)]}'
{
  "commit": "41c5fb1e807178170f38e7c011922b35d192576b",
  "tree": "45795d906bf75fb24123d2f599f35526cbe3bb2c",
  "parents": [
    "12263e28305a2a43b6c6a6b4f7f76814ab7ffa5f"
  ],
  "author": {
    "name": "Sameer Agarwal",
    "email": "sameeragarwal@google.com",
    "time": "Thu May 19 00:47:24 2022 -0700"
  },
  "committer": {
    "name": "Sameer Agarwal",
    "email": "sameeragarwal@google.com",
    "time": "Thu May 19 11:05:46 2022 -0700"
  },
  "message": "Refactor suitesparse.h/cc\n\n1. Generalize SuiteSparse::AnalyzeCholesky and\n   SuiteSparse::BlockAnalyzeCholesky from just doing AMD to taking\n   OrderingType as an argument and using that to determine whether\n   AMD \u0026 Nested Dissection algorithms are used for computing the\n   fill-reducing ordering or a natural ordering when computing\n   the symbolic factorization.\n\n2. Remove AnalyzeCholeskyWithNaturalOrdering.\n\n3. Replace and generalize SuiteSparse::BlockAMDOrdering with\n   SuiteSparse::BlockOrdering which also takes OrderingType as an\n   argument. Same for SuiteSparse::ApproximateMinimumDegreeOrdering\n   and SuiteSparse::NestedDissectionOrdering by\n   SuiteSparse::Ordering.\n\n4. Remove LinearSolver::Options::use_postordering and replace it\n   with LinearSolver::Options::ordering_type.\n\n5. Replace Preconditioner::Options::use_postordering and replace it\n   with Preconditioner::Options::ordering_type.\n\n6. Add NESDIS to OrderingType. With the above changes, the linear\n   solvers can now use Nested Dissection once this information\n   is piped through the nonlinear solver.\n\nChange-Id: Ib8e93fbf34ae2981bf2ac54dcda9e25c7c213790\n",
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