…l:1345 slot2reg(ir::Compiler.IRC… ╎ ╎ ╎ ╎ ╎ ╎ 1 @Compiler/…l:738 construct_ssa!(ci::Core.C… ╎ ╎ ╎ ╎ ╎ ╎ ╎ 1 @Compiler/…l:440 Compiler.NewInstruction(… ╎ ╎ ╎ ╎ ╎ ╎ ╎ 1 @Compiler/…l:440 Compiler.NewInstruction… 1╎ ╎ ╎ ╎ ╎ ╎ ╎ 1 @Compiler/…l:436 Compiler.NewInstructio… ╎ ╎ ╎ ╎ ╎ ╎ 2 @Compiler/…l:76 ssa_inlining_pass!(ir::Comp… ╎ ╎ ╎ ╎ ╎ ╎ 1 @Compiler/…l:1582 assemble_inline_todo!(ir… ╎ ╎ ╎ ╎ ╎ ╎ ╎ 1 @Compiler/…l:1239 process_simple!(todo::V… ╎ ╎ ╎ ╎ ╎ ╎ ╎ 1 @Compiler/…l:1190 add_inst_flag!(inst::C… ╎ ╎ ╎ ╎ ╎ ╎ ╎ 1 @Compiler/…l:1193 add_inst_flag!(inst::… ╎ ╎ ╎ ╎ ╎ ╎ ╎ 1 @Compiler/…l:452 recompute_effects_fla… ╎ ╎ ╎ ╎ ╎ ╎ ╎ 1 @Compiler/…l:404 stmt_effect_flags(𝕃ₒ… ╎ ╎ ╎ ╎ ╎ ╎ ╎ ╎ 1 @Compiler/…l:2736 builtin_effects(𝕃:… ╎ ╎ ╎ ╎ ╎ ╎ ╎ ╎ 1 @Compiler/…l:2625 getfield_effects(… 1╎ ╎ ╎ ╎ ╎ ╎ ╎ ╎ 1 @Compiler/…l:477 is_immutable_argt… ╎ ╎ ╎ ╎ ╎ ╎ 1 @Compiler/…l:1615 assemble_inline_todo!(ir… ╎ ╎ ╎ ╎ ╎ ╎ ╎ 1 @Compiler/…l:1368 handle_call!(todo::Vect… ╎ ╎ ╎ ╎ ╎ ╎ ╎ 1 @Compiler/…l:1336 compute_inlining_cases… ╎ ╎ ╎ ╎ ╎ ╎ ╎ 1 @Compiler/…l:1272 kwcall(::@NamedTuple{… ╎ ╎ ╎ ╎ ╎ ╎ ╎ 1 @Compiler/…l:1283 handle_any_call_resu… ╎ ╎ ╎ ╎ ╎ ╎ ╎ 1 @Compiler/…l:1376 kwcall(::@NamedTupl… ╎ ╎ ╎ ╎ ╎ ╎ ╎ ╎ 1 @Compiler/…l:1387 handle_call_result… ╎ ╎ ╎ ╎ ╎ ╎ ╎ ╎ 1 @Compiler/…l:872 kwcall(::@NamedTup… ╎ ╎ ╎ ╎ ╎ ╎ ╎ ╎ 1 @Compiler/…l:905 analyze_method!(c… ╎ ╎ ╎ ╎ ╎ ╎ ╎ ╎ 1 @Base/…ls.jl:1833 specialize_meth… ╎ ╎ ╎ ╎ ╎ ╎ ╎ ╎ 1 @Base/…ls.jl:1834 specialize_met… ╎ ╎ ╎ ╎ ╎ ╎ ╎ ╎ +1 1 @Base/…ls.jl:1817 specialize_met… 1╎ ╎ ╎ ╎ ╎ ╎ ╎ ╎ +2 1 @Base/…ls.jl:1830 specialize_met… ╎ ╎ ╎ ╎ ╎ 1 @Compiler/….jl:285 finish_nocycle(interp::Compi… ╎ ╎ ╎ ╎ ╎ ╎ 1 @Compiler/….jl:153 finish!(interp::Compiler.Na… ╎ ╎ ╎ ╎ ╎ ╎ 1 @Compiler/…jl:296 ir_to_codeinf!(opt::Compile… ╎ ╎ ╎ ╎ ╎ ╎ 1 @Compiler/…jl:305 ir_to_codeinf!(src::Core.C… 1╎ ╎ ╎ ╎ ╎ ╎ 1 @Compiler/…l:313 widen_all_consts!(src::Cor… ╎ ╎ ╎ ╎ ╎ 29 @Base/…rshow.jl:107 kwcall(::@NamedTuple{backtrace:… ╎ ╎ ╎ ╎ ╎ 29 @Base/…rshow.jl:109 showerror(io::IOContext{IOBuff… ╎ ╎ ╎ ╎ ╎ 29 @Base/…rshow.jl:412 showerror(io::IOContext{IOBuf… 26╎ ╎ ╎ ╎ ╎ 29 @Base/…ntal.jl:326 show_error_hints(::Any, ::Any) ╎ ╎ ╎ ╎ ╎ 3 @Compiler/….jl:1750 typeinf_ext_toplevel(mi::Co… ╎ ╎ ╎ ╎ ╎ ╎ 1 @Compiler/…jl:1741 typeinf_ext_toplevel(interp… ╎ ╎ ╎ ╎ ╎ ╎ 1 @Compiler/…jl:1537 typeinf_ext(interp::Compil… ╎ ╎ ╎ ╎ ╎ ╎ 1 @Compiler/…l:4952 typeinf(interp::Compiler.N… ╎ ╎ ╎ ╎ ╎ ╎ 1 @Compiler/…l:278 finish_nocycle(interp::Com… ╎ ╎ ╎ ╎ ╎ ╎ 1 @Compiler/…l:1034 optimize(interp::Compile… ╎ ╎ ╎ ╎ ╎ ╎ ╎ 1 @Compiler/…l:1061 run_passes_ipo_safe(ci:… ╎ ╎ ╎ ╎ ╎ ╎ ╎ 1 @Compiler/…l:1048 run_passes_ipo_safe(ci… ╎ ╎ ╎ ╎ ╎ ╎ ╎ 1 @Compiler/…l:79 ssa_inlining_pass!(ir::… ╎ ╎ ╎ ╎ ╎ ╎ ╎ 1 @Compiler/…l:665 batch_inline!(ir::Com… ╎ ╎ ╎ ╎ ╎ ╎ ╎ 1 @Compiler/…l:581 ir_inline_unionsplit… ╎ ╎ ╎ ╎ ╎ ╎ ╎ ╎ 1 @Compiler/…l:414 ir_inline_item!(com… ╎ ╎ ╎ ╎ ╎ ╎ ╎ ╎ 1 @Compiler/…l:1234 setindex!(compact… ╎ ╎ ╎ ╎ ╎ ╎ ╎ ╎ 1 @Compiler/…l:1202 setindex!(compac… ╎ ╎ ╎ ╎ ╎ ╎ ╎ ╎ 1 @Compiler/…l:1194 kill_current_us… ╎ ╎ ╎ ╎ ╎ ╎ ╎ ╎ 1 @Compiler/…l:724 userefs(x::Any) ╎ ╎ ╎ ╎ ╎ ╎ ╎ ╎ +1 1 @Compiler/…l:661 is_relevant_exp… ╎ ╎ ╎ ╎ ╎ ╎ ╎ ╎ +2 1 @Base/…le.jl:683 in(x::Symbol, i… 1╎ ╎ ╎ ╎ ╎ ╎ ╎ ╎ +3 1 @Base/…le.jl:679 sym_in(x::Symbo… ╎ ╎ ╎ ╎ ╎ ╎ 2 @Compiler/…jl:1742 typeinf_ext_toplevel(interp… 2╎ ╎ ╎ ╎ ╎ ╎ 2 @Compiler/…jl:1736 add_codeinsts_to_jit!(inte… ╎ ╎ ╎ ╎ 19 @Test/src/Test.jl:258 Test.Error(test_type::Symbol, orig… 7╎ ╎ ╎ ╎ 19 @Base/…ompiler.jl:268 kwcall(::@NamedTuple{context::Pai… ╎ ╎ ╎ ╎ 1 @Compiler/…er.jl:1750 typeinf_ext_toplevel(mi::Core.Me… ╎ ╎ ╎ ╎ 1 @Compiler/…er.jl:1741 typeinf_ext_toplevel(interp::Co… ╎ ╎ ╎ ╎ 1 @Compiler/…er.jl:1537 typeinf_ext(interp::Compiler.N… ╎ ╎ ╎ ╎ ╎ 1 @Compiler/…n.jl:4952 typeinf(interp::Compiler.Nativ… ╎ ╎ ╎ ╎ ╎ 1 @Compiler/…r.jl:285 finish_nocycle(interp::Compile… ╎ ╎ ╎ ╎ ╎ 1 @Compiler/…r.jl:153 finish!(interp::Compiler.Nati… ╎ ╎ ╎ ╎ ╎ 1 @Compiler/….jl:296 ir_to_codeinf!(opt::Compiler.… ╎ ╎ ╎ ╎ ╎ 1 @Compiler/….jl:305 ir_to_codeinf!(src::Core.Cod… 1╎ ╎ ╎ ╎ ╎ ╎ 1 @Compiler/….jl:313 widen_all_consts!(src::Core… 10╎ ╎ ╎ ╎ 11 @Base/…ngs/io.jl:102 kwcall(::@NamedTuple{context::Pai… ╎ ╎ ╎ ╎ 1 @Compiler/…er.jl:1750 typeinf_ext_toplevel(mi::Core.M… ╎ ╎ ╎ ╎ 1 @Compiler/…er.jl:1741 typeinf_ext_toplevel(interp::C… ╎ ╎ ╎ ╎ ╎ 1 @Compiler/…r.jl:1537 typeinf_ext(interp::Compiler.N… ╎ ╎ ╎ ╎ ╎ 1 @Compiler/…n.jl:4936 typeinf(interp::Compiler.Nati… ╎ ╎ ╎ ╎ ╎ 1 @Compiler/….jl:1301 doworkloop(interp::Compiler.N… ╎ ╎ ╎ ╎ ╎ 1 @Compiler/….jl:189 (::Compiler.var"#handle1#abst… ╎ ╎ ╎ ╎ ╎ 1 @Compiler/….jl:919 abstract_call_method_with_co… ╎ ╎ ╎ ╎ ╎ ╎ 1 @Compiler/….jl:951 abstract_call_method_with_c… ╎ ╎ ╎ ╎ ╎ ╎ 1 @Compiler/…jl:1457 const_prop_call(interp::Co… ╎ ╎ ╎ ╎ ╎ ╎ 1 @Compiler/…l:4952 typeinf(interp::Compiler.N… ╎ ╎ ╎ ╎ ╎ ╎ 1 @Compiler/…l:278 finish_nocycle(interp::Com… ╎ ╎ ╎ ╎ ╎ ╎ 1 @Compiler/…l:1034 optimize(interp::Compile… ╎ ╎ ╎ ╎ ╎ ╎ ╎ 1 @Compiler/…l:1061 run_passes_ipo_safe(ci:… ╎ ╎ ╎ ╎ ╎ ╎ ╎ 1 @Compiler/…l:1048 run_passes_ipo_safe(ci… ╎ ╎ ╎ ╎ ╎ ╎ ╎ 1 @Compiler/…l:76 ssa_inlining_pass!(ir::… ╎ ╎ ╎ ╎ ╎ ╎ ╎ 1 @Compiler/…l:1615 assemble_inline_todo… ╎ ╎ ╎ ╎ ╎ ╎ ╎ 1 @Compiler/…l:1368 handle_call!(todo::… ╎ ╎ ╎ ╎ ╎ ╎ ╎ ╎ 1 @Compiler/…l:1336 compute_inlining_c… ╎ ╎ ╎ ╎ ╎ ╎ ╎ ╎ 1 @Compiler/…l:1272 kwcall(::@NamedTu… ╎ ╎ ╎ ╎ ╎ ╎ ╎ ╎ 1 @Compiler/…l:1283 handle_any_call_… ╎ ╎ ╎ ╎ ╎ ╎ ╎ ╎ 1 @Compiler/…l:1376 kwcall(::@Named… ╎ ╎ ╎ ╎ ╎ ╎ ╎ ╎ 1 @Compiler/…l:1387 handle_call_re… ╎ ╎ ╎ ╎ ╎ ╎ ╎ ╎ +1 1 @Compiler/…l:872 kwcall(::@Named… ╎ ╎ ╎ ╎ ╎ ╎ ╎ ╎ +2 1 @Compiler/…l:906 analyze_method!… ╎ ╎ ╎ ╎ ╎ ╎ ╎ ╎ +3 1 @Compiler/…l:853 resolve_todo(mi… ╎ ╎ ╎ ╎ ╎ ╎ ╎ ╎ +4 1 @Compiler/…l:936 retrieve_ir_for… ╎ ╎ ╎ ╎ ╎ ╎ ╎ ╎ +5 1 @Compiler/…l:197 simplify_ir!(re… ╎ ╎ ╎ ╎ ╎ ╎ ╎ ╎ +6 1 @Compiler/…l:2624 cfg_simplify!(… ╎ ╎ ╎ ╎ ╎ ╎ ╎ ╎ +7 1 @Base/…ot.jl:719 Vector{Int64}(:… 1╎ ╎ ╎ ╎ ╎ ╎ ╎ ╎ +8 1 @Base/…ot.jl:664 memoryref(mem::… ╎ ╎ ╎ 22 @Test/src/Test.jl:851 do_test(result::Test.ExecutionResul… ╎ ╎ ╎ ╎ 22 @Test/…rc/Test.jl:1568 record(ts::Test.DefaultTestSet, t… ╎ ╎ ╎ ╎ 22 @Test/…rc/Test.jl:1574 record(ts::Test.DefaultTestSet, … ╎ ╎ ╎ ╎ 22 @Base/coreio.jl:6 print(x::Test.Error) ╎ ╎ ╎ ╎ 22 @Base/…ings/io.jl:35 print(io::Base.PipeEndpoint, x::… 5╎ ╎ ╎ ╎ 5 @Test/…c/Test.jl:295 show(io::IO, t::Test.Error) 16╎ ╎ ╎ ╎ 17 @Test/…c/Test.jl:297 show(io::IO, t::Test.Error) ╎ ╎ ╎ ╎ ╎ 1 @Compiler/…r.jl:1750 typeinf_ext_toplevel(mi::Core.… ╎ ╎ ╎ ╎ ╎ 1 @Compiler/…r.jl:1742 typeinf_ext_toplevel(interp::… 1╎ ╎ ╎ ╎ ╎ 1 @Compiler/….jl:1736 add_codeinsts_to_jit!(interp:… @ Base Base_compiler.jl:58 [2] top-level scope @ ~/.julia/packages/CalibrateEmulateSample/yapkx/test/MarkovChainMonteCarlo/runtests.jl:303 [3] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined] [4] macro expansion @ ~/.julia/packages/CalibrateEmulateSample/yapkx/test/MarkovChainMonteCarlo/runtests.jl:647 [inlined] [5] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined] [6] macro expansion @ ~/.julia/packages/CalibrateEmulateSample/yapkx/test/MarkovChainMonteCarlo/runtests.jl:658 [inlined] [7] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:781 [inlined] ====================================================================================== Information request received. A stacktrace will print followed by a 1.0 second profile. --trace-compile is enabled during profile collection. ====================================================================================== cmd: /opt/julia/bin/julia 1 running 0 of 1 signal (10): User defined signal 1 epoll_pwait at /lib/x86_64-linux-gnu/libc.so.6 (unknown line) uv__io_poll at /workspace/srcdir/libuv/src/unix/linux.c:1404:0 uv_run at /workspace/srcdir/libuv/src/unix/core.c:430:0 ijl_task_get_next at /source/src/scheduler.c:524:34 Autodiff MCMC variants: Error During Test at /home/pkgeval/.julia/packages/CalibrateEmulateSample/yapkx/test/MarkovChainMonteCarlo/runtests.jl:659 Test threw exception Expression: contains(thrown.value.msg, "GradFreeProtocol") FieldError: type String has no field `msg`; String has no fields at all. Stacktrace: [1] getproperty(x::String, f::Symbol) @ Base Base_compiler.jl:58 [2] top-level scope @ ~/.julia/packages/CalibrateEmulateSample/yapkx/test/MarkovChainMonteCarlo/runtests.jl:303 [3] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined] [4] macro expansion @ ~/.julia/packages/CalibrateEmulateSample/yapkx/test/MarkovChainMonteCarlo/runtests.jl:647 [inlined] [5] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined] [6] macro expansion @ ~/.julia/packages/CalibrateEmulateSample/yapkx/test/MarkovChainMonteCarlo/runtests.jl:659 [inlined] [7] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:781 [inlined] Autodiff MCMC variants: Error During Test at /home/pkgeval/.julia/packages/CalibrateEmulateSample/yapkx/test/MarkovChainMonteCarlo/runtests.jl:660 Test threw exception Expression: contains(thrown.value.msg, "ForwardDiffProtocol") FieldError: type String has no field `msg`; String has no fields at all. Stacktrace: [1] getproperty(x::String, f::Symbol) @ Base Base_compiler.jl:58 [2] top-level scope @ ~/.julia/packages/CalibrateEmulateSample/yapkx/test/MarkovChainMonteCarlo/runtests.jl:303 [3] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined] [4] macro expansion @ ~/.julia/packages/CalibrateEmulateSample/yapkx/test/MarkovChainMonteCarlo/runtests.jl:647 [inlined] [5] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined] [6] macro expansion @ ~/.julia/packages/CalibrateEmulateSample/yapkx/test/MarkovChainMonteCarlo/runtests.jl:660 [inlined] [7] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:781 [inlined] wait at ./task.jl:1248:0 (pc: 107) wait_forever at ./task.jl:1170:0 (pc: 4) jfptr_wait_forever_0.1 at /opt/julia/lib/julia/sys.so (unknown line) _jl_invoke at /source/src/gf.c:4167:23 [inlined] ijl_apply_generic at /source/src/gf.c:4393:12 jl_apply at /source/src/julia.h:2388:12 [inlined] start_task at /source/src/task.c:1275:19 unknown function (ip: (nil)) at (unknown file) ============================================================== Profile collected. A report will print at the next yield point. Disabling --trace-compile ============================================================== Autodiff MCMC variants: Test Failed at /home/pkgeval/.julia/packages/CalibrateEmulateSample/yapkx/test/MarkovChainMonteCarlo/runtests.jl:666 Expression: mcmc_test_template(prior, σ2_y, em_1; bad_mcmc_params...) Expected: ArgumentError Thrown: TypeError TypeError: in DataContainer, in FT, expected FT<:Real, got Type{Vector{Float64}} Stacktrace: [1] DataContainer(data::Matrix{Vector{Float64}}; data_are_columns::Bool) @ EnsembleKalmanProcesses.DataContainers ~/.julia/packages/EnsembleKalmanProcesses/1ArOR/src/DataContainers.jl:0 [2] DataContainer(data::Matrix{Vector{Float64}}) @ EnsembleKalmanProcesses.DataContainers ~/.julia/packages/EnsembleKalmanProcesses/1ArOR/src/DataContainers.jl:30 [3] encode_data(encoder_schedule::Vector{Any}, data::Matrix{Vector{Float64}}, in_or_out::String) @ CalibrateEmulateSample.Utilities ~/.julia/packages/CalibrateEmulateSample/yapkx/src/Utilities.jl:822 [4] MCMCWrapper(mcmc_alg::BarkerSampling{ForwardDiffProtocol}, observation::Vector{Float64}, prior::ParameterDistribution{Parameterized, Constraint{Bounded}, String}, em_or_fmw::Emulator{Float64, Vector{Any}}; init_params::Vector{Any}, burnin::Int64, kwargs::@Kwargs{}) @ CalibrateEmulateSample.MarkovChainMonteCarlo ~/.julia/packages/CalibrateEmulateSample/yapkx/src/MarkovChainMonteCarlo.jl:603 [5] MCMCWrapper(mcmc_alg::BarkerSampling{ForwardDiffProtocol}, observation::Vector{Float64}, prior::ParameterDistribution{Parameterized, Constraint{Bounded}, String}, em_or_fmw::Emulator{Float64, Vector{Any}}) @ CalibrateEmulateSample.MarkovChainMonteCarlo ~/.julia/packages/CalibrateEmulateSample/yapkx/src/MarkovChainMonteCarlo.jl:571 [inlined] [6] MCMCWrapper(mcmc_alg::BarkerSampling{ForwardDiffProtocol}, observation::Observation{Vector{Vector{Float64}}, Vector{Diagonal{Float64, Vector{Float64}}}, Vector{Diagonal{Float64, Vector{Float64}}}, Vector{String}, Vector{UnitRange{Int64}}, Nothing}, prior::ParameterDistribution{Parameterized, Constraint{Bounded}, String}, em_or_fmw::Emulator{Float64, Vector{Any}}; kwargs::@Kwargs{}) @ CalibrateEmulateSample.MarkovChainMonteCarlo ~/.julia/packages/CalibrateEmulateSample/yapkx/src/MarkovChainMonteCarlo.jl:655 [inlined] [7] MCMCWrapper(mcmc_alg::BarkerSampling{ForwardDiffProtocol}, observation::Observation{Vector{Vector{Float64}}, Vector{Diagonal{Float64, Vector{Float64}}}, Vector{Diagonal{Float64, Vector{Float64}}}, Vector{String}, Vector{UnitRange{Int64}}, Nothing}, prior::ParameterDistribution{Parameterized, Constraint{Bounded}, String}, em_or_fmw::Emulator{Float64, Vector{Any}}) @ CalibrateEmulateSample.MarkovChainMonteCarlo ~/.julia/packages/CalibrateEmulateSample/yapkx/src/MarkovChainMonteCarlo.jl:648 [inlined] [8] mcmc_test_template(prior::ParameterDistribution{Parameterized, Constraint{Bounded}, String}, σ2_y::UniformScaling{Float64}, em::Emulator{Float64, Vector{Any}}; exp_name::String, mcmc_alg::BarkerSampling{ForwardDiffProtocol}, obs_sample::Observation{Vector{Vector{Float64}}, Vector{Diagonal{Float64, Vector{Float64}}}, Vector{Diagonal{Float64, Vector{Float64}}}, Vector{String}, Vector{UnitRange{Int64}}, Nothing}, init_params::Vector{Float64}, step::Float64, rng::MersenneTwister, target_acc::Float64, return_samples::Bool) @ Main ~/.julia/packages/CalibrateEmulateSample/yapkx/test/MarkovChainMonteCarlo/runtests.jl:260 [9] top-level scope @ ~/.julia/packages/CalibrateEmulateSample/yapkx/test/MarkovChainMonteCarlo/runtests.jl:303 [10] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined] [11] macro expansion @ ~/.julia/packages/CalibrateEmulateSample/yapkx/test/MarkovChainMonteCarlo/runtests.jl:647 [inlined] [12] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined] [13] macro expansion @ ~/.julia/packages/CalibrateEmulateSample/yapkx/test/MarkovChainMonteCarlo/runtests.jl:666 [inlined] [14] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:980 [inlined] [15] macro expansion @ ~/.julia/packages/CalibrateEmulateSample/yapkx/test/MarkovChainMonteCarlo/runtests.jl:666 [inlined] Stacktrace: [1] top-level scope @ ~/.julia/packages/CalibrateEmulateSample/yapkx/test/MarkovChainMonteCarlo/runtests.jl:303 [2] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined] [3] macro expansion @ ~/.julia/packages/CalibrateEmulateSample/yapkx/test/MarkovChainMonteCarlo/runtests.jl:647 [inlined] [4] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined] [5] macro expansion @ ~/.julia/packages/CalibrateEmulateSample/yapkx/test/MarkovChainMonteCarlo/runtests.jl:666 [inlined] Autodiff MCMC variants: Error During Test at /home/pkgeval/.julia/packages/CalibrateEmulateSample/yapkx/test/MarkovChainMonteCarlo/runtests.jl:667 Test threw exception Expression: contains(thrown.value.msg, "does not implement the required emulator interface") FieldError: type String has no field `msg`; String has no fields at all. Stacktrace: [1] getproperty(x::String, f::Symbol) @ Base Base_compiler.jl:58 [2] top-level scope @ ~/.julia/packages/CalibrateEmulateSample/yapkx/test/MarkovChainMonteCarlo/runtests.jl:303 [3] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined] [4] macro expansion @ ~/.julia/packages/CalibrateEmulateSample/yapkx/test/MarkovChainMonteCarlo/runtests.jl:647 [inlined] [5] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined] [6] macro expansion @ ~/.julia/packages/CalibrateEmulateSample/yapkx/test/MarkovChainMonteCarlo/runtests.jl:667 [inlined] [7] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:781 [inlined] [ Info: testing algorithm: RWMHSampling{GradFreeProtocol} Autodiff MCMC variants: Error During Test at /home/pkgeval/.julia/packages/CalibrateEmulateSample/yapkx/test/MarkovChainMonteCarlo/runtests.jl:646 Got exception outside of a @test TypeError: in DataContainer, in FT, expected FT<:Real, got Type{Vector{Float64}} Stacktrace: [1] DataContainer(data::Matrix{Vector{Float64}}; data_are_columns::Bool) @ EnsembleKalmanProcesses.DataContainers ~/.julia/packages/EnsembleKalmanProcesses/1ArOR/src/DataContainers.jl:0 [2] DataContainer(data::Matrix{Vector{Float64}}) @ EnsembleKalmanProcesses.DataContainers ~/.julia/packages/EnsembleKalmanProcesses/1ArOR/src/DataContainers.jl:30 [3] encode_data(encoder_schedule::Vector{Any}, data::Matrix{Vector{Float64}}, in_or_out::String) @ CalibrateEmulateSample.Utilities ~/.julia/packages/CalibrateEmulateSample/yapkx/src/Utilities.jl:822 [4] MCMCWrapper(mcmc_alg::RWMHSampling{GradFreeProtocol}, observation::Vector{Float64}, prior::ParameterDistribution{Parameterized, Constraint{Bounded}, String}, em_or_fmw::Emulator{Float64, Vector{Any}}; init_params::Vector{Any}, burnin::Int64, kwargs::@Kwargs{}) @ CalibrateEmulateSample.MarkovChainMonteCarlo ~/.julia/packages/CalibrateEmulateSample/yapkx/src/MarkovChainMonteCarlo.jl:603 [5] MCMCWrapper(mcmc_alg::RWMHSampling{GradFreeProtocol}, observation::Vector{Float64}, prior::ParameterDistribution{Parameterized, Constraint{Bounded}, String}, em_or_fmw::Emulator{Float64, Vector{Any}}) @ CalibrateEmulateSample.MarkovChainMonteCarlo ~/.julia/packages/CalibrateEmulateSample/yapkx/src/MarkovChainMonteCarlo.jl:571 [inlined] [6] MCMCWrapper(mcmc_alg::RWMHSampling{GradFreeProtocol}, observation::Observation{Vector{Vector{Float64}}, Vector{Diagonal{Float64, Vector{Float64}}}, Vector{Diagonal{Float64, Vector{Float64}}}, Vector{String}, Vector{UnitRange{Int64}}, Nothing}, prior::ParameterDistribution{Parameterized, Constraint{Bounded}, String}, em_or_fmw::Emulator{Float64, Vector{Any}}; kwargs::@Kwargs{}) @ CalibrateEmulateSample.MarkovChainMonteCarlo ~/.julia/packages/CalibrateEmulateSample/yapkx/src/MarkovChainMonteCarlo.jl:655 [inlined] [7] MCMCWrapper(mcmc_alg::RWMHSampling{GradFreeProtocol}, observation::Observation{Vector{Vector{Float64}}, Vector{Diagonal{Float64, Vector{Float64}}}, Vector{Diagonal{Float64, Vector{Float64}}}, Vector{String}, Vector{UnitRange{Int64}}, Nothing}, prior::ParameterDistribution{Parameterized, Constraint{Bounded}, String}, em_or_fmw::Emulator{Float64, Vector{Any}}) @ CalibrateEmulateSample.MarkovChainMonteCarlo ~/.julia/packages/CalibrateEmulateSample/yapkx/src/MarkovChainMonteCarlo.jl:648 [inlined] [8] mcmc_test_template(prior::ParameterDistribution{Parameterized, Constraint{Bounded}, String}, σ2_y::UniformScaling{Float64}, em::Emulator{Float64, Vector{Any}}; exp_name::String, mcmc_alg::RWMHSampling{GradFreeProtocol}, obs_sample::Observation{Vector{Vector{Float64}}, Vector{Diagonal{Float64, Vector{Float64}}}, Vector{Diagonal{Float64, Vector{Float64}}}, Vector{String}, Vector{UnitRange{Int64}}, Nothing}, init_params::Vector{Float64}, step::Float64, rng::MersenneTwister, target_acc::Float64, return_samples::Bool) @ Main ~/.julia/packages/CalibrateEmulateSample/yapkx/test/MarkovChainMonteCarlo/runtests.jl:260 [9] top-level scope @ ~/.julia/packages/CalibrateEmulateSample/yapkx/test/MarkovChainMonteCarlo/runtests.jl:303 [10] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined] [11] macro expansion @ ~/.julia/packages/CalibrateEmulateSample/yapkx/test/MarkovChainMonteCarlo/runtests.jl:647 [inlined] [12] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined] [13] macro expansion @ ~/.julia/packages/CalibrateEmulateSample/yapkx/test/MarkovChainMonteCarlo/runtests.jl:676 [inlined] [14] include(mapexpr::Function, mod::Module, _path::String) @ Base Base.jl:327 [15] macro expansion @ timing.jl:505 [inlined] [16] include_test(_module::String) @ Main ~/.julia/packages/CalibrateEmulateSample/yapkx/test/runtests.jl:15 [17] top-level scope @ ~/.julia/packages/CalibrateEmulateSample/yapkx/test/runtests.jl:21 [18] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined] [19] macro expansion @ ~/.julia/packages/CalibrateEmulateSample/yapkx/test/runtests.jl:33 [inlined] [20] include(mapexpr::Function, mod::Module, _path::String) @ Base Base.jl:327 [21] top-level scope @ none:6 [22] eval(m::Module, e::Any) @ Core boot.jl:521 [23] exec_options(opts::Base.JLOptions) @ Base client.jl:321 [24] _start() @ Base client.jl:596 Completed tests for MarkovChainMonteCarlo, 202 seconds elapsed Starting tests for Utilities ┌ Warning: There were no samples collected in one or more groups. │ This may be due to idle threads, or you may need to run your │ program longer (perhaps by running it multiple times), │ or adjust the delay between samples with `Profile.init()`. └ @ Profile /opt/julia/share/julia/stdlib/v1.14/Profile/src/Profile.jl:1361 Overhead ╎ [+additional indent] Count File:Line Function ========================================================= Thread 1 (default) Task 0x00007b4c068e90f0 Total snapshots: 417. Utilization: 0% ╎417 @Base/task.jl:1170 wait_forever() 416╎ 417 @Base/task.jl:1248 wait() ┌ Warning: For 2 parameters, the recommended minimum ensemble size (`N_ens`) is 20. Got `N_ens` = 10`. └ @ EnsembleKalmanProcesses ~/.julia/packages/EnsembleKalmanProcesses/1ArOR/src/EnsembleKalmanProcess.jl:262 [1] signal 15: Terminated in expression starting at /PkgEval.jl/scripts/evaluate.jl:214 epoll_pwait at /lib/x86_64-linux-gnu/libc.so.6 (unknown line) uv__io_poll at /workspace/srcdir/libuv/src/unix/linux.c:1404:0 uv_run at /workspace/srcdir/libuv/src/unix/core.c:430:0 ijl_task_get_next at /source/src/scheduler.c:524:34 wait at ./task.jl:1248:0 (pc: 107) wait_forever at ./task.jl:1170:0 (pc: 4) jfptr_wait_forever_0.1 at /opt/julia/lib/julia/sys.so (unknown line) _jl_invoke at /source/src/gf.c:4167:23 [inlined] ijl_apply_generic at /source/src/gf.c:4393:12 jl_apply at /source/src/julia.h:2388:12 [inlined] start_task at /source/src/task.c:1275:19 unknown function (ip: (nil)) at (unknown file) Allocations: 31329419 (Pool: 31328166; Big: 1253); GC: 41 [1311] signal 15: Terminated in expression starting at /home/pkgeval/.julia/packages/CalibrateEmulateSample/yapkx/test/Utilities/runtests.jl:12 unknown function (ip: 0x717cd9be7bf4) at /lib/x86_64-linux-gnu/libc.so.6 malloc at /lib/x86_64-linux-gnu/libc.so.6 (unknown line) operator new at /workspace/srcdir/gcc-15.2.0/libstdc++-v3/libsupc++/new_op.cc:50:22 _ZN4llvm5APInt12initSlowCaseERKS0_ at /opt/julia/bin/../lib/julia/libLLVM.so.21.1jl (unknown line) _ZNK4llvm13ConstantRange8truncateEj at /opt/julia/bin/../lib/julia/libLLVM.so.21.1jl (unknown line) _ZNK4llvm13ConstantRange8multiplyERKS0_ at /opt/julia/bin/../lib/julia/libLLVM.so.21.1jl (unknown line) _ZN4llvm15ScalarEvolution11getRangeRefEPKNS_4SCEVENS0_13RangeSignHintEj at /opt/julia/bin/../lib/julia/libLLVM.so.21.1jl (unknown line) _ZL21StrengthenNoWrapFlagsPN4llvm15ScalarEvolutionENS_9SCEVTypesENS_8ArrayRefIPKNS_4SCEVEEENS4_11NoWrapFlagsE at /opt/julia/bin/../lib/julia/libLLVM.so.21.1jl (unknown line) _ZN4llvm15ScalarEvolution10getAddExprERNS_15SmallVectorImplIPKNS_4SCEVEEENS2_11NoWrapFlagsEj at /opt/julia/bin/../lib/julia/libLLVM.so.21.1jl (unknown line) _ZN4llvm15ScalarEvolution10getAddExprEPKNS_4SCEVES3_NS1_11NoWrapFlagsEj at /opt/julia/bin/../lib/julia/libLLVM.so.21.1jl (unknown line) _ZN4llvm15ScalarEvolution20SimplifyICmpOperandsERNS_12CmpPredicateERPKNS_4SCEVES6_j at /opt/julia/bin/../lib/julia/libLLVM.so.21.1jl (unknown line) _ZN4llvm15ScalarEvolution16isKnownPredicateENS_12CmpPredicateEPKNS_4SCEVES4_ at /opt/julia/bin/../lib/julia/libLLVM.so.21.1jl (unknown line) _ZN4llvm15ScalarEvolution16howManyLessThansEPKNS_4SCEVES3_PKNS_4LoopEbbb at /opt/julia/bin/../lib/julia/libLLVM.so.21.1jl (unknown line) _ZN4llvm15ScalarEvolution24computeExitLimitFromICmpEPKNS_4LoopENS_12CmpPredicateEPKNS_4SCEVES7_bb at /opt/julia/bin/../lib/julia/libLLVM.so.21.1jl (unknown line) _ZN4llvm15ScalarEvolution24computeExitLimitFromICmpEPKNS_4LoopEPNS_8ICmpInstEbbb at /opt/julia/bin/../lib/julia/libLLVM.so.21.1jl (unknown line) _ZN4llvm15ScalarEvolution28computeExitLimitFromCondImplERNS0_14ExitLimitCacheEPKNS_4LoopEPNS_5ValueEbbb at /opt/julia/bin/../lib/julia/libLLVM.so.21.1jl (unknown line) _ZN4llvm15ScalarEvolution30computeExitLimitFromCondCachedERNS0_14ExitLimitCacheEPKNS_4LoopEPNS_5ValueEbbb at /opt/julia/bin/../lib/julia/libLLVM.so.21.1jl (unknown line) _ZN4llvm15ScalarEvolution33computeExitLimitFromCondFromBinOpERNS0_14ExitLimitCacheEPKNS_4LoopEPNS_5ValueEbbb at /opt/julia/bin/../lib/julia/libLLVM.so.21.1jl (unknown line) _ZN4llvm15ScalarEvolution28computeExitLimitFromCondImplERNS0_14ExitLimitCacheEPKNS_4LoopEPNS_5ValueEbbb at /opt/julia/bin/../lib/julia/libLLVM.so.21.1jl (unknown line) _ZN4llvm15ScalarEvolution30computeExitLimitFromCondCachedERNS0_14ExitLimitCacheEPKNS_4LoopEPNS_5ValueEbbb at /opt/julia/bin/../lib/julia/libLLVM.so.21.1jl (unknown line) _ZN4llvm15ScalarEvolution24computeExitLimitFromCondEPKNS_4LoopEPNS_5ValueEbbb at /opt/julia/bin/../lib/julia/libLLVM.so.21.1jl (unknown line) _ZN4llvm15ScalarEvolution16computeExitLimitEPKNS_4LoopEPNS_10BasicBlockEbb at /opt/julia/bin/../lib/julia/libLLVM.so.21.1jl (unknown line) _ZN4llvm15ScalarEvolution25computeBackedgeTakenCountEPKNS_4LoopEb at /opt/julia/bin/../lib/julia/libLLVM.so.21.1jl (unknown line) _ZN4llvm15ScalarEvolution20getBackedgeTakenInfoEPKNS_4LoopE at /opt/julia/bin/../lib/julia/libLLVM.so.21.1jl (unknown line) _ZN4llvm15ScalarEvolution25getSmallConstantTripCountEPKNS_4LoopEPKNS_10BasicBlockE at /opt/julia/bin/../lib/julia/libLLVM.so.21.1jl (unknown line) _ZL15tryToUnrollLoopPN4llvm4LoopERNS_13DominatorTreeEPNS_8LoopInfoERNS_15ScalarEvolutionERKNS_19TargetTransformInfoERNS_15AssumptionCacheERNS_25OptimizationRemarkEmitterEPNS_18BlockFrequencyInfoEPNS_18ProfileSummaryInfoEbibbbSt8optionalIjESK_SJ_IbESL_SL_SL_SL_SK_PNS_9AAResultsE at /opt/julia/bin/../lib/julia/libLLVM.so.21.1jl (unknown line) _ZN4llvm14LoopUnrollPass3runERNS_8FunctionERNS_15AnalysisManagerIS1_JEEE at /opt/julia/bin/../lib/julia/libLLVM.so.21.1jl (unknown line) run at /source/usr/include/llvm/IR/PassManagerInternal.h:91:41 _ZN4llvm11PassManagerINS_8FunctionENS_15AnalysisManagerIS1_JEEEJEE3runERS1_RS3_ at /opt/julia/bin/../lib/julia/libLLVM.so.21.1jl (unknown line) run at /source/usr/include/llvm/IR/PassManagerInternal.h:91:41 _ZN4llvm27ModuleToFunctionPassAdaptor3runERNS_6ModuleERNS_15AnalysisManagerIS1_JEEE at /opt/julia/bin/../lib/julia/libLLVM.so.21.1jl (unknown line) run at /source/usr/include/llvm/IR/PassManagerInternal.h:91:41 _ZN4llvm11PassManagerINS_6ModuleENS_15AnalysisManagerIS1_JEEEJEE3runERS1_RS3_ at /opt/julia/bin/../lib/julia/libLLVM.so.21.1jl (unknown line) run at /source/src/pipeline.cpp:982:12 operator() at /source/src/jitlayers.cpp:1298:17 operator() at /source/src/jitlayers.cpp:1435:12 [inlined] optimizeModule at /source/src/jitlayers.cpp:2382:18 materialize at /source/src/jitlayers.cpp:905:31 _ZN4llvm3orc19MaterializationTask3runEv at /opt/julia/bin/../lib/julia/libLLVM.so.21.1jl (unknown line) dispatch at /source/src/julia-task-dispatcher.h:353:11 _ZN4llvm3orc16ExecutionSession22dispatchOutstandingMUsEv at /opt/julia/bin/../lib/julia/libLLVM.so.21.1jl (unknown line) _ZN4llvm3orc16ExecutionSession17OL_completeLookupESt10unique_ptrINS0_21InProgressLookupStateESt14default_deleteIS3_EESt10shared_ptrINS0_23AsynchronousSymbolQueryEESt8functionIFvRKNS_8DenseMapIPNS0_8JITDylibENS_8DenseSetINS0_15SymbolStringPtrENS_12DenseMapInfoISF_vEEEENSG_ISD_vEENS_6detail12DenseMapPairISD_SI_EEEEEE at /opt/julia/bin/../lib/julia/libLLVM.so.21.1jl (unknown line) _ZN4llvm3orc25InProgressFullLookupState8completeESt10unique_ptrINS0_21InProgressLookupStateESt14default_deleteIS3_EE at /opt/julia/bin/../lib/julia/libLLVM.so.21.1jl (unknown line) _ZN4llvm3orc16ExecutionSession19OL_applyQueryPhase1ESt10unique_ptrINS0_21InProgressLookupStateESt14default_deleteIS3_EENS_5ErrorE at /opt/julia/bin/../lib/julia/libLLVM.so.21.1jl (unknown line) _ZN4llvm3orc16ExecutionSession6lookupENS0_10LookupKindERKSt6vectorISt4pairIPNS0_8JITDylibENS0_19JITDylibLookupFlagsEESaIS8_EENS0_15SymbolLookupSetENS0_11SymbolStateENS_15unique_functionIFvNS_8ExpectedINS_8DenseMapINS0_15SymbolStringPtrENS0_17ExecutorSymbolDefENS_12DenseMapInfoISI_vEENS_6detail12DenseMapPairISI_SJ_EEEEEEEEESt8functionIFvRKNSH_IS6_NS_8DenseSetISI_SL_EENSK_IS6_vEENSN_IS6_SV_EEEEEE at /opt/julia/bin/../lib/julia/libLLVM.so.21.1jl (unknown line) publishCIs at /source/src/jitlayers.cpp:2085:14 jl_compile_codeinst_impl at /source/src/jitlayers.cpp:510:39 jl_compile_method_internal at /source/src/gf.c:3704:27 _jl_invoke at /source/src/gf.c:4159:16 [inlined] ijl_apply_generic at /source/src/gf.c:4393:12 #get_obs#109 at /home/pkgeval/.julia/packages/EnsembleKalmanProcesses/1ArOR/src/Observations.jl:1172:0 (pc: 4) get_obs at /home/pkgeval/.julia/packages/EnsembleKalmanProcesses/1ArOR/src/Observations.jl:1169:0 [inlined] #get_obs#113 at /home/pkgeval/.julia/packages/EnsembleKalmanProcesses/1ArOR/src/Observations.jl:1196:0 [inlined] get_obs at /home/pkgeval/.julia/packages/EnsembleKalmanProcesses/1ArOR/src/Observations.jl:1196:0 (pc: 1) unknown function (ip: 0x717c35372022) at (unknown file) _jl_invoke at /source/src/gf.c:4167:23 [inlined] ijl_apply_generic at /source/src/gf.c:4393:12 #EnsembleKalmanProcess#127 at /home/pkgeval/.julia/packages/EnsembleKalmanProcesses/1ArOR/src/EnsembleKalmanProcess.jl:269:0 (pc: 277) _jl_invoke at /source/src/gf.c:4167:23 [inlined] ijl_apply_generic at /source/src/gf.c:4393:12 EnsembleKalmanProcess at /home/pkgeval/.julia/packages/EnsembleKalmanProcesses/1ArOR/src/EnsembleKalmanProcess.jl:240:0 (pc: 17) unknown function (ip: 0x717c35371fb5) at (unknown file) _jl_invoke at /source/src/gf.c:4167:23 [inlined] ijl_apply_generic at /source/src/gf.c:4393:12 #EnsembleKalmanProcess#128 at /home/pkgeval/.julia/packages/EnsembleKalmanProcesses/1ArOR/src/EnsembleKalmanProcess.jl:384:0 (pc: 104) _jl_invoke at /source/src/gf.c:4167:23 [inlined] ijl_apply_generic at /source/src/gf.c:4393:12 EnsembleKalmanProcess at /home/pkgeval/.julia/packages/EnsembleKalmanProcesses/1ArOR/src/EnsembleKalmanProcess.jl:338:0 (pc: 25) unknown function (ip: 0x717c35370d56) at (unknown file) _jl_invoke at /source/src/gf.c:4167:23 [inlined] ijl_apply_generic at /source/src/gf.c:4393:12 #EnsembleKalmanProcess#129 at /home/pkgeval/.julia/packages/EnsembleKalmanProcesses/1ArOR/src/EnsembleKalmanProcess.jl:404:0 (pc: 4) EnsembleKalmanProcess at /home/pkgeval/.julia/packages/EnsembleKalmanProcesses/1ArOR/src/EnsembleKalmanProcess.jl:397:0 (pc: 3) unknown function (ip: 0x717c3536e8f6) at (unknown file) _jl_invoke at /source/src/gf.c:4167:23 [inlined] ijl_apply_generic at /source/src/gf.c:4393:12 #EnsembleKalmanProcess#130 at /home/pkgeval/.julia/packages/EnsembleKalmanProcesses/1ArOR/src/EnsembleKalmanProcess.jl:417:0 (pc: 23) EnsembleKalmanProcess at /home/pkgeval/.julia/packages/EnsembleKalmanProcesses/1ArOR/src/EnsembleKalmanProcess.jl:407:0 (pc: 3) unknown function (ip: 0x717c3535f08a) at (unknown file) _jl_invoke at /source/src/gf.c:4167:23 [inlined] ijl_apply_generic at /source/src/gf.c:4393:12 jl_apply at /source/src/julia.h:2388:12 [inlined] do_call at /source/src/interpreter.c:123:26 eval_value at /source/src/interpreter.c:243:16 eval_body at /source/src/interpreter.c:594:35 eval_body at /source/src/interpreter.c:563:21 eval_body at /source/src/interpreter.c:571:21 eval_body at /source/src/interpreter.c:571:21 eval_body at /source/src/interpreter.c:571:21 jl_interpret_toplevel_thunk at /source/src/interpreter.c:897:21 ijl_eval_thunk at /source/src/toplevel.c:768:18 jl_toplevel_eval_flex at /source/src/toplevel.c:712:26 jl_eval_toplevel_stmts at /source/src/toplevel.c:602:15 jl_toplevel_eval_flex at /source/src/toplevel.c:684:27 ijl_toplevel_eval at /source/src/toplevel.c:782:12 ijl_toplevel_eval_in at /source/src/toplevel.c:827:13 eval at ./boot.jl:521:0 (pc: 1) include_string at ./loading.jl:3132:0 (pc: 207) _jl_invoke at /source/src/gf.c:4167:23 [inlined] ijl_apply_generic at /source/src/gf.c:4393:12 _include at ./loading.jl:3192:0 (pc: 122) include at ./Base.jl:327:0 (pc: 1) IncludeInto at ./Base.jl:328:0 [inlined] macro expansion at ./timing.jl:505:0 [inlined] include_test at /home/pkgeval/.julia/packages/CalibrateEmulateSample/yapkx/test/runtests.jl:15:0 (pc: 6) unknown function (ip: 0x717cbf505fe2) at (unknown file) _jl_invoke at /source/src/gf.c:4167:23 [inlined] ijl_apply_generic at /source/src/gf.c:4393:12 jl_apply at /source/src/julia.h:2388:12 [inlined] do_call at /source/src/interpreter.c:123:26 eval_value at /source/src/interpreter.c:243:16 eval_stmt_value at /source/src/interpreter.c:194:23 [inlined] eval_body at /source/src/interpreter.c:706:13 eval_body at /source/src/interpreter.c:563:21 eval_body at /source/src/interpreter.c:571:21 eval_body at /source/src/interpreter.c:571:21 eval_body at /source/src/interpreter.c:571:21 jl_interpret_toplevel_thunk at /source/src/interpreter.c:897:21 ijl_eval_thunk at /source/src/toplevel.c:768:18 jl_toplevel_eval_flex at /source/src/toplevel.c:712:26 jl_eval_toplevel_stmts at /source/src/toplevel.c:602:15 jl_toplevel_eval_flex at /source/src/toplevel.c:684:27 ijl_toplevel_eval at /source/src/toplevel.c:782:12 ijl_toplevel_eval_in at /source/src/toplevel.c:827:13 eval at ./boot.jl:521:0 (pc: 1) include_string at ./loading.jl:3132:0 (pc: 207) _jl_invoke at /source/src/gf.c:4167:23 [inlined] ijl_apply_generic at /source/src/gf.c:4393:12 _include at ./loading.jl:3192:0 (pc: 122) include at ./Base.jl:327:0 (pc: 1) IncludeInto at ./Base.jl:328:0 (pc: 2) jfptr_IncludeInto_1.1 at /opt/julia/lib/julia/sys.so (unknown line) _jl_invoke at /source/src/gf.c:4167:23 [inlined] ijl_apply_generic at /source/src/gf.c:4393:12 jl_apply at /source/src/julia.h:2388:12 [inlined] do_call at /source/src/interpreter.c:123:26 eval_value at /source/src/interpreter.c:243:16 eval_stmt_value at /source/src/interpreter.c:194:23 [inlined] eval_body at /source/src/interpreter.c:706:13 jl_interpret_toplevel_thunk at /source/src/interpreter.c:897:21 ijl_eval_thunk at /source/src/toplevel.c:768:18 jl_toplevel_eval_flex at /source/src/toplevel.c:712:26 jl_eval_toplevel_stmts at /source/src/toplevel.c:602:15 jl_toplevel_eval_flex at /source/src/toplevel.c:684:27 ijl_toplevel_eval at /source/src/toplevel.c:782:12 ijl_toplevel_eval_in at /source/src/toplevel.c:827:13 eval at ./boot.jl:521:0 (pc: 1) exec_options at ./client.jl:321:0 (pc: 425) _start at ./client.jl:596:0 (pc: 294) jfptr__start_0.1 at /opt/julia/lib/julia/sys.so (unknown line) _jl_invoke at /source/src/gf.c:4167:23 [inlined] ijl_apply_generic at /source/src/gf.c:4393:12 jl_apply at /source/src/julia.h:2388:12 [inlined] true_main at /source/src/jlapi.c:971:29 jl_repl_entrypoint at /source/src/jlapi.c:1138:15 main at /source/cli/loader_exe.c:58:15 unknown function (ip: 0x717cd9b77249) at /lib/x86_64-linux-gnu/libc.so.6 __libc_start_main at /lib/x86_64-linux-gnu/libc.so.6 (unknown line) unknown function (ip: 0x4010b8) at /workspace/srcdir/glibc-2.17/csu/../sysdeps/x86_64/start.S unknown function (ip: (nil)) at (unknown file) Allocations: 554033822 (Pool: 554030024; Big: 3798); GC: 479 PkgEval terminated after 2738.16s: test duration exceeded the time limit