Package evaluation to test SDPLRPlus on Julia 1.14.0-DEV.1918 (78a0dc1151*) started at 2026-03-20T02:06:07.252 ################################################################################ # Set-up # Installing PkgEval dependencies (TestEnv)... Activating project at `~/.julia/environments/v1.14` Set-up completed after 13.54s ################################################################################ # Installation # Installing SDPLRPlus... Resolving package versions... Updating `~/.julia/environments/v1.14/Project.toml` [9040bce9] + SDPLRPlus v0.2.0 Updating `~/.julia/environments/v1.14/Manifest.toml` [6e4b80f9] + BenchmarkTools v1.6.3 [523fee87] + CodecBzip2 v0.8.5 [944b1d66] + CodecZlib v0.7.8 [bbf7d656] + CommonSubexpressions v0.3.1 [34da2185] + Compat v4.18.1 [187b0558] + ConstructionBase v1.6.0 [a8cc5b0e] + Crayons v4.1.1 [9a962f9c] + DataAPI v1.16.0 [e2d170a0] + DataValueInterfaces v1.0.0 [163ba53b] + DiffResults v1.1.0 [b552c78f] + DiffRules v1.15.1 [ffbed154] + DocStringExtensions v0.9.5 [e2ba6199] + ExprTools v0.1.10 [9aa1b823] + FastClosures v0.3.2 [1a297f60] + FillArrays v1.16.0 [f6369f11] + ForwardDiff v1.3.2 [408c25d7] + GenericArpack v0.2.1 [92d709cd] + IrrationalConstants v0.2.6 [82899510] + IteratorInterfaceExtensions v1.0.0 [692b3bcd] + JLLWrappers v1.7.1 [682c06a0] + JSON v1.4.0 [4076af6c] + JuMP v1.30.0 ⌅ [0b1a1467] + KrylovKit v0.9.5 [b964fa9f] + LaTeXStrings v1.4.0 [5c8ed15e] + LinearOperators v2.13.0 [2ab3a3ac] + LogExpFunctions v0.3.29 [607ca3ad] + LowRankOpt v0.2.1 [d05aeea4] + LuxurySparse v0.8.1 [33e6dc65] + MKL v0.9.1 [0c723cd3] + MKLSparse v3.0.0 [1914dd2f] + MacroTools v0.5.16 [b8f27783] + MathOptInterface v1.49.0 [d8a4904e] + MutableArithmetics v1.6.7 [a4795742] + NLPModels v0.21.12 [792afdf1] + NLPModelsJuMP v0.13.5 [77ba4419] + NaNMath v1.1.3 [bac558e1] + OrderedCollections v1.8.1 [65ce6f38] + PackageExtensionCompat v1.0.2 [d96e819e] + Parameters v0.12.3 [69de0a69] + Parsers v2.8.3 [3a141323] + PolynomialRoots v1.0.0 [f27b6e38] + Polynomials v4.1.1 [aea7be01] + PrecompileTools v1.3.3 [21216c6a] + Preferences v1.5.2 [08abe8d2] + PrettyTables v3.2.3 [189a3867] + Reexport v1.2.2 [9040bce9] + SDPLRPlus v0.2.0 [efcf1570] + Setfield v1.1.2 [ff4d7338] + SolverCore v0.3.10 [276daf66] + SpecialFunctions v2.7.1 [90137ffa] + StaticArrays v1.9.18 [1e83bf80] + StaticArraysCore v1.4.4 [10745b16] + Statistics v1.11.1 [892a3eda] + StringManipulation v0.4.4 [ec057cc2] + StructUtils v2.7.1 [3783bdb8] + TableTraits v1.0.1 [bd369af6] + Tables v1.12.1 [a759f4b9] + TimerOutputs v0.5.29 [3bb67fe8] + TranscodingStreams v0.11.3 [3a884ed6] + UnPack v1.0.2 [c4a57d5a] + UnsafeArrays v1.0.8 [409d34a3] + VectorInterface v0.5.0 [6e34b625] + Bzip2_jll v1.0.9+0 [1d5cc7b8] + IntelOpenMP_jll v2025.2.0+0 [856f044c] + MKL_jll v2025.2.0+0 [efe28fd5] + OpenSpecFun_jll v0.5.6+0 [1317d2d5] + oneTBB_jll v2022.0.0+1 [0dad84c5] + ArgTools v1.1.2 [56f22d72] + Artifacts v1.11.0 [2a0f44e3] + Base64 v1.11.0 [ade2ca70] + Dates 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 v1.13.0 [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 [9abbd945] + Profile v1.11.0 [3fa0cd96] + REPL 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 v8.19.0+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 [05823500] + OpenLibm_jll v0.8.7+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 v1.3.2+0 [3161d3a3] + Zstd_jll v1.5.7+1 [8e850b90] + libblastrampoline_jll v5.15.0+0 [8e850ede] + nghttp2_jll v1.68.0+1 [3f19e933] + p7zip_jll v17.8.0+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 5.5s ################################################################################ # Precompilation # Precompiling PkgEval dependencies... Precompiling package dependencies... Precompiling packages... 25698.0 ms ✓ SDPLRPlus 1 dependency successfully precompiled in 28 seconds. 127 already precompiled. Precompilation completed after 44.95s ################################################################################ # Testing # Testing SDPLRPlus Status `/tmp/jl_AJtWHN/Project.toml` [6a86dc24] FiniteDiff v2.29.0 [d05aeea4] LuxurySparse v0.8.1 [9040bce9] SDPLRPlus v0.2.0 [37e2e46d] LinearAlgebra v1.13.0 [9a3f8284] Random v1.11.0 [2f01184e] SparseArrays v1.13.0 [8dfed614] Test v1.11.0 Status `/tmp/jl_AJtWHN/Manifest.toml` [79e6a3ab] Adapt v4.5.0 [4fba245c] ArrayInterface v7.23.0 [6e4b80f9] BenchmarkTools v1.6.3 [523fee87] CodecBzip2 v0.8.5 [944b1d66] CodecZlib v0.7.8 [bbf7d656] CommonSubexpressions v0.3.1 [34da2185] Compat v4.18.1 [187b0558] ConstructionBase v1.6.0 [a8cc5b0e] Crayons v4.1.1 [9a962f9c] DataAPI v1.16.0 [e2d170a0] DataValueInterfaces v1.0.0 [163ba53b] DiffResults v1.1.0 [b552c78f] DiffRules v1.15.1 [ffbed154] DocStringExtensions v0.9.5 [e2ba6199] ExprTools v0.1.10 [9aa1b823] FastClosures v0.3.2 [1a297f60] FillArrays v1.16.0 [6a86dc24] FiniteDiff v2.29.0 [f6369f11] ForwardDiff v1.3.2 [408c25d7] GenericArpack v0.2.1 [92d709cd] IrrationalConstants v0.2.6 [82899510] IteratorInterfaceExtensions v1.0.0 [692b3bcd] JLLWrappers v1.7.1 [682c06a0] JSON v1.4.0 [4076af6c] JuMP v1.30.0 ⌅ [0b1a1467] KrylovKit v0.9.5 [b964fa9f] LaTeXStrings v1.4.0 [5c8ed15e] LinearOperators v2.13.0 [2ab3a3ac] LogExpFunctions v0.3.29 [607ca3ad] LowRankOpt v0.2.1 [d05aeea4] LuxurySparse v0.8.1 [33e6dc65] MKL v0.9.1 [0c723cd3] MKLSparse v3.0.0 [1914dd2f] MacroTools v0.5.16 [b8f27783] MathOptInterface v1.49.0 [d8a4904e] MutableArithmetics v1.6.7 [a4795742] NLPModels v0.21.12 [792afdf1] NLPModelsJuMP v0.13.5 [77ba4419] NaNMath v1.1.3 [bac558e1] OrderedCollections v1.8.1 [65ce6f38] PackageExtensionCompat v1.0.2 [d96e819e] Parameters v0.12.3 [69de0a69] Parsers v2.8.3 [3a141323] PolynomialRoots v1.0.0 [f27b6e38] Polynomials v4.1.1 [aea7be01] PrecompileTools v1.3.3 [21216c6a] Preferences v1.5.2 [08abe8d2] PrettyTables v3.2.3 [189a3867] Reexport v1.2.2 [ae029012] Requires v1.3.1 [9040bce9] SDPLRPlus v0.2.0 [efcf1570] Setfield v1.1.2 [ff4d7338] SolverCore v0.3.10 [276daf66] SpecialFunctions v2.7.1 [90137ffa] StaticArrays v1.9.18 [1e83bf80] StaticArraysCore v1.4.4 [10745b16] Statistics v1.11.1 [892a3eda] StringManipulation v0.4.4 [ec057cc2] StructUtils v2.7.1 [3783bdb8] TableTraits v1.0.1 [bd369af6] Tables v1.12.1 [a759f4b9] TimerOutputs v0.5.29 [3bb67fe8] TranscodingStreams v0.11.3 [3a884ed6] UnPack v1.0.2 [c4a57d5a] UnsafeArrays v1.0.8 [409d34a3] VectorInterface v0.5.0 [6e34b625] Bzip2_jll v1.0.9+0 [1d5cc7b8] IntelOpenMP_jll v2025.2.0+0 [856f044c] MKL_jll v2025.2.0+0 [efe28fd5] OpenSpecFun_jll v0.5.6+0 [1317d2d5] oneTBB_jll v2022.0.0+1 [0dad84c5] ArgTools v1.1.2 [56f22d72] Artifacts v1.11.0 [2a0f44e3] Base64 v1.11.0 [ade2ca70] Dates 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 v1.13.0 [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 [9abbd945] Profile v1.11.0 [3fa0cd96] REPL 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 v8.19.0+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 [05823500] OpenLibm_jll v0.8.7+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 v1.3.2+0 [3161d3a3] Zstd_jll v1.5.7+1 [8e850b90] libblastrampoline_jll v5.15.0+0 [8e850ede] nghttp2_jll v1.68.0+1 [3f19e933] p7zip_jll v17.8.0+0 Info Packages marked with ⌅ have new versions available but compatibility constraints restrict them from upgrading. Testing Running tests... Test Summary: | Pass Total Time SymLowRankMatrix tests | 200 200 7.3s [ Info: Max Cut SDP is formed. ========================================================================================================================= SDPLRPlus.jl: a julia implementation of SDPLR with objval gap bound ========================================================================================================================= [ Info: Finish classifying constraints. ┌─────────┬───┬───────┬─────────┬───────────┬───────────┬──────────┬──────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼───┼───────┼─────────┼───────────┼───────────┼──────────┼──────────── │ │ 1 │ 1 │ 1 │ -1.12E+00 │ -1.25E+00 │ 2.00E+00 │ 5.00E-01 ⋯ └─────────┴───┴───────┴─────────┴───────────┴───────────┴──────────┴──────────── 5 columns omitted var.obj[] = -1.249872279165569 max_dual_value = -1.002579336228003 duality_gap = -0.24665673229208404 ┌─────────┬───┬───────┬─────────┬───────────┬───────────┬──────────┬──────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼───┼───────┼─────────┼───────────┼───────────┼──────────┼──────────── │ │ 2 │ 1 │ 2 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 2.50E-01 ⋯ └─────────┴───┴───────┴─────────┴───────────┴───────────┴──────────┴──────────── 5 columns omitted var.obj[] = -1.000781561051126 max_dual_value = -1.002579336228003 duality_gap = 0.0017963712031114649 ┌─────────┬───┬───────┬─────────┬───────────┬───────────┬──────────┬──────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼───┼───────┼─────────┼───────────┼───────────┼──────────┼──────────── │ │ 3 │ 1 │ 3 │ -1.00E+00 │ -9.99E-01 │ 2.00E+00 │ 1.25E-01 ⋯ └─────────┴───┴───────┴─────────┴───────────┴───────────┴──────────┴──────────── 5 columns omitted var.obj[] = -0.9990603747661084 max_dual_value = -0.9995164477136981 duality_gap = 0.0004565018882831975 ┌─────────┬───┬───────┬─────────┬───────────┬───────────┬──────────┬──────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼───┼───────┼─────────┼───────────┼───────────┼──────────┼──────────── │ │ 4 │ 0 │ 3 │ -1.00E+00 │ -9.99E-01 │ 2.00E+00 │ 6.25E-02 ⋯ └─────────┴───┴───────┴─────────┴───────────┴───────────┴──────────┴──────────── 5 columns omitted var.obj[] = -0.9990603747661084 max_dual_value = -0.9957651231760783 duality_gap = -0.003309265923594102 ┌─────────┬───┬───────┬─────────┬───────────┬───────────┬──────────┬──────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼───┼───────┼─────────┼───────────┼───────────┼──────────┼──────────── │ │ 5 │ 1 │ 4 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 3.12E-02 ⋯ └─────────┴───┴───────┴─────────┴───────────┴───────────┴──────────┴──────────── 5 columns omitted var.obj[] = -1.0008551149417282 max_dual_value = -0.9957651231760783 duality_gap = -0.005111638926873509 ┌─────────┬───┬───────┬─────────┬───────────┬───────────┬──────────┬──────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼───┼───────┼─────────┼───────────┼───────────┼──────────┼──────────── │ │ 6 │ 1 │ 5 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 1.56E-02 ⋯ └─────────┴───┴───────┴─────────┴───────────┴───────────┴──────────┴──────────── 5 columns omitted var.obj[] = -1.0002672876265983 max_dual_value = -0.9957651231760783 duality_gap = -0.0045213116484336645 ┌─────────┬───┬───────┬─────────┬───────────┬───────────┬──────────┬──────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼───┼───────┼─────────┼───────────┼───────────┼──────────┼──────────── │ │ 7 │ 0 │ 5 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 7.81E-03 ⋯ └─────────┴───┴───────┴─────────┴───────────┴───────────┴──────────┴──────────── 5 columns omitted var.obj[] = -1.0002672876265981 max_dual_value = -0.9957651231760783 duality_gap = -0.004521311648433441 ┌─────────┬───┬───────┬─────────┬───────────┬───────────┬──────────┬──────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼───┼───────┼─────────┼───────────┼───────────┼──────────┼──────────── │ │ 8 │ 1 │ 6 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 3.91E-03 ⋯ └─────────┴───┴───────┴─────────┴───────────┴───────────┴──────────┴──────────── 5 columns omitted var.obj[] = -0.9996815973595596 max_dual_value = -0.9957651231760783 duality_gap = -0.003933130506709613 ┌─────────┬───┬───────┬─────────┬───────────┬───────────┬──────────┬──────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼───┼───────┼─────────┼───────────┼───────────┼──────────┼──────────── │ │ 9 │ 1 │ 7 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 1.95E-03 ⋯ └─────────┴───┴───────┴─────────┴───────────┴───────────┴──────────┴──────────── 5 columns omitted var.obj[] = -0.9999785409072924 max_dual_value = -0.9957651231760783 duality_gap = -0.004231336921878754 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 10 │ 0 │ 7 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 9.77E-04 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -0.9999785409072923 max_dual_value = -0.9957651231760783 duality_gap = -0.004231336921878643 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 11 │ 1 │ 8 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 4.88E-04 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -1.0000255608084307 max_dual_value = -0.9957651231760783 duality_gap = -0.004278556793356416 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 12 │ 1 │ 9 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 2.44E-04 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -1.0000055048582488 max_dual_value = -0.9957651231760783 duality_gap = -0.004258415547479093 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 13 │ 0 │ 9 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 1.22E-04 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -1.0000055048582486 max_dual_value = -0.9957651231760783 duality_gap = -0.00425841554747887 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 14 │ 1 │ 10 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 6.10E-05 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -0.9999926178254189 max_dual_value = -0.9957651231760783 duality_gap = -0.004245473707551257 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 15 │ 1 │ 11 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 3.05E-05 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -0.9999999901198096 max_dual_value = -0.9957651231760783 duality_gap = -0.004252877355478907 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 16 │ 0 │ 11 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 1.53E-05 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -0.9999999901198096 max_dual_value = -0.9957651231760783 duality_gap = -0.004252877355478907 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 17 │ 0 │ 11 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 7.63E-06 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -0.9999999901198096 max_dual_value = -0.9957651231760783 duality_gap = -0.004252877355478907 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 18 │ 0 │ 11 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 3.81E-06 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -0.9999999901198096 max_dual_value = -0.9957651231760783 duality_gap = -0.004252877355478907 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 19 │ 1 │ 12 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 1.91E-06 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -1.000000033430537 max_dual_value = -0.9957651231760783 duality_gap = -0.004252920850401997 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 20 │ 1 │ 13 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 9.54E-07 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -1.0000000082662706 max_dual_value = -0.9957651231760783 duality_gap = -0.004252895579114761 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 21 │ 0 │ 13 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 4.77E-07 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -1.0000000082662706 max_dual_value = -0.9957651231760783 duality_gap = -0.004252895579114761 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 22 │ 1 │ 14 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 2.38E-07 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -0.9999999903871383 max_dual_value = -0.9957651231760783 duality_gap = -0.0042528776239445405 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 23 │ 1 │ 15 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 1.19E-07 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -0.9999999975668049 max_dual_value = -0.9957651231760783 duality_gap = -0.0042528848341454924 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 23 │ -1 │ 15 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 1.19E-07 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted ========================================================================================================================= End of SDPLRPlus.jl ========================================================================================================================= [ Info: Max Cut SDP is formed. ========================================================================================================================= SDPLRPlus.jl: a julia implementation of SDPLR with objval gap bound ========================================================================================================================= [ Info: Finish classifying constraints. ┌─────────┬───┬───────┬─────────┬───────────┬───────────┬──────────┬──────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼───┼───────┼─────────┼───────────┼───────────┼──────────┼──────────── │ │ 1 │ 2 │ 2 │ -1.02E+00 │ -1.05E+00 │ 1.00E+01 │ 1.00E-01 ⋯ └─────────┴───┴───────┴─────────┴───────────┴───────────┴──────────┴──────────── 5 columns omitted var.obj[] = -1.0504519449063907 max_dual_value = -1.0090388993557866 duality_gap = -0.04104207040684353 ┌─────────┬───┬───────┬─────────┬───────────┬───────────┬──────────┬──────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼───┼───────┼─────────┼───────────┼───────────┼──────────┼──────────── │ │ 2 │ 1 │ 3 │ -1.00E+00 │ -1.00E+00 │ 1.00E+01 │ 1.00E-02 ⋯ └─────────┴───┴───────┴─────────┴───────────┴───────────┴──────────┴──────────── 5 columns omitted var.obj[] = -0.9995480557160983 max_dual_value = -1.0000000150927624 duality_gap = 0.0004521637294770154 ┌─────────┬───┬───────┬─────────┬───────────┬───────────┬──────────┬──────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼───┼───────┼─────────┼───────────┼───────────┼──────────┼──────────── │ │ 3 │ 1 │ 4 │ -1.00E+00 │ -1.00E+00 │ 1.00E+01 │ 1.00E-03 ⋯ └─────────┴───┴───────┴─────────┴───────────┴───────────┴──────────┴──────────── 5 columns omitted var.obj[] = -0.9999999815810563 max_dual_value = -0.9999996467207507 duality_gap = -3.3486042389450287e-7 ┌─────────┬───┬───────┬─────────┬───────────┬───────────┬──────────┬──────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼───┼───────┼─────────┼───────────┼───────────┼──────────┼──────────── │ │ 4 │ 0 │ 4 │ -1.00E+00 │ -1.00E+00 │ 1.00E+01 │ 1.00E-04 ⋯ └─────────┴───┴───────┴─────────┴───────────┴───────────┴──────────┴──────────── 5 columns omitted var.obj[] = -0.9999999815810565 max_dual_value = -0.9999992783487422 duality_gap = -7.032328217585697e-7 ┌─────────┬───┬───────┬─────────┬───────────┬───────────┬──────────┬──────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼───┼───────┼─────────┼───────────┼───────────┼──────────┼──────────── │ │ 5 │ 1 │ 5 │ -1.00E+00 │ -1.00E+00 │ 1.00E+01 │ 1.00E-05 ⋯ └─────────┴───┴───────┴─────────┴───────────┴───────────┴──────────┴──────────── 5 columns omitted var.obj[] = -1.0000000347518447 max_dual_value = -0.9999992783487422 duality_gap = -7.564036483461245e-7 ┌─────────┬───┬───────┬─────────┬───────────┬───────────┬──────────┬──────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼───┼───────┼─────────┼───────────┼───────────┼──────────┼──────────── │ │ 6 │ 1 │ 6 │ -1.00E+00 │ -1.00E+00 │ 1.00E+01 │ 1.00E-06 ⋯ └─────────┴───┴───────┴─────────┴───────────┴───────────┴──────────┴──────────── 5 columns omitted var.obj[] = -1.0000000021431923 max_dual_value = -0.9999992783487422 duality_gap = -7.237949723691116e-7 ┌─────────┬───┬───────┬─────────┬───────────┬───────────┬──────────┬──────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼───┼───────┼─────────┼───────────┼───────────┼──────────┼──────────── │ │ 7 │ 1 │ 7 │ -1.00E+00 │ -1.00E+00 │ 1.00E+01 │ 1.00E-07 ⋯ └─────────┴───┴───────┴─────────┴───────────┴───────────┴──────────┴──────────── 5 columns omitted var.obj[] = -0.9999999992585997 max_dual_value = -0.9999992783487422 duality_gap = -7.209103777226289e-7 ┌─────────┬───┬───────┬─────────┬───────────┬───────────┬──────────┬──────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼───┼───────┼─────────┼───────────┼───────────┼──────────┼──────────── │ │ 7 │ -1 │ 7 │ -1.00E+00 │ -1.00E+00 │ 1.00E+01 │ 1.00E-07 ⋯ └─────────┴───┴───────┴─────────┴───────────┴───────────┴──────────┴──────────── 5 columns omitted ========================================================================================================================= End of SDPLRPlus.jl ========================================================================================================================= [ Info: Max Cut SDP is formed. ========================================================================================================================= SDPLRPlus.jl: a julia implementation of SDPLR with objval gap bound ========================================================================================================================= [ Info: Finish classifying constraints. ┌─────────┬───┬───────┬─────────┬───────────┬───────────┬──────────┬──────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼───┼───────┼─────────┼───────────┼───────────┼──────────┼──────────── │ │ 1 │ 2 │ 2 │ -1.12E+00 │ -1.25E+00 │ 2.00E+00 │ 5.00E-01 ⋯ └─────────┴───┴───────┴─────────┴───────────┴───────────┴──────────┴──────────── 5 columns omitted var.obj[] = -1.2461737710553316 max_dual_value = -0.9899607288368679 duality_gap = -0.25881131923232487 ┌─────────┬───┬───────┬─────────┬───────────┬───────────┬──────────┬──────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼───┼───────┼─────────┼───────────┼───────────┼──────────┼──────────── │ │ 2 │ 1 │ 3 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 2.50E-01 ⋯ └─────────┴───┴───────┴─────────┴───────────┴───────────┴──────────┴──────────── 5 columns omitted var.obj[] = -1.00385481081303 max_dual_value = -0.9899607288368679 duality_gap = -0.014034982976028445 ┌─────────┬───┬───────┬─────────┬───────────┬───────────┬──────────┬──────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼───┼───────┼─────────┼───────────┼───────────┼──────────┼──────────── │ │ 3 │ 0 │ 3 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 1.25E-01 ⋯ └─────────┴───┴───────┴─────────┴───────────┴───────────┴──────────┴──────────── 5 columns omitted var.obj[] = -1.00385481081303 max_dual_value = -0.9899607288368679 duality_gap = -0.014034982976028445 ┌─────────┬───┬───────┬─────────┬───────────┬───────────┬──────────┬──────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼───┼───────┼─────────┼───────────┼───────────┼──────────┼──────────── │ │ 4 │ 1 │ 4 │ -1.00E+00 │ -9.97E-01 │ 2.00E+00 │ 6.25E-02 ⋯ └─────────┴───┴───────┴─────────┴───────────┴───────────┴──────────┴──────────── 5 columns omitted var.obj[] = -0.9966365054670552 max_dual_value = -0.9899607288368679 duality_gap = -0.006743476216506903 ┌─────────┬───┬───────┬─────────┬───────────┬───────────┬──────────┬──────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼───┼───────┼─────────┼───────────┼───────────┼──────────┼──────────── │ │ 5 │ 1 │ 5 │ -1.00E+00 │ -9.99E-01 │ 2.00E+00 │ 3.12E-02 ⋯ └─────────┴───┴───────┴─────────┴───────────┴───────────┴──────────┴──────────── 5 columns omitted var.obj[] = -0.9992089809513377 max_dual_value = -0.9899607288368679 duality_gap = -0.009342039381032624 ┌─────────┬───┬───────┬─────────┬───────────┬───────────┬──────────┬──────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼───┼───────┼─────────┼───────────┼───────────┼──────────┼──────────── │ │ 6 │ 0 │ 5 │ -1.00E+00 │ -9.99E-01 │ 2.00E+00 │ 1.56E-02 ⋯ └─────────┴───┴───────┴─────────┴───────────┴───────────┴──────────┴──────────── 5 columns omitted var.obj[] = -0.9992089809513378 max_dual_value = -0.9899607288368679 duality_gap = -0.009342039381032737 ┌─────────┬───┬───────┬─────────┬───────────┬───────────┬──────────┬──────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼───┼───────┼─────────┼───────────┼───────────┼──────────┼──────────── │ │ 7 │ 1 │ 6 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 7.81E-03 ⋯ └─────────┴───┴───────┴─────────┴───────────┴───────────┴──────────┴──────────── 5 columns omitted var.obj[] = -1.001044399777462 max_dual_value = -0.9899607288368679 duality_gap = -0.011196071336705101 ┌─────────┬───┬───────┬─────────┬───────────┬───────────┬──────────┬──────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼───┼───────┼─────────┼───────────┼───────────┼──────────┼──────────── │ │ 8 │ 1 │ 7 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 3.91E-03 ⋯ └─────────┴───┴───────┴─────────┴───────────┴───────────┴──────────┴──────────── 5 columns omitted var.obj[] = -1.000004219920868 max_dual_value = -0.9899607288368679 duality_gap = -0.010145342932744947 ┌─────────┬───┬───────┬─────────┬───────────┬───────────┬──────────┬──────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼───┼───────┼─────────┼───────────┼───────────┼──────────┼──────────── │ │ 9 │ 0 │ 7 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 1.95E-03 ⋯ └─────────┴───┴───────┴─────────┴───────────┴───────────┴──────────┴──────────── 5 columns omitted var.obj[] = -1.0000042199208679 max_dual_value = -0.9899607288368679 duality_gap = -0.010145342932744723 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 10 │ 0 │ 7 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 9.77E-04 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -1.0000042199208679 max_dual_value = -0.9899607288368679 duality_gap = -0.010145342932744723 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 11 │ 1 │ 8 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 4.88E-04 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -0.9999903073468372 max_dual_value = -0.9899607288368679 duality_gap = -0.010131289270184845 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 12 │ 1 │ 9 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 2.44E-04 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -0.9999974719447573 max_dual_value = -0.9899607288368679 duality_gap = -0.010138526524867127 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 13 │ 0 │ 9 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 1.22E-04 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -0.9999974719447573 max_dual_value = -0.9899607288368679 duality_gap = -0.010138526524867127 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 14 │ 1 │ 10 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 6.10E-05 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -1.0000029205420171 max_dual_value = -0.9899607288368679 duality_gap = -0.010144030376788828 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 15 │ 1 │ 11 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 3.05E-05 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -1.000000683144906 max_dual_value = -0.9899607288368679 duality_gap = -0.010141770290054107 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 16 │ 0 │ 11 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 1.53E-05 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -1.000000683144906 max_dual_value = -0.9899607288368679 duality_gap = -0.010141770290054107 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 17 │ 1 │ 12 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 7.63E-06 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -0.9999991121405518 max_dual_value = -0.9899607288368679 duality_gap = -0.010140183354018768 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 18 │ 1 │ 13 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 3.81E-06 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -0.9999999981598191 max_dual_value = -0.9899607288368679 duality_gap = -0.010141078358478519 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 18 │ -1 │ 13 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 3.81E-06 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted ========================================================================================================================= End of SDPLRPlus.jl ========================================================================================================================= Test Summary: | Pass Total Time Max Cut | 3 3 1m45.8s [ Info: Minimum Bisection SDP is formed. ========================================================================================================================= SDPLRPlus.jl: a julia implementation of SDPLR with objval gap bound ========================================================================================================================= [ Info: Finish classifying constraints. ┌─────────┬───┬───────┬─────────┬──────────┬──────────┬──────────┬──────────┬─── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ │ ⋯ ├─────────┼───┼───────┼─────────┼──────────┼──────────┼──────────┼──────────┼─── │ │ 1 │ 1 │ 1 │ 8.75E-01 │ 7.50E-01 │ 2.00E+00 │ 5.00E-01 │ ⋯ └─────────┴───┴───────┴─────────┴──────────┴──────────┴──────────┴──────────┴─── 5 columns omitted var.obj[] = 0.7499017389328628 max_dual_value = 0.9748869826185544 duality_gap = -0.30001963191318065 ┌─────────┬───┬───────┬─────────┬──────────┬──────────┬──────────┬──────────┬─── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ │ ⋯ ├─────────┼───┼───────┼─────────┼──────────┼──────────┼──────────┼──────────┼─── │ │ 2 │ 1 │ 2 │ 1.00E+00 │ 1.00E+00 │ 2.00E+00 │ 2.50E-01 │ ⋯ └─────────┴───┴───────┴─────────┴──────────┴──────────┴──────────┴──────────┴─── 5 columns omitted var.obj[] = 1.0005419503704749 max_dual_value = 0.9748869826185544 duality_gap = 0.02631583784513256 ┌─────────┬───┬───────┬─────────┬──────────┬──────────┬──────────┬──────────┬─── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ │ ⋯ ├─────────┼───┼───────┼─────────┼──────────┼──────────┼──────────┼──────────┼─── │ │ 3 │ 0 │ 2 │ 1.00E+00 │ 1.00E+00 │ 2.00E+00 │ 1.25E-01 │ ⋯ └─────────┴───┴───────┴─────────┴──────────┴──────────┴──────────┴──────────┴─── 5 columns omitted var.obj[] = 1.0005419503704749 max_dual_value = 0.9748869826185544 duality_gap = 0.02631583784513256 ┌─────────┬───┬───────┬─────────┬──────────┬──────────┬──────────┬──────────┬─── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ │ ⋯ ├─────────┼───┼───────┼─────────┼──────────┼──────────┼──────────┼──────────┼─── │ │ 4 │ 1 │ 3 │ 1.00E+00 │ 9.99E-01 │ 2.00E+00 │ 6.25E-02 │ ⋯ └─────────┴───┴───────┴─────────┴──────────┴──────────┴──────────┴──────────┴─── 5 columns omitted var.obj[] = 0.9986271802710288 max_dual_value = 0.9847623624015258 duality_gap = 0.014079353962808922 ┌─────────┬───┬───────┬─────────┬──────────┬──────────┬──────────┬──────────┬─── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ │ ⋯ ├─────────┼───┼───────┼─────────┼──────────┼──────────┼──────────┼──────────┼─── │ │ 5 │ 1 │ 4 │ 1.00E+00 │ 1.00E+00 │ 2.00E+00 │ 3.12E-02 │ ⋯ └─────────┴───┴───────┴─────────┴──────────┴──────────┴──────────┴──────────┴─── 5 columns omitted var.obj[] = 1.0004802641780588 max_dual_value = 0.9847623624015258 duality_gap = 0.015961111407834436 ┌─────────┬───┬───────┬─────────┬──────────┬──────────┬──────────┬──────────┬─── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ │ ⋯ ├─────────┼───┼───────┼─────────┼──────────┼──────────┼──────────┼──────────┼─── │ │ 6 │ 0 │ 4 │ 1.00E+00 │ 1.00E+00 │ 2.00E+00 │ 1.56E-02 │ ⋯ └─────────┴───┴───────┴─────────┴──────────┴──────────┴──────────┴──────────┴─── 5 columns omitted var.obj[] = 1.000480264178059 max_dual_value = 0.9847623624015258 duality_gap = 0.015961111407834662 ┌─────────┬───┬───────┬─────────┬──────────┬──────────┬──────────┬──────────┬─── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ │ ⋯ ├─────────┼───┼───────┼─────────┼──────────┼──────────┼──────────┼──────────┼─── │ │ 7 │ 1 │ 5 │ 1.00E+00 │ 9.99E-01 │ 2.00E+00 │ 7.81E-03 │ ⋯ └─────────┴───┴───────┴─────────┴──────────┴──────────┴──────────┴──────────┴─── 5 columns omitted var.obj[] = 0.9992837456694187 max_dual_value = 0.9847623624015258 duality_gap = 0.014746078670675213 ┌─────────┬───┬───────┬─────────┬──────────┬──────────┬──────────┬──────────┬─── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ │ ⋯ ├─────────┼───┼───────┼─────────┼──────────┼──────────┼──────────┼──────────┼─── │ │ 8 │ 1 │ 6 │ 1.00E+00 │ 1.00E+00 │ 2.00E+00 │ 3.91E-03 │ ⋯ └─────────┴───┴───────┴─────────┴──────────┴──────────┴──────────┴──────────┴─── 5 columns omitted var.obj[] = 1.0000627272035851 max_dual_value = 0.9847623624015258 duality_gap = 0.015537113710100109 ┌─────────┬───┬───────┬─────────┬──────────┬──────────┬──────────┬──────────┬─── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ │ ⋯ ├─────────┼───┼───────┼─────────┼──────────┼──────────┼──────────┼──────────┼─── │ │ 9 │ 0 │ 6 │ 1.00E+00 │ 1.00E+00 │ 2.00E+00 │ 1.95E-03 │ ⋯ └─────────┴───┴───────┴─────────┴──────────┴──────────┴──────────┴──────────┴─── 5 columns omitted var.obj[] = 1.0000627272035851 max_dual_value = 0.9847623624015258 duality_gap = 0.015537113710100109 ┌─────────┬────┬───────┬─────────┬──────────┬──────────┬──────────┬──────────┬── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ │ ⋯ ├─────────┼────┼───────┼─────────┼──────────┼──────────┼──────────┼──────────┼── │ │ 10 │ 1 │ 7 │ 1.00E+00 │ 1.00E+00 │ 2.00E+00 │ 9.77E-04 │ ⋯ └─────────┴────┴───────┴─────────┴──────────┴──────────┴──────────┴──────────┴── 5 columns omitted var.obj[] = 0.9999118589958723 max_dual_value = 0.9847623624015258 duality_gap = 0.0153839110558629 ┌─────────┬────┬───────┬─────────┬──────────┬──────────┬──────────┬──────────┬── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ │ ⋯ ├─────────┼────┼───────┼─────────┼──────────┼──────────┼──────────┼──────────┼── │ │ 11 │ 1 │ 8 │ 1.00E+00 │ 1.00E+00 │ 2.00E+00 │ 4.88E-04 │ ⋯ └─────────┴────┴───────┴─────────┴──────────┴──────────┴──────────┴──────────┴── 5 columns omitted var.obj[] = 1.000017537526704 max_dual_value = 0.9847623624015258 duality_gap = 0.015491224794554068 ┌─────────┬────┬───────┬─────────┬──────────┬──────────┬──────────┬──────────┬── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ │ ⋯ ├─────────┼────┼───────┼─────────┼──────────┼──────────┼──────────┼──────────┼── │ │ 12 │ 1 │ 9 │ 1.00E+00 │ 1.00E+00 │ 2.00E+00 │ 2.44E-04 │ ⋯ └─────────┴────┴───────┴─────────┴──────────┴──────────┴──────────┴──────────┴── 5 columns omitted var.obj[] = 0.9999928670342884 max_dual_value = 0.9847623624015258 duality_gap = 0.01546617256534879 ┌─────────┬────┬───────┬─────────┬──────────┬──────────┬──────────┬──────────┬── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ │ ⋯ ├─────────┼────┼───────┼─────────┼──────────┼──────────┼──────────┼──────────┼── │ │ 13 │ 0 │ 9 │ 1.00E+00 │ 1.00E+00 │ 2.00E+00 │ 1.22E-04 │ ⋯ └─────────┴────┴───────┴─────────┴──────────┴──────────┴──────────┴──────────┴── 5 columns omitted var.obj[] = 0.9999928670342884 max_dual_value = 0.9847623624015258 duality_gap = 0.01546617256534879 [ Info: rank doubled, newrank is 2. ┌─────────┬────┬───────┬─────────┬──────────┬──────────┬──────────┬──────────┬── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ │ ⋯ ├─────────┼────┼───────┼─────────┼──────────┼──────────┼──────────┼──────────┼── │ │ 14 │ 4 │ 13 │ 8.65E-01 │ 7.12E-01 │ 2.00E+00 │ 5.00E-01 │ ⋯ └─────────┴────┴───────┴─────────┴──────────┴──────────┴──────────┴──────────┴── 5 columns omitted var.obj[] = 0.7115499978867459 max_dual_value = 0.9577012824789133 duality_gap = -0.34593673715581424 ┌─────────┬────┬───────┬─────────┬──────────┬──────────┬──────────┬──────────┬── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ │ ⋯ ├─────────┼────┼───────┼─────────┼──────────┼──────────┼──────────┼──────────┼── │ │ 15 │ 5 │ 18 │ 1.00E+00 │ 9.91E-01 │ 2.00E+00 │ 2.50E-01 │ ⋯ └─────────┴────┴───────┴─────────┴──────────┴──────────┴──────────┴──────────┴── 5 columns omitted var.obj[] = 0.9913912867097129 max_dual_value = 0.9919709322219177 duality_gap = -0.0005846788447461116 ┌─────────┬────┬───────┬─────────┬──────────┬──────────┬──────────┬──────────┬── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ │ ⋯ ├─────────┼────┼───────┼─────────┼──────────┼──────────┼──────────┼──────────┼── │ │ 16 │ 0 │ 18 │ 1.00E+00 │ 9.91E-01 │ 2.00E+00 │ 1.25E-01 │ ⋯ └─────────┴────┴───────┴─────────┴──────────┴──────────┴──────────┴──────────┴── 5 columns omitted var.obj[] = 0.9913912867097129 max_dual_value = 1.026240581964922 duality_gap = -0.03515190795237777 ┌─────────┬────┬───────┬─────────┬──────────┬──────────┬──────────┬──────────┬── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ │ ⋯ ├─────────┼────┼───────┼─────────┼──────────┼──────────┼──────────┼──────────┼── │ │ 17 │ 1 │ 19 │ 1.00E+00 │ 1.01E+00 │ 2.00E+00 │ 6.25E-02 │ ⋯ └─────────┴────┴───────┴─────────┴──────────┴──────────┴──────────┴──────────┴── 5 columns omitted var.obj[] = 1.006259811217959 max_dual_value = 1.026240581964922 duality_gap = -0.01985647297468698 ┌─────────┬────┬───────┬─────────┬──────────┬──────────┬──────────┬──────────┬── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ │ ⋯ ├─────────┼────┼───────┼─────────┼──────────┼──────────┼──────────┼──────────┼── │ │ 18 │ 1 │ 20 │ 1.00E+00 │ 1.00E+00 │ 2.00E+00 │ 3.12E-02 │ ⋯ └─────────┴────┴───────┴─────────┴──────────┴──────────┴──────────┴──────────┴── 5 columns omitted var.obj[] = 1.0003059472083842 max_dual_value = 1.026240581964922 duality_gap = -0.025926702554268814 ┌─────────┬────┬───────┬─────────┬──────────┬──────────┬──────────┬──────────┬── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ │ ⋯ ├─────────┼────┼───────┼─────────┼──────────┼──────────┼──────────┼──────────┼── │ │ 19 │ 0 │ 20 │ 1.00E+00 │ 1.00E+00 │ 2.00E+00 │ 1.56E-02 │ ⋯ └─────────┴────┴───────┴─────────┴──────────┴──────────┴──────────┴──────────┴── 5 columns omitted var.obj[] = 1.0003059472083842 max_dual_value = 1.026240581964922 duality_gap = -0.025926702554268814 ┌─────────┬────┬───────┬─────────┬──────────┬──────────┬──────────┬──────────┬── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ │ ⋯ ├─────────┼────┼───────┼─────────┼──────────┼──────────┼──────────┼──────────┼── │ │ 20 │ 2 │ 22 │ 1.00E+00 │ 9.99E-01 │ 2.00E+00 │ 7.81E-03 │ ⋯ └─────────┴────┴───────┴─────────┴──────────┴──────────┴──────────┴──────────┴── 5 columns omitted var.obj[] = 0.9992480027907109 max_dual_value = 1.026240581964922 duality_gap = -0.02701289279420723 ┌─────────┬────┬───────┬─────────┬──────────┬──────────┬──────────┬──────────┬── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ │ ⋯ ├─────────┼────┼───────┼─────────┼──────────┼──────────┼──────────┼──────────┼── │ │ 21 │ 1 │ 23 │ 1.00E+00 │ 1.00E+00 │ 2.00E+00 │ 3.91E-03 │ ⋯ └─────────┴────┴───────┴─────────┴──────────┴──────────┴──────────┴──────────┴── 5 columns omitted var.obj[] = 1.0003754029191343 max_dual_value = 1.026240581964922 duality_gap = -0.02585547282581337 ┌─────────┬────┬───────┬─────────┬──────────┬──────────┬──────────┬──────────┬── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ │ ⋯ ├─────────┼────┼───────┼─────────┼──────────┼──────────┼──────────┼──────────┼── │ │ 22 │ 1 │ 24 │ 1.00E+00 │ 1.00E+00 │ 2.00E+00 │ 1.95E-03 │ ⋯ └─────────┴────┴───────┴─────────┴──────────┴──────────┴──────────┴──────────┴── 5 columns omitted var.obj[] = 0.9999219155672198 max_dual_value = 1.026240581964922 duality_gap = -0.026320721636321643 ┌─────────┬────┬───────┬─────────┬──────────┬──────────┬──────────┬──────────┬── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ │ ⋯ ├─────────┼────┼───────┼─────────┼──────────┼──────────┼──────────┼──────────┼── │ │ 22 │ -1 │ 24 │ 1.00E+00 │ 1.00E+00 │ 2.00E+00 │ 1.95E-03 │ ⋯ └─────────┴────┴───────┴─────────┴──────────┴──────────┴──────────┴──────────┴── 5 columns omitted ========================================================================================================================= End of SDPLRPlus.jl ========================================================================================================================= Test Summary: | Pass Total Time Minimum Bisection | 1 1 2.2s Test Summary: | Total Time Lovasz Theta | 0 0.0s Test Summary: | Total Time Cut Norm | 0 0.0s [ Info: Max Cut SDP is formed. [ Info: Finish classifying constraints. [ Info: Max Cut SDP is formed. [ Info: Finish classifying constraints. [ Info: Max Cut SDP is formed. [ Info: Finish classifying constraints. [ Info: Max Cut SDP is formed. [ Info: Finish classifying constraints. [ Info: Max Cut SDP is formed. [ Info: Finish classifying constraints. [ Info: Max Cut SDP is formed. [ Info: Finish classifying constraints. [ Info: Max Cut SDP is formed. [ Info: Finish classifying constraints. [ Info: Max Cut SDP is formed. [ Info: Finish classifying constraints. [ Info: Max Cut SDP is formed. [ Info: Finish classifying constraints. [ Info: Max Cut SDP is formed. [ Info: Finish classifying constraints. [ Info: Max Cut SDP is formed. [ Info: Finish classifying constraints. [ Info: Max Cut SDP is formed. [ Info: Finish classifying constraints. [ Info: Lovasz Theta SDP is formed. [ Info: Finish classifying constraints. [ Info: Lovasz Theta SDP is formed. [ Info: Finish classifying constraints. [ Info: Lovasz Theta SDP is formed. [ Info: Finish classifying constraints. [ Info: Lovasz Theta SDP is formed. [ Info: Finish classifying constraints. [ Info: Lovasz Theta SDP is formed. [ Info: Finish classifying constraints. [ Info: Lovasz Theta SDP is formed. [ Info: Finish classifying constraints. [ Info: Lovasz Theta SDP is formed. [ Info: Finish classifying constraints. [ Info: Lovasz Theta SDP is formed. [ Info: Finish classifying constraints. [ Info: Lovasz Theta SDP is formed. [ Info: Finish classifying constraints. [ Info: Lovasz Theta SDP is formed. [ Info: Finish classifying constraints. [ Info: Lovasz Theta SDP is formed. [ Info: Finish classifying constraints. [ Info: Lovasz Theta SDP is formed. [ Info: Finish classifying constraints. [ Info: Minimum Bisection SDP is formed. [ Info: Finish classifying constraints. [ Info: Minimum Bisection SDP is formed. [ Info: Finish classifying constraints. [ Info: Minimum Bisection SDP is formed. [ Info: Finish classifying constraints. [ Info: Minimum Bisection SDP is formed. [ Info: Finish classifying constraints. [ Info: Minimum Bisection SDP is formed. [ Info: Finish classifying constraints. [ Info: Minimum Bisection SDP is formed. [ Info: Finish classifying constraints. [ Info: Minimum Bisection SDP is formed. [ Info: Finish classifying constraints. [ Info: Minimum Bisection SDP is formed. [ Info: Finish classifying constraints. [ Info: Minimum Bisection SDP is formed. [ Info: Finish classifying constraints. [ Info: Minimum Bisection SDP is formed. [ Info: Finish classifying constraints. [ Info: Minimum Bisection SDP is formed. [ Info: Finish classifying constraints. [ Info: Minimum Bisection SDP is formed. [ Info: Finish classifying constraints. [ Info: Cut Norm SDP is formed. [ Info: Finish classifying constraints. [ Info: Cut Norm SDP is formed. [ Info: Finish classifying constraints. [ Info: Cut Norm SDP is formed. [ Info: Finish classifying constraints. [ Info: Cut Norm SDP is formed. [ Info: Finish classifying constraints. [ Info: Cut Norm SDP is formed. [ Info: Finish classifying constraints. [ Info: Cut Norm SDP is formed. [ Info: Finish classifying constraints. [ Info: Cut Norm SDP is formed. [ Info: Finish classifying constraints. [ Info: Cut Norm SDP is formed. [ Info: Finish classifying constraints. [ Info: Cut Norm SDP is formed. [ Info: Finish classifying constraints. [ Info: Cut Norm SDP is formed. [ Info: Finish classifying constraints. [ Info: Cut Norm SDP is formed. [ Info: Finish classifying constraints. [ Info: Cut Norm SDP is formed. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. Test Summary: | Pass Total Time f!, g! and linesearch! | 252 252 28.7s [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. Test Summary: | Pass Total Time f!, g! with inequality constraints | 108 108 0.9s [ Info: Max Cut SDP is formed. [ Info: Finish classifying constraints. [ Info: Max Cut SDP is formed. [ Info: Finish classifying constraints. [ Info: Max Cut SDP is formed. [ Info: Finish classifying constraints. [ Info: Max Cut SDP is formed. [ Info: Finish classifying constraints. [ Info: Max Cut SDP is formed. [ Info: Finish classifying constraints. [ Info: Max Cut SDP is formed. [ Info: Finish classifying constraints. [ Info: Max Cut SDP is formed. [ Info: Finish classifying constraints. [ Info: Max Cut SDP is formed. [ Info: Finish classifying constraints. [ Info: Max Cut SDP is formed. [ Info: Finish classifying constraints. [ Info: Max Cut SDP is formed. [ Info: Finish classifying constraints. [ Info: Max Cut SDP is formed. [ Info: Finish classifying constraints. [ Info: Max Cut SDP is formed. [ Info: Finish classifying constraints. [ Info: Lovasz Theta SDP is formed. [ Info: Finish classifying constraints. [ Info: Lovasz Theta SDP is formed. [ Info: Finish classifying constraints. [ Info: Lovasz Theta SDP is formed. [ Info: Finish classifying constraints. [ Info: Lovasz Theta SDP is formed. [ Info: Finish classifying constraints. [ Info: Lovasz Theta SDP is formed. [ Info: Finish classifying constraints. [ Info: Lovasz Theta SDP is formed. [ Info: Finish classifying constraints. [ Info: Lovasz Theta SDP is formed. [ Info: Finish classifying constraints. [ Info: Lovasz Theta SDP is formed. [ Info: Finish classifying constraints. [ Info: Lovasz Theta SDP is formed. [ Info: Finish classifying constraints. [ Info: Lovasz Theta SDP is formed. [ Info: Finish classifying constraints. [ Info: Lovasz Theta SDP is formed. [ Info: Finish classifying constraints. [ Info: Lovasz Theta SDP is formed. [ Info: Finish classifying constraints. [ Info: Minimum Bisection SDP is formed. [ Info: Finish classifying constraints. [ Info: Minimum Bisection SDP is formed. [ Info: Finish classifying constraints. [ Info: Minimum Bisection SDP is formed. [ Info: Finish classifying constraints. [ Info: Minimum Bisection SDP is formed. [ Info: Finish classifying constraints. [ Info: Minimum Bisection SDP is formed. [ Info: Finish classifying constraints. [ Info: Minimum Bisection SDP is formed. [ Info: Finish classifying constraints. [ Info: Minimum Bisection SDP is formed. [ Info: Finish classifying constraints. [ Info: Minimum Bisection SDP is formed. [ Info: Finish classifying constraints. [ Info: Minimum Bisection SDP is formed. [ Info: Finish classifying constraints. [ Info: Minimum Bisection SDP is formed. [ Info: Finish classifying constraints. [ Info: Minimum Bisection SDP is formed. [ Info: Finish classifying constraints. [ Info: Minimum Bisection SDP is formed. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. Test Summary: | Pass Total Time 𝒜t! operator | 216 216 7.0s Testing SDPLRPlus tests passed Testing completed after 143.73s PkgEval succeeded after 302.29s