Package evaluation to test SDPLRPlus on Julia 1.14.0-DEV.1877 (00654c1407*) started at 2026-03-10T20:09:37.426 ################################################################################ # Set-up # Installing PkgEval dependencies (TestEnv)... Activating project at `~/.julia/environments/v1.14` Set-up completed after 14.02s ################################################################################ # 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 v0.21.11 [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 v1.9.17 [1e83bf80] + StaticArraysCore v1.4.4 [10745b16] + Statistics v1.11.1 [892a3eda] + StringManipulation v0.4.4 [ec057cc2] + StructUtils v2.6.3 [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 v8.18.0+1 [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 v17.7.0+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 5.04s ################################################################################ # Precompilation # Precompiling PkgEval dependencies... Precompiling package dependencies... Precompiling packages... 20106.2 ms ✓ SDPLRPlus 1 dependency successfully precompiled in 23 seconds. 126 already precompiled. Precompilation completed after 45.98s ################################################################################ # Testing # Testing SDPLRPlus Status `/tmp/jl_Vydr5m/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_Vydr5m/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 v0.21.11 [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 v1.9.17 [1e83bf80] StaticArraysCore v1.4.4 [10745b16] Statistics v1.11.1 [892a3eda] StringManipulation v0.4.4 [ec057cc2] StructUtils v2.6.3 [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 v8.18.0+1 [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 v17.7.0+0 Info Packages marked with ⌅ have new versions available but compatibility constraints restrict them from upgrading. Testing Running tests... Test Summary: | Pass Total Time SymLowRankMatrix tests | 200 200 5.6s [ 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 │ 3 │ 3 │ -1.12E+00 │ -1.25E+00 │ 2.00E+00 │ 5.00E-01 ⋯ └─────────┴───┴───────┴─────────┴───────────┴───────────┴──────────┴──────────── 5 columns omitted var.obj[] = -1.2464122808766995 max_dual_value = -0.9857249654512705 duality_gap = -0.26446252713715623 ┌─────────┬───┬───────┬─────────┬───────────┬───────────┬──────────┬──────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼───┼───────┼─────────┼───────────┼───────────┼──────────┼──────────── │ │ 2 │ 1 │ 4 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 2.50E-01 ⋯ └─────────┴───┴───────┴─────────┴───────────┴───────────┴──────────┴──────────── 5 columns omitted var.obj[] = -1.003804558288948 max_dual_value = -0.9857249654512705 duality_gap = -0.01834141720190746 ┌─────────┬───┬───────┬─────────┬───────────┬───────────┬──────────┬──────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼───┼───────┼─────────┼───────────┼───────────┼──────────┼──────────── │ │ 3 │ 1 │ 5 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 1.25E-01 ⋯ └─────────┴───┴───────┴─────────┴───────────┴───────────┴──────────┴──────────── 5 columns omitted var.obj[] = -1.0000706653537825 max_dual_value = -0.9857249654512705 duality_gap = -0.014553450917157663 ┌─────────┬───┬───────┬─────────┬───────────┬───────────┬──────────┬──────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼───┼───────┼─────────┼───────────┼───────────┼──────────┼──────────── │ │ 4 │ 0 │ 5 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 6.25E-02 ⋯ └─────────┴───┴───────┴─────────┴───────────┴───────────┴──────────┴──────────── 5 columns omitted var.obj[] = -1.0000706653537828 max_dual_value = -0.9857249654512705 duality_gap = -0.014553450917157889 ┌─────────┬───┬───────┬─────────┬───────────┬───────────┬──────────┬──────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼───┼───────┼─────────┼───────────┼───────────┼──────────┼──────────── │ │ 5 │ 1 │ 6 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 3.12E-02 ⋯ └─────────┴───┴───────┴─────────┴───────────┴───────────┴──────────┴──────────── 5 columns omitted var.obj[] = -0.9996386322443096 max_dual_value = -0.9857249654512705 duality_gap = -0.014115161206928866 ┌─────────┬───┬───────┬─────────┬───────────┬───────────┬──────────┬──────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼───┼───────┼─────────┼───────────┼───────────┼──────────┼──────────── │ │ 6 │ 1 │ 7 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 1.56E-02 ⋯ └─────────┴───┴───────┴─────────┴───────────┴───────────┴──────────┴──────────── 5 columns omitted var.obj[] = -0.9999156477438481 max_dual_value = -0.9857249654512705 duality_gap = -0.014396188379058664 ┌─────────┬───┬───────┬─────────┬───────────┬───────────┬──────────┬──────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼───┼───────┼─────────┼───────────┼───────────┼──────────┼──────────── │ │ 7 │ 0 │ 7 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 7.81E-03 ⋯ └─────────┴───┴───────┴─────────┴───────────┴───────────┴──────────┴──────────── 5 columns omitted var.obj[] = -0.9999156477438481 max_dual_value = -0.9857249654512705 duality_gap = -0.014396188379058664 ┌─────────┬───┬───────┬─────────┬───────────┬───────────┬──────────┬──────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼───┼───────┼─────────┼───────────┼───────────┼──────────┼──────────── │ │ 8 │ 0 │ 7 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 3.91E-03 ⋯ └─────────┴───┴───────┴─────────┴───────────┴───────────┴──────────┴──────────── 5 columns omitted var.obj[] = -0.9999156477438481 max_dual_value = -0.9857249654512705 duality_gap = -0.014396188379058664 ┌─────────┬───┬───────┬─────────┬───────────┬───────────┬──────────┬──────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼───┼───────┼─────────┼───────────┼───────────┼──────────┼──────────── │ │ 9 │ 1 │ 8 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 1.95E-03 ⋯ └─────────┴───┴───────┴─────────┴───────────┴───────────┴──────────┴──────────── 5 columns omitted var.obj[] = -1.0001806836316656 max_dual_value = -0.9857249654512705 duality_gap = -0.014665062453579156 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 10 │ 1 │ 9 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 9.77E-04 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -1.000035112995057 max_dual_value = -0.9857249654512705 duality_gap = -0.014517383697627359 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 11 │ 1 │ 10 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 4.88E-04 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -0.9999869960475601 max_dual_value = -0.9857249654512705 duality_gap = -0.014468569931938744 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 12 │ 0 │ 10 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 2.44E-04 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -0.9999869960475604 max_dual_value = -0.9857249654512705 duality_gap = -0.01446856993193897 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 13 │ 1 │ 11 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 1.22E-04 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -1.0000120607796668 max_dual_value = -0.9857249654512705 duality_gap = -0.01449399764553545 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 14 │ 1 │ 12 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 6.10E-05 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -1.0000014695088484 max_dual_value = -0.9857249654512705 duality_gap = -0.014483252994451641 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 15 │ 0 │ 12 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 3.05E-05 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -1.0000014695088484 max_dual_value = -0.9857249654512705 duality_gap = -0.014483252994451641 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 16 │ 1 │ 13 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 1.53E-05 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -0.999998127769499 max_dual_value = -0.9857249654512705 duality_gap = -0.014479862860827685 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 17 │ 1 │ 14 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 7.63E-06 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -0.9999997521204335 max_dual_value = -0.9857249654512705 duality_gap = -0.01448151073522608 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 18 │ 1 │ 15 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 3.81E-06 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -1.0000000897837162 max_dual_value = -0.9857249654512705 duality_gap = -0.014481853288468226 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 19 │ 0 │ 15 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 1.91E-06 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -1.0000000897837162 max_dual_value = -0.9857249654512705 duality_gap = -0.014481853288468226 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 20 │ 1 │ 16 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 9.54E-07 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -0.9999999327063743 max_dual_value = -0.9857249654512705 duality_gap = -0.0144816939363696 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 21 │ 1 │ 17 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 4.77E-07 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -0.9999999831237589 max_dual_value = -0.9857249654512705 duality_gap = -0.014481745083886777 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 22 │ 1 │ 18 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 2.38E-07 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -1.0000000049685356 max_dual_value = -0.9857249654512705 duality_gap = -0.014481767245014291 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 22 │ -1 │ 18 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 2.38E-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 │ 4 │ 4 │ -1.02E+00 │ -1.05E+00 │ 1.00E+01 │ 1.00E-01 ⋯ └─────────┴───┴───────┴─────────┴───────────┴───────────┴──────────┴──────────── 5 columns omitted var.obj[] = -1.05019894696544 max_dual_value = -1.0039789618475439 duality_gap = -0.046036806421562 ┌─────────┬───┬───────┬─────────┬───────────┬───────────┬──────────┬──────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼───┼───────┼─────────┼───────────┼───────────┼──────────┼──────────── │ │ 2 │ 1 │ 5 │ -1.00E+00 │ -1.00E+00 │ 1.00E+01 │ 1.00E-02 ⋯ └─────────┴───┴───────┴─────────┴───────────┴───────────┴──────────┴──────────── 5 columns omitted var.obj[] = -0.9998010645533462 max_dual_value = -1.0000002788627356 duality_gap = 0.00019925394806256147 ┌─────────┬───┬───────┬─────────┬───────────┬───────────┬──────────┬──────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼───┼───────┼─────────┼───────────┼───────────┼──────────┼──────────── │ │ 3 │ 1 │ 6 │ -1.00E+00 │ -1.00E+00 │ 1.00E+01 │ 1.00E-03 ⋯ └─────────┴───┴───────┴─────────┴───────────┴───────────┴──────────┴──────────── 5 columns omitted var.obj[] = -0.999999342216483 max_dual_value = -0.9999871233061879 duality_gap = -1.2219067636317963e-5 ┌─────────┬───┬───────┬─────────┬───────────┬───────────┬──────────┬──────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼───┼───────┼─────────┼───────────┼───────────┼──────────┼──────────── │ │ 4 │ 1 │ 7 │ -1.00E+00 │ -1.00E+00 │ 1.00E+01 │ 1.00E-04 ⋯ └─────────┴───┴───────┴─────────┴───────────┴───────────┴──────────┴──────────── 5 columns omitted var.obj[] = -1.0000006132885797 max_dual_value = -0.9999871233061879 duality_gap = -1.3490156100421788e-5 ┌─────────┬───┬───────┬─────────┬───────────┬───────────┬──────────┬──────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼───┼───────┼─────────┼───────────┼───────────┼──────────┼──────────── │ │ 5 │ 1 │ 8 │ -1.00E+00 │ -1.00E+00 │ 1.00E+01 │ 1.00E-05 ⋯ └─────────┴───┴───────┴─────────┴───────────┴───────────┴──────────┴──────────── 5 columns omitted var.obj[] = -1.0000000429696467 max_dual_value = -0.9999871233061879 duality_gap = -1.2919829823536286e-5 ┌─────────┬───┬───────┬─────────┬───────────┬───────────┬──────────┬──────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼───┼───────┼─────────┼───────────┼───────────┼──────────┼──────────── │ │ 6 │ 1 │ 9 │ -1.00E+00 │ -1.00E+00 │ 1.00E+01 │ 1.00E-06 ⋯ └─────────┴───┴───────┴─────────┴───────────┴───────────┴──────────┴──────────── 5 columns omitted var.obj[] = -0.99999998775519 max_dual_value = -0.9999871233061879 duality_gap = -1.2864614655763008e-5 ┌─────────┬───┬───────┬─────────┬───────────┬───────────┬──────────┬──────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼───┼───────┼─────────┼───────────┼───────────┼──────────┼──────────── │ │ 7 │ 1 │ 10 │ -1.00E+00 │ -1.00E+00 │ 1.00E+01 │ 1.00E-07 ⋯ └─────────┴───┴───────┴─────────┴───────────┴───────────┴──────────┴──────────── 5 columns omitted var.obj[] = -0.9999999997857306 max_dual_value = -0.9999871233061879 duality_gap = -1.287664535135337e-5 ┌─────────┬───┬───────┬─────────┬───────────┬───────────┬──────────┬──────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼───┼───────┼─────────┼───────────┼───────────┼──────────┼──────────── │ │ 7 │ -1 │ 10 │ -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 │ 5 │ 5 │ -1.12E+00 │ -1.25E+00 │ 2.00E+00 │ 5.00E-01 ⋯ └─────────┴───┴───────┴─────────┴───────────┴───────────┴──────────┴──────────── 5 columns omitted var.obj[] = -1.2513113115085044 max_dual_value = -1.0052472099846559 duality_gap = -0.24477969108474762 ┌─────────┬───┬───────┬─────────┬───────────┬───────────┬──────────┬──────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼───┼───────┼─────────┼───────────┼───────────┼──────────┼──────────── │ │ 2 │ 1 │ 6 │ -1.00E+00 │ -9.99E-01 │ 2.00E+00 │ 2.50E-01 ⋯ └─────────┴───┴───────┴─────────┴───────────┴───────────┴──────────┴──────────── 5 columns omitted var.obj[] = -0.9986941678290012 max_dual_value = -1.000027327708321 duality_gap = 0.0013349030386527376 ┌─────────┬───┬───────┬─────────┬───────────┬───────────┬──────────┬──────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼───┼───────┼─────────┼───────────┼───────────┼──────────┼──────────── │ │ 3 │ 0 │ 6 │ -1.00E+00 │ -9.99E-01 │ 2.00E+00 │ 1.25E-01 ⋯ └─────────┴───┴───────┴─────────┴───────────┴───────────┴──────────┴──────────── 5 columns omitted var.obj[] = -0.9986941678290011 max_dual_value = -0.9948074454319853 duality_gap = -0.003907009758383993 ┌─────────┬───┬───────┬─────────┬───────────┬───────────┬──────────┬──────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼───┼───────┼─────────┼───────────┼───────────┼──────────┼──────────── │ │ 4 │ 0 │ 6 │ -1.00E+00 │ -9.99E-01 │ 2.00E+00 │ 6.25E-02 ⋯ └─────────┴───┴───────┴─────────┴───────────┴───────────┴──────────┴──────────── 5 columns omitted var.obj[] = -0.9986941678290011 max_dual_value = -0.9895875631556497 duality_gap = -0.009202424335560384 ┌─────────┬───┬───────┬─────────┬───────────┬───────────┬──────────┬──────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼───┼───────┼─────────┼───────────┼───────────┼──────────┼──────────── │ │ 5 │ 1 │ 7 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 3.12E-02 ⋯ └─────────┴───┴───────┴─────────┴───────────┴───────────┴──────────┴──────────── 5 columns omitted var.obj[] = -1.0022815445745095 max_dual_value = -0.9895875631556497 duality_gap = -0.01282754744651454 ┌─────────┬───┬───────┬─────────┬───────────┬───────────┬──────────┬──────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼───┼───────┼─────────┼───────────┼───────────┼──────────┼──────────── │ │ 6 │ 1 │ 8 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 1.56E-02 ⋯ └─────────┴───┴───────┴─────────┴───────────┴───────────┴──────────┴──────────── 5 columns omitted var.obj[] = -1.0004909710274983 max_dual_value = -0.9895875631556497 duality_gap = -0.011018133490965929 ┌─────────┬───┬───────┬─────────┬───────────┬───────────┬──────────┬──────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼───┼───────┼─────────┼───────────┼───────────┼──────────┼──────────── │ │ 7 │ 0 │ 8 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 7.81E-03 ⋯ └─────────┴───┴───────┴─────────┴───────────┴───────────┴──────────┴──────────── 5 columns omitted var.obj[] = -1.0004909710274983 max_dual_value = -0.9895875631556497 duality_gap = -0.011018133490965929 ┌─────────┬───┬───────┬─────────┬───────────┬───────────┬──────────┬──────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼───┼───────┼─────────┼───────────┼───────────┼──────────┼──────────── │ │ 8 │ 1 │ 9 │ -1.00E+00 │ -9.99E-01 │ 2.00E+00 │ 3.91E-03 ⋯ └─────────┴───┴───────┴─────────┴───────────┴───────────┴──────────┴──────────── 5 columns omitted var.obj[] = -0.9993413547715622 max_dual_value = -0.9895875631556497 duality_gap = -0.00985642097684523 ┌─────────┬───┬───────┬─────────┬───────────┬───────────┬──────────┬──────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼───┼───────┼─────────┼───────────┼───────────┼──────────┼──────────── │ │ 9 │ 1 │ 10 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 1.95E-03 ⋯ └─────────┴───┴───────┴─────────┴───────────┴───────────┴──────────┴──────────── 5 columns omitted var.obj[] = -0.9999930969964183 max_dual_value = -0.9895875631556497 duality_gap = -0.010515020831089334 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 10 │ 0 │ 10 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 9.77E-04 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -0.9999930969964183 max_dual_value = -0.9895875631556497 duality_gap = -0.010515020831089334 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 11 │ 1 │ 11 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 4.88E-04 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -1.0000069388046406 max_dual_value = -0.9895875631556497 duality_gap = -0.010529008282768954 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 12 │ 1 │ 12 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 2.44E-04 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -1.00000221203338 max_dual_value = -0.9895875631556497 duality_gap = -0.010524231776437822 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 13 │ 0 │ 12 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 1.22E-04 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -1.0000022120333802 max_dual_value = -0.9895875631556497 duality_gap = -0.010524231776438048 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 14 │ 1 │ 13 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 6.10E-05 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -0.9999975577379514 max_dual_value = -0.9895875631556497 duality_gap = -0.010519528508529143 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 15 │ 1 │ 14 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 3.05E-05 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -0.9999994994272741 max_dual_value = -0.9895875631556497 duality_gap = -0.010521490628299998 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 16 │ 0 │ 14 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 1.53E-05 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -0.9999994994272741 max_dual_value = -0.9895875631556497 duality_gap = -0.010521490628299998 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 17 │ 1 │ 15 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 7.63E-06 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -1.000000649988483 max_dual_value = -0.9895875631556497 duality_gap = -0.010522653295709948 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 18 │ 1 │ 16 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 3.81E-06 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -1.0000000155540187 max_dual_value = -0.9895875631556497 duality_gap = -0.01052201218572846 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 19 │ 0 │ 16 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 1.91E-06 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -1.000000015554019 max_dual_value = -0.9895875631556497 duality_gap = -0.010522012185728683 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 20 │ 1 │ 17 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 9.54E-07 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -0.9999999797143174 max_dual_value = -0.9895875631556497 duality_gap = -0.01052197596892193 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 21 │ 1 │ 18 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 4.77E-07 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -0.9999999947079641 max_dual_value = -0.9895875631556497 duality_gap = -0.010521991120331685 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 21 │ -1 │ 18 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 4.77E-07 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted ========================================================================================================================= End of SDPLRPlus.jl ========================================================================================================================= Test Summary: | Pass Total Time Max Cut | 3 3 1m24.9s [ 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 │ 2 │ 2 │ 8.76E-01 │ 7.67E-01 │ 2.00E+00 │ 5.00E-01 │ ⋯ └─────────┴───┴───────┴─────────┴──────────┴──────────┴──────────┴──────────┴─── 5 columns omitted var.obj[] = 0.7666740821186381 max_dual_value = 0.5222828165018496 duality_gap = 0.4679289800374334 ┌─────────┬───┬───────┬─────────┬──────────┬──────────┬──────────┬──────────┬─── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ │ ⋯ ├─────────┼───┼───────┼─────────┼──────────┼──────────┼──────────┼──────────┼─── │ │ 2 │ 1 │ 3 │ 9.99E-01 │ 9.83E-01 │ 2.00E+00 │ 2.50E-01 │ ⋯ └─────────┴───┴───────┴─────────┴──────────┴──────────┴──────────┴──────────┴─── 5 columns omitted var.obj[] = 0.9833530308520774 max_dual_value = 0.5222828165018496 duality_gap = 0.8827979779966492 ┌─────────┬───┬───────┬─────────┬──────────┬──────────┬──────────┬──────────┬─── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ │ ⋯ ├─────────┼───┼───────┼─────────┼──────────┼──────────┼──────────┼──────────┼─── │ │ 3 │ 1 │ 4 │ 1.00E+00 │ 1.00E+00 │ 2.00E+00 │ 1.25E-01 │ ⋯ └─────────┴───┴───────┴─────────┴──────────┴──────────┴──────────┴──────────┴─── 5 columns omitted var.obj[] = 0.9999739756041635 max_dual_value = 0.5744967886649005 duality_gap = 0.7406084687227737 ┌─────────┬───┬───────┬─────────┬──────────┬──────────┬──────────┬──────────┬─── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ │ ⋯ ├─────────┼───┼───────┼─────────┼──────────┼──────────┼──────────┼──────────┼─── │ │ 4 │ 0 │ 4 │ 1.00E+00 │ 1.00E+00 │ 2.00E+00 │ 6.25E-02 │ ⋯ └─────────┴───┴───────┴─────────┴──────────┴──────────┴──────────┴──────────┴─── 5 columns omitted var.obj[] = 0.9999739756041637 max_dual_value = 0.5744967886649005 duality_gap = 0.7406084687227742 ┌─────────┬───┬───────┬─────────┬──────────┬──────────┬──────────┬──────────┬─── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ │ ⋯ ├─────────┼───┼───────┼─────────┼──────────┼──────────┼──────────┼──────────┼─── │ │ 5 │ 0 │ 4 │ 1.00E+00 │ 1.00E+00 │ 2.00E+00 │ 3.12E-02 │ ⋯ └─────────┴───┴───────┴─────────┴──────────┴──────────┴──────────┴──────────┴─── 5 columns omitted var.obj[] = 0.9999739756041637 max_dual_value = 0.5744967886649005 duality_gap = 0.7406084687227742 ┌─────────┬───┬───────┬─────────┬──────────┬──────────┬──────────┬──────────┬─── │ 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[] = 1.000052281190417 max_dual_value = 0.5744967886649005 duality_gap = 0.7407447716365558 ┌─────────┬───┬───────┬─────────┬──────────┬──────────┬──────────┬──────────┬─── │ 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[] = 0.9999717700921752 max_dual_value = 0.5744967886649005 duality_gap = 0.7406046296900206 ┌─────────┬───┬───────┬─────────┬──────────┬──────────┬──────────┬──────────┬─── │ 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[] = 1.000025250914093 max_dual_value = 0.5744967886649005 duality_gap = 0.7406977212842175 ┌─────────┬───┬───────┬─────────┬──────────┬──────────┬──────────┬──────────┬─── │ 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[] = 1.0000252509140928 max_dual_value = 0.9582486143586799 duality_gap = 0.04359686612578345 ┌─────────┬────┬───────┬─────────┬──────────┬──────────┬──────────┬──────────┬── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ │ ⋯ ├─────────┼────┼───────┼─────────┼──────────┼──────────┼──────────┼──────────┼── │ │ 10 │ 1 │ 8 │ 1.00E+00 │ 1.00E+00 │ 2.00E+00 │ 9.77E-04 │ ⋯ └─────────┴────┴───────┴─────────┴──────────┴──────────┴──────────┴──────────┴── 5 columns omitted var.obj[] = 0.9999616090556223 max_dual_value = 0.9582486143586799 duality_gap = 0.04353045135876277 ┌─────────┬────┬───────┬─────────┬──────────┬──────────┬──────────┬──────────┬── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ │ ⋯ ├─────────┼────┼───────┼─────────┼──────────┼──────────┼──────────┼──────────┼── │ │ 11 │ 1 │ 9 │ 1.00E+00 │ 1.00E+00 │ 2.00E+00 │ 4.88E-04 │ ⋯ └─────────┴────┴───────┴─────────┴──────────┴──────────┴──────────┴──────────┴── 5 columns omitted var.obj[] = 1.0000113438875833 max_dual_value = 0.9582486143586799 duality_gap = 0.04358235316296659 ┌─────────┬────┬───────┬─────────┬──────────┬──────────┬──────────┬──────────┬── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ │ ⋯ ├─────────┼────┼───────┼─────────┼──────────┼──────────┼──────────┼──────────┼── │ │ 12 │ 0 │ 9 │ 1.00E+00 │ 1.00E+00 │ 2.00E+00 │ 2.44E-04 │ ⋯ └─────────┴────┴───────┴─────────┴──────────┴──────────┴──────────┴──────────┴── 5 columns omitted var.obj[] = 1.0000113438875833 max_dual_value = 0.9582486143586799 duality_gap = 0.04358235316296659 ┌─────────┬────┬───────┬─────────┬──────────┬──────────┬──────────┬──────────┬── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ │ ⋯ ├─────────┼────┼───────┼─────────┼──────────┼──────────┼──────────┼──────────┼── │ │ 13 │ 1 │ 10 │ 1.00E+00 │ 1.00E+00 │ 2.00E+00 │ 1.22E-04 │ ⋯ └─────────┴────┴───────┴─────────┴──────────┴──────────┴──────────┴──────────┴── 5 columns omitted var.obj[] = 0.9999837629436599 max_dual_value = 0.9999977567414327 duality_gap = -1.3994024994554463e-5 ┌─────────┬────┬───────┬─────────┬──────────┬──────────┬──────────┬──────────┬── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ │ ⋯ ├─────────┼────┼───────┼─────────┼──────────┼──────────┼──────────┼──────────┼── │ │ 13 │ -1 │ 10 │ 1.00E+00 │ 1.00E+00 │ 2.00E+00 │ 1.22E-04 │ ⋯ └─────────┴────┴───────┴─────────┴──────────┴──────────┴──────────┴──────────┴── 5 columns omitted ========================================================================================================================= End of SDPLRPlus.jl ========================================================================================================================= Test Summary: | Pass Total Time Minimum Bisection | 1 1 1.9s 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 23.0s [ 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 0.7s [ 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 5.1s Testing SDPLRPlus tests passed Testing completed after 150.95s PkgEval succeeded after 227.9s