Package evaluation to test SimilaritySearch on Julia 1.14.0-DEV.1741 (f7ebeb5678*) started at 2026-02-19T17:07:32.005 ################################################################################ # Set-up # Installing PkgEval dependencies (TestEnv)... Activating project at `~/.julia/environments/v1.14` Set-up completed after 13.4s ################################################################################ # Installation # Installing SimilaritySearch... Resolving package versions... Installed CommonWorldInvalidations ─ v1.0.0 Installed ManualMemory ───────────── v0.1.8 Installed MacroTools ─────────────── v0.5.16 Installed DataStructures ─────────── v0.18.22 Installed ConstructionBase ───────── v1.6.0 Installed CompositionsBase ───────── v0.1.2 Installed Adapt ──────────────────── v4.4.0 Installed StatsBase ──────────────── v0.33.21 Installed SIMDTypes ──────────────── v0.1.0 Installed Compat ─────────────────── v4.18.1 Installed DataAPI ────────────────── v1.16.0 Installed OrderedCollections ─────── v1.8.1 Installed ArrayInterface ─────────── v7.22.0 Installed Statistics ─────────────── v1.11.1 Installed StrideArraysCore ───────── v0.5.8 Installed PrecompileTools ────────── v1.3.3 Installed StatsAPI ───────────────── v1.8.0 Installed IrrationalConstants ────── v0.2.6 Installed ProgressMeter ──────────── v1.11.0 Installed LayoutPointers ─────────── v0.1.17 Installed SciMLPublic ────────────── v1.0.1 Installed Requires ───────────────── v1.3.1 Installed Distances ──────────────── v0.10.12 Installed StaticArrayInterface ───── v1.9.0 Installed LogExpFunctions ────────── v0.3.29 Installed IfElse ─────────────────── v0.1.1 Installed InverseFunctions ───────── v0.1.17 Installed Missings ───────────────── v1.2.0 Installed CloseOpenIntervals ─────── v0.1.13 Installed Preferences ────────────── v1.5.1 Installed Static ─────────────────── v1.3.1 Installed SortingAlgorithms ──────── v1.2.2 Installed ThreadingUtilities ─────── v0.5.5 Installed SearchModels ───────────── v0.5.0 Installed DocStringExtensions ────── v0.9.5 Installed Accessors ──────────────── v0.1.43 Installed SimilaritySearch ───────── v0.13.8 Updating `~/.julia/environments/v1.14/Project.toml` [053f045d] + SimilaritySearch v0.13.8 Updating `~/.julia/environments/v1.14/Manifest.toml` [7d9f7c33] + Accessors v0.1.43 [79e6a3ab] + Adapt v4.4.0 [4fba245c] + ArrayInterface v7.22.0 [fb6a15b2] + CloseOpenIntervals v0.1.13 [f70d9fcc] + CommonWorldInvalidations v1.0.0 [34da2185] + Compat v4.18.1 [a33af91c] + CompositionsBase v0.1.2 [187b0558] + ConstructionBase v1.6.0 [9a962f9c] + DataAPI v1.16.0 ⌅ [864edb3b] + DataStructures v0.18.22 [b4f34e82] + Distances v0.10.12 [ffbed154] + DocStringExtensions v0.9.5 [615f187c] + IfElse v0.1.1 [3587e190] + InverseFunctions v0.1.17 [92d709cd] + IrrationalConstants v0.2.6 [10f19ff3] + LayoutPointers v0.1.17 [2ab3a3ac] + LogExpFunctions v0.3.29 [1914dd2f] + MacroTools v0.5.16 [d125e4d3] + ManualMemory v0.1.8 [e1d29d7a] + Missings v1.2.0 [bac558e1] + OrderedCollections v1.8.1 [aea7be01] + PrecompileTools v1.3.3 [21216c6a] + Preferences v1.5.1 [92933f4c] + ProgressMeter v1.11.0 [ae029012] + Requires v1.3.1 [94e857df] + SIMDTypes v0.1.0 [431bcebd] + SciMLPublic v1.0.1 [0e966ebe] + SearchModels v0.5.0 [053f045d] + SimilaritySearch v0.13.8 [a2af1166] + SortingAlgorithms v1.2.2 [aedffcd0] + Static v1.3.1 [0d7ed370] + StaticArrayInterface v1.9.0 [10745b16] + Statistics v1.11.1 [82ae8749] + StatsAPI v1.8.0 ⌅ [2913bbd2] + StatsBase v0.33.21 [7792a7ef] + StrideArraysCore v0.5.8 [8290d209] + ThreadingUtilities v0.5.5 [56f22d72] + Artifacts v1.11.0 [2a0f44e3] + Base64 v1.11.0 [ade2ca70] + Dates v1.11.0 [8ba89e20] + Distributed v1.11.0 [b77e0a4c] + InteractiveUtils v1.11.0 [ac6e5ff7] + JuliaSyntaxHighlighting v1.13.0 [8f399da3] + Libdl v1.11.0 [37e2e46d] + LinearAlgebra v1.13.0 [d6f4376e] + Markdown v1.11.0 [de0858da] + Printf v1.11.0 [9a3f8284] + Random v1.11.0 [ea8e919c] + SHA v1.0.0 [9e88b42a] + Serialization v1.11.0 [6462fe0b] + Sockets v1.11.0 [2f01184e] + SparseArrays v1.13.0 [f489334b] + StyledStrings v1.13.0 [fa267f1f] + TOML v1.0.3 [cf7118a7] + UUIDs v1.11.0 [4ec0a83e] + Unicode v1.11.0 [e66e0078] + CompilerSupportLibraries_jll v1.3.0+1 [4536629a] + OpenBLAS_jll v0.3.30+0 [bea87d4a] + SuiteSparse_jll v7.10.1+0 [8e850b90] + libblastrampoline_jll v5.15.0+0 Info Packages marked with ⌅ have new versions available but compatibility constraints restrict them from upgrading. To see why use `status --outdated -m` Installation completed after 5.97s ################################################################################ # Precompilation # Precompiling PkgEval dependencies... Precompiling packages... 5136.9 ms ✓ TestEnv 1 dependency successfully precompiled in 5 seconds. 27 already precompiled. Precompiling package dependencies... Precompiling packages... 4870.7 ms ✓ MacroTools 1006.8 ms ✓ ManualMemory 1229.5 ms ✓ Statistics 950.9 ms ✓ DataAPI 931.0 ms ✓ SciMLPublic 1198.9 ms ✓ ConstructionBase 2240.4 ms ✓ IrrationalConstants 837.6 ms ✓ CommonWorldInvalidations 921.8 ms ✓ StatsAPI 1195.6 ms ✓ Requires 1318.5 ms ✓ OrderedCollections 994.0 ms ✓ InverseFunctions 865.6 ms ✓ CompositionsBase 1177.4 ms ✓ DocStringExtensions 810.8 ms ✓ IfElse 793.2 ms ✓ SIMDTypes 1888.1 ms ✓ ProgressMeter 1249.3 ms ✓ Compat 1205.1 ms ✓ Preferences 1877.6 ms ✓ ThreadingUtilities 1377.3 ms ✓ Statistics → SparseArraysExt 1001.5 ms ✓ Missings 794.2 ms ✓ ConstructionBase → ConstructionBaseLinearAlgebraExt 1499.8 ms ✓ Distances 947.5 ms ✓ Adapt 1742.3 ms ✓ InverseFunctions → InverseFunctionsTestExt 897.0 ms ✓ InverseFunctions → InverseFunctionsDatesExt 857.1 ms ✓ CompositionsBase → CompositionsBaseInverseFunctionsExt 1372.9 ms ✓ LogExpFunctions 866.2 ms ✓ Compat → CompatLinearAlgebraExt 945.7 ms ✓ PrecompileTools 1347.1 ms ✓ Distances → DistancesSparseArraysExt 1170.1 ms ✓ ArrayInterface 1338.0 ms ✓ Adapt → AdaptSparseArraysExt 5366.7 ms ✓ Accessors 868.7 ms ✓ LogExpFunctions → LogExpFunctionsInverseFunctionsExt 7080.7 ms ✓ Aqua 3941.6 ms ✓ DataStructures 7244.9 ms ✓ Static 1337.1 ms ✓ ArrayInterface → ArrayInterfaceSparseArraysExt 2344.2 ms ✓ Accessors → LinearAlgebraExt 1819.3 ms ✓ Accessors → TestExt 1544.0 ms ✓ SortingAlgorithms 5103.7 ms ✓ StaticArrayInterface 4964.1 ms ✓ StatsBase 1139.1 ms ✓ CloseOpenIntervals 1321.8 ms ✓ LayoutPointers 3041.8 ms ✓ SearchModels 2099.9 ms ✓ StrideArraysCore 6995.6 ms ✓ SimilaritySearch 50 dependencies successfully precompiled in 100 seconds. 33 already precompiled. Precompilation completed after 128.26s ################################################################################ # Testing # Testing SimilaritySearch Status `/tmp/jl_re0FU8/Project.toml` [7d9f7c33] Accessors v0.1.43 [4c88cf16] Aqua v0.8.14 [b4f34e82] Distances v0.10.12 [92933f4c] ProgressMeter v1.11.0 [0e966ebe] SearchModels v0.5.0 [053f045d] SimilaritySearch v0.13.8 [10745b16] Statistics v1.11.1 ⌅ [2913bbd2] StatsBase v0.33.21 [7792a7ef] StrideArraysCore v0.5.8 [ade2ca70] Dates v1.11.0 [37e2e46d] LinearAlgebra v1.13.0 [9a3f8284] Random v1.11.0 [2f01184e] SparseArrays v1.13.0 [8dfed614] Test v1.11.0 Status `/tmp/jl_re0FU8/Manifest.toml` [7d9f7c33] Accessors v0.1.43 [79e6a3ab] Adapt v4.4.0 [4c88cf16] Aqua v0.8.14 [4fba245c] ArrayInterface v7.22.0 [fb6a15b2] CloseOpenIntervals v0.1.13 [f70d9fcc] CommonWorldInvalidations v1.0.0 [34da2185] Compat v4.18.1 [a33af91c] CompositionsBase v0.1.2 [187b0558] ConstructionBase v1.6.0 [9a962f9c] DataAPI v1.16.0 ⌅ [864edb3b] DataStructures v0.18.22 [b4f34e82] Distances v0.10.12 [ffbed154] DocStringExtensions v0.9.5 [615f187c] IfElse v0.1.1 [3587e190] InverseFunctions v0.1.17 [92d709cd] IrrationalConstants v0.2.6 [10f19ff3] LayoutPointers v0.1.17 [2ab3a3ac] LogExpFunctions v0.3.29 [1914dd2f] MacroTools v0.5.16 [d125e4d3] ManualMemory v0.1.8 [e1d29d7a] Missings v1.2.0 [bac558e1] OrderedCollections v1.8.1 [aea7be01] PrecompileTools v1.3.3 [21216c6a] Preferences v1.5.1 [92933f4c] ProgressMeter v1.11.0 [ae029012] Requires v1.3.1 [94e857df] SIMDTypes v0.1.0 [431bcebd] SciMLPublic v1.0.1 [0e966ebe] SearchModels v0.5.0 [053f045d] SimilaritySearch v0.13.8 [a2af1166] SortingAlgorithms v1.2.2 [aedffcd0] Static v1.3.1 [0d7ed370] StaticArrayInterface v1.9.0 [10745b16] Statistics v1.11.1 [82ae8749] StatsAPI v1.8.0 ⌅ [2913bbd2] StatsBase v0.33.21 [7792a7ef] StrideArraysCore v0.5.8 [8290d209] ThreadingUtilities v0.5.5 [0dad84c5] ArgTools v1.1.2 [56f22d72] Artifacts v1.11.0 [2a0f44e3] Base64 v1.11.0 [ade2ca70] Dates v1.11.0 [8ba89e20] Distributed v1.11.0 [f43a241f] Downloads v1.7.0 [7b1f6079] FileWatching v1.11.0 [b77e0a4c] InteractiveUtils v1.11.0 [ac6e5ff7] JuliaSyntaxHighlighting v1.13.0 [b27032c2] LibCURL v1.0.0 [76f85450] LibGit2 v1.11.0 [8f399da3] Libdl v1.11.0 [37e2e46d] LinearAlgebra v1.13.0 [56ddb016] Logging v1.11.0 [d6f4376e] Markdown v1.11.0 [ca575930] NetworkOptions v1.3.0 [44cfe95a] Pkg v1.14.0 [de0858da] Printf v1.11.0 [9a3f8284] Random v1.11.0 [ea8e919c] SHA v1.0.0 [9e88b42a] Serialization v1.11.0 [6462fe0b] Sockets v1.11.0 [2f01184e] SparseArrays v1.13.0 [f489334b] StyledStrings v1.13.0 [fa267f1f] TOML v1.0.3 [a4e569a6] Tar v1.10.0 [8dfed614] Test v1.11.0 [cf7118a7] UUIDs v1.11.0 [4ec0a83e] Unicode v1.11.0 [e66e0078] CompilerSupportLibraries_jll v1.3.0+1 [deac9b47] LibCURL_jll v8.18.0+0 [e37daf67] LibGit2_jll v1.9.2+0 [29816b5a] LibSSH2_jll v1.11.3+1 [14a3606d] MozillaCACerts_jll v2025.12.2 [4536629a] OpenBLAS_jll v0.3.30+0 [458c3c95] OpenSSL_jll v3.5.5+0 [efcefdf7] PCRE2_jll v10.47.0+0 [bea87d4a] SuiteSparse_jll v7.10.1+0 [83775a58] Zlib_jll v1.3.1+2 [3161d3a3] Zstd_jll v1.5.7+1 [8e850b90] libblastrampoline_jll v5.15.0+0 [8e850ede] nghttp2_jll v1.68.0+1 [3f19e933] p7zip_jll v17.7.0+0 Info Packages marked with ⌅ have new versions available but compatibility constraints restrict them from upgrading. Testing Running tests... Test Summary: | Pass Total Time test database abstractions | 57 57 16.8s Test Summary: | Pass Total Time heap | 16 16 0.1s Test Summary: | Pass Total Time KnnHeap | 30005 30005 3.8s Test Summary: | Pass Total Time XKnn | 25005 25005 3.0s Test Summary: | Pass Total Time XKnn pop ops | 9603 9603 1.2s [ Info: (MatrixDatabase{Matrix{Float32}}, SubDatabase{MatrixDatabase{Matrix{Float32}}, Vector{Int64}}) 5.896537 seconds (400.99 k allocations: 24.701 MiB, 35.95% compilation time) 3.709886 seconds (7 allocations: 512 bytes) 5.766611 seconds (255.89 k allocations: 16.085 MiB, 34.86% compilation time) 3.745626 seconds (7 allocations: 512 bytes) 5.703521 seconds (239.64 k allocations: 15.178 MiB, 37.79% compilation time) 3.502791 seconds (7 allocations: 512 bytes) 5.629227 seconds (235.08 k allocations: 14.923 MiB, 36.38% compilation time) 3.600167 seconds (7 allocations: 512 bytes) 16.148774 seconds (247.56 k allocations: 15.587 MiB, 11.73% compilation time) 14.210972 seconds (7 allocations: 512 bytes) 27.116985 seconds (7 allocations: 512 bytes) 27.369850 seconds (7 allocations: 512 bytes) 20.861574 seconds (511.71 k allocations: 31.517 MiB, 7.69% compilation time) 19.161955 seconds (7 allocations: 512 bytes) 17.783248 seconds (406.88 k allocations: 25.466 MiB, 6.47% compilation time) 16.972809 seconds (7 allocations: 512 bytes) Test Summary: | Pass Total Time indexing vectors with ExhaustiveSearch | 8000 8000 3m22.6s [ Info: (VectorDatabase{Vector{Vector{Int64}}}, SubDatabase{VectorDatabase{Vector{Vector{Int64}}}, Vector{Int64}}) 4.274021 seconds (169.02 k allocations: 11.272 MiB, 1.60% gc time, 40.93% compilation time) 2.453463 seconds (7 allocations: 512 bytes) 29.671032 seconds (210.48 k allocations: 13.626 MiB, 6.12% compilation time) 27.707498 seconds (7 allocations: 528 bytes) 27.646953 seconds (7 allocations: 528 bytes) 27.610450 seconds (7 allocations: 528 bytes) 5.144652 seconds (152.92 k allocations: 9.926 MiB, 35.77% compilation time) 3.276702 seconds (7 allocations: 512 bytes) Test Summary: | Pass Total Time indexing sequences with ExhaustiveSearch | 4000 4000 2m09.7s [ Info: (VectorDatabase{Vector{Vector{Int64}}}, SubDatabase{VectorDatabase{Vector{Vector{Int64}}}, Vector{Int64}}) 11.568096 seconds (165.79 k allocations: 10.783 MiB, 14.33% compilation time) 9.977713 seconds (7 allocations: 512 bytes) 11.734066 seconds (154.66 k allocations: 10.078 MiB, 14.45% compilation time) 10.057816 seconds (7 allocations: 512 bytes) 11.752496 seconds (154.57 k allocations: 10.074 MiB, 14.53% compilation time) 10.001471 seconds (7 allocations: 512 bytes) Test Summary: | Pass Total Time indexing sets with ExhaustiveSearch | 3000 3000 1m07.2s 1.254844 seconds (227.56 k allocations: 14.252 MiB, 5.72% gc time, 96.79% compilation time) 0.040281 seconds (7 allocations: 512 bytes) 2.007048 seconds (235.80 k allocations: 15.066 MiB, 98.07% compilation time) 0.038788 seconds (7 allocations: 512 bytes) Test Summary: | Pass Total Time Normalized Cosine and Normalized Angle distances | 2000 2000 5.2s 2.158367 seconds (289.77 k allocations: 17.789 MiB, 97.44% compilation time) 0.057174 seconds (7 allocations: 512 bytes) Test Summary: | Pass Total Time Binary hamming distance | 1000 1000 2.8s allknn 2%|▉ | ETA: 0:03:35 allknn 100%|█████████████████████████████████████████████| Time: 0:00:04 ExhaustiveSearch allknn: 5.080306 seconds (1.81 M allocations: 110.501 MiB, 0.60% gc time, 99.95% compilation time) Test Summary: | Pass Total Time allknn | 1 1 5.3s quantile(length.(hsp_knns), 0:0.1:1) = [3.0, 4.0, 4.0, 4.0, 4.0, 4.0, 4.0, 4.0, 5.0, 5.0, 6.0] Test Summary: | Total Time HSP | 0 5.4s [ Info: neardup> starting: 1:100, current elements: 0, n: 100, ϵ: 0.1, timestamp: 2026-02-19T17:17:56.942 LOG add_vertex! sp=1 ep=1 n=1 BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2026-02-19T17:17:57.681 LOG n.size quantiles:[0.0, 0.0, 0.0, 0.0, 0.0] LOG add_vertex! sp=2 ep=2 n=2 BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2026-02-19T17:18:01.036 LOG n.size quantiles:[1.0, 1.0, 1.0, 1.0, 1.0] LOG add_vertex! sp=5 ep=9 n=4 BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2026-02-19T17:18:03.084 LOG n.size quantiles:[1.0, 2.0, 2.0, 2.0, 2.0] [ Info: neardup> finished current elements: 12, n: 100, ϵ: 0.1, timestamp: 2026-02-19T17:18:03.557 D.map = UInt32[0x00000001, 0x00000002, 0x00000003, 0x00000007, 0x00000009, 0x0000000b, 0x0000000e, 0x00000022, 0x00000030, 0x00000044, 0x0000005d, 0x0000005f] D.nn = Int32[1, 2, 3, 3, 1, 1, 7, 1, 9, 1, 11, 9, 9, 14, 14, 7, 1, 1, 9, 7, 1, 1, 11, 14, 2, 2, 11, 9, 7, 14, 2, 3, 3, 34, 1, 11, 2, 3, 3, 11, 34, 3, 9, 9, 1, 3, 11, 48, 11, 48, 1, 2, 3, 14, 7, 9, 48, 9, 1, 34, 9, 7, 1, 11, 48, 3, 34, 68, 9, 7, 68, 14, 14, 68, 2, 1, 1, 14, 48, 11, 7, 2, 11, 7, 48, 7, 1, 11, 11, 34, 48, 11, 93, 9, 95, 93, 93, 14, 9, 11] D.dist = Float32[0.0, 0.0, 0.0, 0.053242743, 0.011630833, 0.07508248, 0.0, 0.010545671, 0.0, 0.03357017, 0.0, 0.044772744, 0.053450286, 0.0, 0.016091228, 0.037350953, 0.062147856, 0.05768037, 0.09454423, 0.036830425, 0.020806551, 0.08483237, 0.07743555, 0.05142021, 0.07697016, 0.050526857, 0.044469535, 0.04352653, 0.051562488, 0.050738513, 0.030996084, 0.011872888, 0.033986032, 0.0, 0.007006705, 0.020004869, 0.080976605, 0.06735194, 0.01363039, 0.041792095, 0.038717806, 0.039270163, 0.052939475, 0.04357457, 0.05615866, 0.06202364, 0.034244955, 0.0, 0.009577334, 0.025219262, 0.036094308, 0.0419634, 0.027754247, 0.051286995, 0.06518948, 0.022545278, 0.008521736, 0.08160925, 0.02417624, 0.03688848, 0.0048692226, 0.037638426, 0.031674743, 0.04694599, 0.05217266, 0.013875604, 0.09111768, 0.0, 0.028819025, 0.026486754, 0.011133313, 0.059875727, 0.044933617, 0.03954506, 0.037974775, 0.012112856, 0.018227696, 0.06065184, 0.03312087, 0.056931257, 0.051261365, 0.03336966, 0.08425677, 0.0615021, 0.034631968, 0.03901446, 0.046931863, 0.08842683, 0.04693407, 0.065642774, 0.08071196, 0.035370648, 0.0, 0.024067163, 0.0, 0.061671793, 0.032922924, 0.0076129436, 0.043724537, 0.0099288225] Test Summary: | Pass Total Time neardup single block | 3 3 22.1s [ Info: neardup> starting: 1:16, current elements: 0, n: 100, ϵ: 0.1, timestamp: 2026-02-19T17:18:04.707 LOG add_vertex! sp=1 ep=1 n=1 BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2026-02-19T17:18:04.707 LOG n.size quantiles:[0.0, 0.0, 0.0, 0.0, 0.0] [ Info: neardup> range: 17:32, current elements: 7, n: 100, ϵ: 0.1, timestamp: 2026-02-19T17:18:07.978 [ Info: neardup> range: 33:48, current elements: 7, n: 100, ϵ: 0.1, timestamp: 2026-02-19T17:18:07.979 LOG add_vertex! sp=8 ep=9 n=7 BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2026-02-19T17:18:07.979 LOG n.size quantiles:[2.0, 2.0, 2.0, 2.0, 2.0] [ Info: neardup> range: 49:64, current elements: 9, n: 100, ϵ: 0.1, timestamp: 2026-02-19T17:18:07.980 [ Info: neardup> range: 65:80, current elements: 9, n: 100, ϵ: 0.1, timestamp: 2026-02-19T17:18:07.980 [ Info: neardup> range: 81:96, current elements: 10, n: 100, ϵ: 0.1, timestamp: 2026-02-19T17:18:07.980 [ Info: neardup> range: 97:100, current elements: 12, n: 100, ϵ: 0.1, timestamp: 2026-02-19T17:18:08.264 [ Info: neardup> finished current elements: 12, n: 100, ϵ: 0.1, timestamp: 2026-02-19T17:18:08.264 D.map = UInt32[0x00000001, 0x00000002, 0x00000003, 0x00000007, 0x00000009, 0x0000000b, 0x0000000e, 0x00000022, 0x00000030, 0x00000044, 0x0000005d, 0x0000005f] D.nn = Int32[1, 2, 3, 3, 1, 1, 7, 1, 9, 1, 11, 9, 9, 14, 14, 7, 1, 1, 9, 7, 1, 1, 11, 14, 2, 2, 11, 9, 7, 14, 2, 3, 3, 34, 1, 11, 2, 3, 3, 11, 9, 3, 9, 9, 1, 3, 11, 48, 11, 48, 1, 2, 3, 14, 7, 9, 48, 9, 1, 34, 9, 7, 1, 11, 48, 3, 34, 68, 9, 7, 34, 14, 14, 68, 2, 1, 1, 14, 48, 11, 7, 2, 11, 7, 48, 7, 1, 11, 11, 34, 48, 11, 93, 9, 95, 68, 93, 14, 9, 11] D.dist = Float32[0.0, 0.0, 0.0, 0.053242743, 0.011630833, 0.07508248, 0.0, 0.010545671, 0.0, 0.03357017, 0.0, 0.044772744, 0.053450286, 0.0, 0.016091228, 0.037350953, 0.062147856, 0.05768037, 0.09454423, 0.036830425, 0.020806551, 0.08483237, 0.07743555, 0.05142021, 0.07697016, 0.050526857, 0.044469535, 0.04352653, 0.051562488, 0.050738513, 0.030996084, 0.011872888, 0.033986032, 0.0, 0.007006705, 0.020004869, 0.080976605, 0.06735194, 0.01363039, 0.041792095, 0.072062254, 0.039270163, 0.052939475, 0.04357457, 0.05615866, 0.06202364, 0.034244955, 0.0, 0.009577334, 0.025219262, 0.036094308, 0.0419634, 0.027754247, 0.051286995, 0.06518948, 0.022545278, 0.008521736, 0.08160925, 0.02417624, 0.03688848, 0.0048692226, 0.037638426, 0.031674743, 0.04694599, 0.05217266, 0.013875604, 0.09111768, 0.0, 0.028819025, 0.026486754, 0.06297058, 0.059875727, 0.044933617, 0.03954506, 0.037974775, 0.012112856, 0.018227696, 0.06065184, 0.03312087, 0.056931257, 0.051261365, 0.03336966, 0.08425677, 0.0615021, 0.034631968, 0.03901446, 0.046931863, 0.08842683, 0.04693407, 0.065642774, 0.08071196, 0.035370648, 0.0, 0.024067163, 0.0, 0.06259799, 0.032922924, 0.0076129436, 0.043724537, 0.0099288225] Test Summary: | Pass Total Time neardup small block | 3 3 3.6s [ Info: neardup> starting: 1:16, current elements: 0, n: 100, ϵ: 0.1, timestamp: 2026-02-19T17:18:08.352 LOG add_vertex! sp=1 ep=1 n=1 BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2026-02-19T17:18:08.353 LOG n.size quantiles:[0.0, 0.0, 0.0, 0.0, 0.0] [ Info: neardup> range: 17:32, current elements: 16, n: 100, ϵ: 0.1, timestamp: 2026-02-19T17:18:08.354 [ Info: neardup> range: 33:48, current elements: 16, n: 100, ϵ: 0.1, timestamp: 2026-02-19T17:18:08.354 [ Info: neardup> range: 49:64, current elements: 16, n: 100, ϵ: 0.1, timestamp: 2026-02-19T17:18:08.354 [ Info: neardup> range: 65:80, current elements: 16, n: 100, ϵ: 0.1, timestamp: 2026-02-19T17:18:08.354 [ Info: neardup> range: 81:96, current elements: 16, n: 100, ϵ: 0.1, timestamp: 2026-02-19T17:18:08.354 [ Info: neardup> range: 97:100, current elements: 18, n: 100, ϵ: 0.1, timestamp: 2026-02-19T17:18:08.354 [ Info: neardup> finished current elements: 18, n: 100, ϵ: 0.1, timestamp: 2026-02-19T17:18:08.355 D.map = UInt32[0x00000001, 0x00000002, 0x00000003, 0x00000004, 0x00000005, 0x00000006, 0x00000007, 0x00000008, 0x00000009, 0x0000000a, 0x0000000b, 0x0000000c, 0x0000000d, 0x0000000e, 0x0000000f, 0x00000010, 0x0000005d, 0x0000005f] D.nn = Int32[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 10, 10, 9, 7, 5, 8, 11, 4, 15, 15, 11, 9, 7, 4, 2, 3, 4, 10, 1, 11, 2, 3, 3, 11, 9, 4, 13, 12, 4, 4, 13, 6, 11, 5, 4, 2, 3, 4, 16, 9, 5, 12, 6, 9, 9, 16, 8, 16, 6, 3, 10, 13, 9, 7, 6, 4, 15, 13, 2, 8, 10, 4, 4, 11, 10, 2, 5, 10, 5, 16, 8, 4, 11, 9, 10, 12, 93, 12, 95, 12, 93, 14, 12, 11] D.dist = Float32[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.036014497, 0.008600056, 0.09454423, 0.036830425, 0.008403599, 0.045086145, 0.07743555, 0.016146958, 0.04838568, 0.048401475, 0.044469535, 0.04352653, 0.051562488, 0.005626619, 0.030996084, 0.011872888, 0.007521808, 0.06393874, 0.007006705, 0.020004869, 0.080976605, 0.06735194, 0.01363039, 0.041792095, 0.072062254, 0.027789056, 0.02045399, 0.017352343, 0.015275061, 0.02297765, 0.029554069, 0.057239413, 0.009577334, 0.067786574, 0.024543464, 0.0419634, 0.027754247, 0.0021854043, 0.058829904, 0.022545278, 0.05823326, 0.017896652, 0.018162787, 0.07685369, 0.0048692226, 0.010595977, 0.015221477, 0.028027833, 0.0015767217, 0.013875604, 0.085841715, 0.07755607, 0.028819025, 0.026486754, 0.048580706, 0.042794645, 0.014282048, 0.095047, 0.037974775, 0.00582242, 0.0036183596, 0.010032475, 0.056985497, 0.056931257, 0.029122174, 0.03336966, 0.07412183, 0.03209579, 0.020489395, 0.005981028, 0.025716722, 0.0832932, 0.04693407, 0.074673414, 0.08385116, 0.01815021, 0.0, 0.0088300705, 0.0, 0.05509138, 0.032922924, 0.0076129436, 0.0027854443, 0.0099288225] Test Summary: | Pass Total Time neardup small block with filterblocks=false | 3 3 0.1s [ Info: neardup> starting: 1:16, current elements: 0, n: 100, ϵ: 0.1, timestamp: 2026-02-19T17:18:13.066 LOG append_items! ExhaustiveSearch{SimilaritySearch.DistanceWithIdentifiers{CosineDistance, MatrixDatabase{Matrix{Float32}}}, VectorDatabase{Vector{UInt32}}} sp=0 ep=7 n=7 2026-02-19T17:18:13.440 [ Info: neardup> range: 17:32, current elements: 7, n: 100, ϵ: 0.1, timestamp: 2026-02-19T17:18:14.606 [ Info: neardup> range: 33:48, current elements: 7, n: 100, ϵ: 0.1, timestamp: 2026-02-19T17:18:14.607 LOG append_items! ExhaustiveSearch{SimilaritySearch.DistanceWithIdentifiers{CosineDistance, MatrixDatabase{Matrix{Float32}}}, VectorDatabase{Vector{UInt32}}} sp=7 ep=9 n=9 2026-02-19T17:18:14.607 [ Info: neardup> range: 49:64, current elements: 9, n: 100, ϵ: 0.1, timestamp: 2026-02-19T17:18:14.613 [ Info: neardup> range: 65:80, current elements: 9, n: 100, ϵ: 0.1, timestamp: 2026-02-19T17:18:14.613 [ Info: neardup> range: 81:96, current elements: 10, n: 100, ϵ: 0.1, timestamp: 2026-02-19T17:18:14.613 [ Info: neardup> range: 97:100, current elements: 12, n: 100, ϵ: 0.1, timestamp: 2026-02-19T17:18:15.783 [ Info: neardup> finished current elements: 12, n: 100, ϵ: 0.1, timestamp: 2026-02-19T17:18:15.783 D.map = UInt32[0x00000001, 0x00000002, 0x00000003, 0x00000007, 0x00000009, 0x0000000b, 0x0000000e, 0x00000022, 0x00000030, 0x00000044, 0x0000005d, 0x0000005f] D.nn = Int32[1, 2, 3, 3, 1, 1, 7, 1, 9, 1, 11, 9, 9, 14, 14, 7, 1, 1, 9, 7, 1, 1, 11, 14, 2, 2, 11, 9, 7, 14, 2, 3, 3, 34, 1, 11, 2, 3, 3, 11, 9, 3, 9, 9, 1, 3, 11, 48, 11, 48, 1, 2, 3, 14, 7, 9, 48, 9, 1, 34, 9, 7, 1, 11, 48, 3, 34, 68, 9, 7, 34, 14, 14, 68, 2, 1, 1, 14, 48, 11, 7, 2, 11, 7, 48, 7, 1, 11, 11, 34, 48, 11, 93, 9, 95, 68, 93, 14, 9, 11] D.dist = Float32[0.0, 0.0, 0.0, 0.053242743, 0.011630833, 0.07508248, 0.0, 0.010545671, 0.0, 0.03357017, 0.0, 0.044772744, 0.053450286, 0.0, 0.016091228, 0.037350953, 0.062147856, 0.05768037, 0.09454423, 0.036830425, 0.020806551, 0.08483237, 0.07743555, 0.05142021, 0.07697016, 0.050526857, 0.044469535, 0.04352653, 0.051562488, 0.050738513, 0.030996084, 0.011872888, 0.033986032, 0.0, 0.007006705, 0.020004869, 0.080976605, 0.06735194, 0.01363039, 0.041792095, 0.072062254, 0.039270163, 0.052939475, 0.04357457, 0.05615866, 0.06202364, 0.034244955, 0.0, 0.009577334, 0.025219262, 0.036094308, 0.0419634, 0.027754247, 0.051286995, 0.06518948, 0.022545278, 0.008521736, 0.08160925, 0.02417624, 0.03688848, 0.0048692226, 0.037638426, 0.031674743, 0.04694599, 0.05217266, 0.013875604, 0.09111768, 0.0, 0.028819025, 0.026486754, 0.06297058, 0.059875727, 0.044933617, 0.03954506, 0.037974775, 0.012112856, 0.018227696, 0.06065184, 0.03312087, 0.056931257, 0.051261365, 0.03336966, 0.08425677, 0.0615021, 0.034631968, 0.03901446, 0.046931863, 0.08842683, 0.04693407, 0.065642774, 0.08071196, 0.035370648, 0.0, 0.024067163, 0.0, 0.06259799, 0.032922924, 0.0076129436, 0.043724537, 0.0099288225] Test Summary: | Pass Total Time neardup small block with filterblocks=false | 3 3 7.4s computing farthest point 1, dmax: Inf, imax: 12, n: 30 computing farthest point 2, dmax: 1.1287743, imax: 24, n: 30 computing farthest point 3, dmax: 0.8493014, imax: 6, n: 30 computing farthest point 4, dmax: 0.83833045, imax: 20, n: 30 computing farthest point 5, dmax: 0.7996192, imax: 2, n: 30 computing farthest point 6, dmax: 0.7581536, imax: 29, n: 30 computing farthest point 7, dmax: 0.7197044, imax: 11, n: 30 computing farthest point 8, dmax: 0.6549929, imax: 22, n: 30 computing farthest point 9, dmax: 0.6186762, imax: 1, n: 30 computing farthest point 10, dmax: 0.6152074, imax: 25, n: 30 Test Summary: | Pass Total Time farthest first traversal | 3 3 2.1s Test Summary: | Pass Total Time AdjacencyList | 15 15 1.5s LOG add_vertex! sp=1 ep=1 n=1 BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2026-02-19T17:18:24.676 LOG n.size quantiles:[0.0, 0.0, 0.0, 0.0, 0.0] LOG add_vertex! sp=2 ep=2 n=2 BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2026-02-19T17:18:26.393 LOG n.size quantiles:[1.0, 1.0, 1.0, 1.0, 1.0] LOG add_vertex! sp=295 ep=299 n=294 BeamSearch(bsize=2, Δ=0.8571428, maxvisits=120) 2026-02-19T17:18:40.352 LOG n.size quantiles:[4.0, 4.0, 4.0, 5.0, 5.0] (i, j, d) = (10, 741, -1.1920929f-7) (i, j, d, :parallel) = (10, 741, -1.1920929f-7, :parallel) [ Info: NOTE: the exact method will be faster on small datasets due to the preprocessing step of the approximation method [ Info: ("closestpair computation time", :approx => 23.195806980999997, :exact => 0.978574488) Test Summary: | Pass Total Time closestpair | 4 4 24.7s 7.454662 seconds (196.78 k allocations: 12.325 MiB, 25.15% compilation time) SEARCH Exhaustive 1: 0.005768 seconds SEARCH Exhaustive 2: 0.005572 seconds SEARCH Exhaustive 3: 0.006472 seconds typeof(seq) = ExhaustiveSearch{SqL2Distance, MatrixDatabase{Matrix{Float32}}} typeof(ectx) = GenericContext{KnnSorted} typeof(q) = SubArray{Float32, 1, Matrix{Float32}, Tuple{Base.Slice{Base.OneTo{Int64}}, Int64}, true} typeof(res) = KnnSorted{Vector{IdWeight}} [ Info: ===================== minrecall ============================== LOG add_vertex! sp=1 ep=1 n=1 BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2026-02-19T17:19:09.094 LOG n.size quantiles:[0.0, 0.0, 0.0, 0.0, 0.0] LOG add_vertex! sp=2 ep=2 n=2 BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2026-02-19T17:19:10.920 LOG n.size quantiles:[1.0, 1.0, 1.0, 1.0, 1.0] LOG add_vertex! sp=295 ep=299 n=294 BeamSearch(bsize=8, Δ=1.1, maxvisits=198) 2026-02-19T17:19:21.968 LOG n.size quantiles:[3.0, 5.0, 5.0, 7.0, 7.0] LOG add_vertex! sp=9395 ep=9399 n=9394 BeamSearch(bsize=4, Δ=1.21275, maxvisits=416) 2026-02-19T17:19:22.968 LOG n.size quantiles:[3.0, 5.0, 6.0, 6.0, 6.0] LOG add_vertex! sp=21625 ep=21629 n=21624 BeamSearch(bsize=6, Δ=1.3370568, maxvisits=442) 2026-02-19T17:19:23.968 LOG n.size quantiles:[4.0, 5.0, 5.0, 6.0, 8.0] LOG add_vertex! sp=32475 ep=32479 n=32474 BeamSearch(bsize=16, Δ=1.155, maxvisits=450) 2026-02-19T17:19:24.968 LOG n.size quantiles:[3.0, 6.0, 7.0, 7.0, 8.0] LOG add_vertex! sp=41425 ep=41429 n=41424 BeamSearch(bsize=11, Δ=1.21275, maxvisits=462) 2026-02-19T17:19:25.969 LOG n.size quantiles:[5.0, 6.0, 8.0, 8.0, 9.0] LOG add_vertex! sp=50920 ep=50924 n=50919 BeamSearch(bsize=11, Δ=1.21275, maxvisits=462) 2026-02-19T17:19:26.969 LOG n.size quantiles:[4.0, 4.0, 5.0, 6.0, 9.0] LOG add_vertex! sp=58230 ep=58234 n=58229 BeamSearch(bsize=4, Δ=1.1, maxvisits=498) 2026-02-19T17:19:27.969 LOG n.size quantiles:[3.0, 6.0, 7.0, 8.0, 9.0] LOG add_vertex! sp=67545 ep=67549 n=67544 BeamSearch(bsize=4, Δ=1.1, maxvisits=498) 2026-02-19T17:19:28.969 LOG n.size quantiles:[5.0, 6.0, 6.0, 7.0, 7.0] LOG add_vertex! sp=76325 ep=76329 n=76324 BeamSearch(bsize=4, Δ=1.1, maxvisits=498) 2026-02-19T17:19:29.970 LOG n.size quantiles:[6.0, 7.0, 7.0, 7.0, 11.0] LOG add_vertex! sp=84730 ep=84734 n=84729 BeamSearch(bsize=4, Δ=1.1, maxvisits=498) 2026-02-19T17:19:30.970 LOG n.size quantiles:[4.0, 6.0, 6.0, 7.0, 7.0] LOG add_vertex! sp=91645 ep=91649 n=91644 BeamSearch(bsize=4, Δ=1.1, maxvisits=430) 2026-02-19T17:19:31.971 LOG n.size quantiles:[5.0, 5.0, 6.0, 7.0, 7.0] LOG add_vertex! sp=99920 ep=99924 n=99919 BeamSearch(bsize=4, Δ=1.1, maxvisits=430) 2026-02-19T17:19:32.971 LOG n.size quantiles:[6.0, 6.0, 7.0, 7.0, 8.0] quantile(neighbors_length.(Ref(graph.adj), 1:length(graph)), 0:0.1:1.0) = [1.0, 6.0, 8.0, 9.0, 10.0, 11.0, 13.0, 15.0, 18.0, 23.0, 92.0] [ Info: minrecall: queries per second: 3089.614061199403, recall: 0.905625 graph.algo = Base.RefValue{BeamSearch}(BeamSearch(bsize=4, Δ=1.1851876, maxvisits=710)) quantile(neighbors_length.(Ref(graph.adj), 1:length(graph)), 0:0.1:1.0) = [1.0, 6.0, 8.0, 9.0, 10.0, 11.0, 13.0, 15.0, 18.0, 23.0, 92.0] [ Info: ===================== rebuild ============================== (graph.algo, length(B.queries), B.ksearch) = (Base.RefValue{BeamSearch}(BeamSearch(bsize=8, Δ=1.16, maxvisits=548)), 1000, 8) [ Info: rebuild: queries per second: 13731.532770536392, recall: 0.9065 graph.algo = Base.RefValue{BeamSearch}(BeamSearch(bsize=8, Δ=1.16, maxvisits=548)) quantile(neighbors_length.(Ref(graph.adj), 1:length(graph)), 0:0.1:1.0) = [2.0, 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0, 18.0, 19.0, 30.0] [ Info: ===================== matrixhints ============================== (graph.algo, length(B.queries), B.ksearch) = (Base.RefValue{BeamSearch}(BeamSearch(bsize=6, Δ=1.155, maxvisits=734)), 1000, 8) 0.614002 seconds (93.03 k allocations: 5.463 MiB, 85.54% compilation time) [ Info: matrixhints: queries per second: 11809.844497415534, recall: 0.901125 graph.algo = Base.RefValue{BeamSearch}(BeamSearch(bsize=6, Δ=1.155, maxvisits=734)) quantile(neighbors_length.(Ref(graph.adj), 1:length(graph)), 0:0.1:1.0) = [1.0, 6.0, 8.0, 9.0, 10.0, 11.0, 13.0, 15.0, 18.0, 23.0, 92.0] 3.033241 seconds (158.42 k allocations: 10.370 MiB, 57.22% compilation time) SEARCH Exhaustive 1: 0.002127 seconds SEARCH Exhaustive 2: 0.002210 seconds SEARCH Exhaustive 3: 0.002358 seconds typeof(seq) = ExhaustiveSearch{SqL2Distance, StrideMatrixDatabase{StrideArraysCore.StrideArray{Float32, 2, (1, 2), Tuple{Int64, Int64}, Tuple{Nothing, Nothing}, Tuple{Static.StaticInt{1}, Static.StaticInt{1}}, Matrix{Float32}}}} typeof(ectx) = GenericContext{KnnSorted} typeof(q) = StrideArraysCore.StrideArray{Float32, 1, (1,), Tuple{Int64}, Tuple{Nothing}, Tuple{Static.StaticInt{1}}, Matrix{Float32}} typeof(res) = KnnSorted{Vector{IdWeight}} [ Info: ===================== minrecall ============================== LOG add_vertex! sp=1 ep=1 n=1 BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2026-02-19T17:20:47.043 LOG n.size quantiles:[0.0, 0.0, 0.0, 0.0, 0.0] LOG add_vertex! sp=2 ep=2 n=2 BeamSearch(bsize=4, Δ=1.0, maxvisits=1000000) 2026-02-19T17:20:48.781 LOG n.size quantiles:[1.0, 1.0, 1.0, 1.0, 1.0] LOG add_vertex! sp=295 ep=299 n=294 BeamSearch(bsize=8, Δ=1.1, maxvisits=198) 2026-02-19T17:20:59.318 LOG n.size quantiles:[3.0, 5.0, 5.0, 7.0, 7.0] LOG add_vertex! sp=17030 ep=17034 n=17029 BeamSearch(bsize=6, Δ=1.3370568, maxvisits=442) 2026-02-19T17:21:00.318 LOG n.size quantiles:[6.0, 7.0, 7.0, 8.0, 9.0] LOG add_vertex! sp=28425 ep=28429 n=28424 BeamSearch(bsize=16, Δ=1.155, maxvisits=450) 2026-02-19T17:21:01.645 LOG n.size quantiles:[3.0, 6.0, 8.0, 8.0, 10.0] LOG add_vertex! sp=39520 ep=39524 n=39519 BeamSearch(bsize=11, Δ=1.21275, maxvisits=462) 2026-02-19T17:21:02.645 LOG n.size quantiles:[5.0, 6.0, 8.0, 8.0, 9.0] LOG add_vertex! sp=50335 ep=50339 n=50334 BeamSearch(bsize=11, Δ=1.21275, maxvisits=462) 2026-02-19T17:21:03.646 LOG n.size quantiles:[4.0, 6.0, 7.0, 7.0, 7.0] LOG add_vertex! sp=59865 ep=59869 n=59864 BeamSearch(bsize=4, Δ=1.1, maxvisits=498) 2026-02-19T17:21:04.646 LOG n.size quantiles:[6.0, 6.0, 7.0, 8.0, 8.0] LOG add_vertex! sp=69910 ep=69914 n=69909 BeamSearch(bsize=4, Δ=1.1, maxvisits=498) 2026-02-19T17:21:05.646 LOG n.size quantiles:[5.0, 6.0, 7.0, 8.0, 8.0] LOG add_vertex! sp=79475 ep=79479 n=79474 BeamSearch(bsize=4, Δ=1.1, maxvisits=498) 2026-02-19T17:21:06.646 LOG n.size quantiles:[3.0, 5.0, 6.0, 7.0, 10.0] LOG add_vertex! sp=87915 ep=87919 n=87914 BeamSearch(bsize=4, Δ=1.1, maxvisits=430) 2026-02-19T17:21:07.647 LOG n.size quantiles:[8.0, 8.0, 8.0, 9.0, 9.0] LOG add_vertex! sp=96755 ep=96759 n=96754 BeamSearch(bsize=4, Δ=1.1, maxvisits=430) 2026-02-19T17:21:08.647 LOG n.size quantiles:[4.0, 5.0, 6.0, 6.0, 6.0] quantile(neighbors_length.(Ref(graph.adj), 1:length(graph)), 0:0.1:1.0) = [1.0, 6.0, 8.0, 9.0, 10.0, 11.0, 13.0, 15.0, 18.0, 23.0, 92.0] [ Info: minrecall: queries per second: 2952.314764014499, recall: 0.905625 graph.algo = Base.RefValue{BeamSearch}(BeamSearch(bsize=4, Δ=1.1851876, maxvisits=710)) quantile(neighbors_length.(Ref(graph.adj), 1:length(graph)), 0:0.1:1.0) = [1.0, 6.0, 8.0, 9.0, 10.0, 11.0, 13.0, 15.0, 18.0, 23.0, 92.0] [ Info: ===================== rebuild ============================== (graph.algo, length(B.queries), B.ksearch) = (Base.RefValue{BeamSearch}(BeamSearch(bsize=8, Δ=1.16, maxvisits=548)), 1000, 8) [ Info: rebuild: queries per second: 15508.121828269232, recall: 0.9065 graph.algo = Base.RefValue{BeamSearch}(BeamSearch(bsize=8, Δ=1.16, maxvisits=548)) quantile(neighbors_length.(Ref(graph.adj), 1:length(graph)), 0:0.1:1.0) = [2.0, 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0, 18.0, 19.0, 30.0] [ Info: ===================== matrixhints ============================== (graph.algo, length(B.queries), B.ksearch) = (Base.RefValue{BeamSearch}(BeamSearch(bsize=6, Δ=1.155, maxvisits=734)), 1000, 8) 0.627144 seconds (94.11 k allocations: 5.615 MiB, 88.22% compilation time) [ Info: matrixhints: queries per second: 13815.605353475232, recall: 0.901125 graph.algo = Base.RefValue{BeamSearch}(BeamSearch(bsize=6, Δ=1.155, maxvisits=734)) quantile(neighbors_length.(Ref(graph.adj), 1:length(graph)), 0:0.1:1.0) = [1.0, 6.0, 8.0, 9.0, 10.0, 11.0, 13.0, 15.0, 18.0, 23.0, 92.0] Test Summary: | Pass Total Time vector indexing with SearchGraph | 18 18 3m05.9s Testing SimilaritySearch tests passed Testing completed after 705.52s PkgEval succeeded after 867.48s