)]}'
{
  "commit": "32530788d08c53f8d2c8a5f9bd61aa60a23d6e03",
  "tree": "df519f9957eebee9cd40b5a55fac486fca0bce9e",
  "parents": [
    "2569076ff0bf8ffb3938da8b5df7edc4883aa053"
  ],
  "author": {
    "name": "Richard Stebbing",
    "email": "richie.stebbing@gmail.com",
    "time": "Sat Apr 26 07:42:23 2014 +0100"
  },
  "committer": {
    "name": "Keir Mierle",
    "email": "mierle@gmail.com",
    "time": "Mon Apr 28 07:13:09 2014 +0000"
  },
  "message": "Add dynamic_sparsity option.\n\nThe standard sparse normal Cholesky solver assumes a fixed\nsparsity pattern which is useful for a large number of problems\npresented to Ceres. However, some problems are symbolically dense\nbut numerically sparse i.e. each residual is a function of a\nlarge number of parameters but at any given state the residual\nonly depends on a sparse subset of them. For these class of\nproblems it is faster to re-analyse the sparsity pattern of the\njacobian at each iteration of the non-linear optimisation instead\nof including all of the zero entries in the step computation.\n\nThe proposed solution adds the dynamic_sparsity option which can\nbe used with SPARSE_NORMAL_CHOLESKY. A\nDynamicCompressedRowSparseMatrix type (which extends\nCompressedRowSparseMatrix) has been introduced which allows\ndynamic addition and removal of elements. A Finalize method is\nprovided which then consolidates the matrix so that it can be\nused in place of a regular CompressedRowSparseMatrix. An\nassociated jacobian writer has also been provided.\n\nChanges that were required to make this extension were adding the\nSetMaxNumNonZeros method to CompressedRowSparseMatrix and adding\na JacobianFinalizer template parameter to the ProgramEvaluator.\n\nChange-Id: Ia5a8a9523fdae8d5b027bc35e70b4611ec2a8d01\n",
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