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static LinearSolver* CreateLinearSolver(Solver::Options* options,
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// Reorder the parameter blocks in program using the ordering. A
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// return value of true indicates success and false indicates an
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// error was encountered whose cause is logged to LOG(ERROR).
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static bool ApplyUserOrdering(const ProblemImpl::ParameterMap& parameter_map,
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const ParameterBlockOrdering* ordering,
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// Reorder the residuals for program, if necessary, so that the
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// residuals involving e block (i.e., the first num_eliminate_block
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// parameter blocks) occur together. This is a necessary condition
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static void AlternateLinearSolverForSchurTypeLinearSolver(
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Solver::Options* options);
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// Create a TripletSparseMatrix which contains the zero-one
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// structure corresponding to the block sparsity of the transpose of
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// the Jacobian matrix.
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// Caller owns the result.
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static TripletSparseMatrix* CreateJacobianBlockSparsityTranspose(
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const Program* program);
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// Reorder the parameter blocks in program using the ordering
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static bool ApplyUserOrdering(
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const ProblemImpl::ParameterMap& parameter_map,
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const ParameterBlockOrdering* parameter_block_ordering,
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// Sparse cholesky factorization routines when doing the sparse
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// cholesky factorization of the Jacobian matrix, reorders its
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// columns to reduce the fill-in. Compute this permutation and
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// re-order the parameter blocks.
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// If the parameter_block_ordering contains more than one
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// elimination group and support for constrained fill-reducing
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// ordering is available in the sparse linear algebra library
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// (SuiteSparse version >= 4.2.0) then the fill reducing
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// ordering will take it into account, otherwise it will be ignored.
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static bool ReorderProgramForSparseNormalCholesky(
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const SparseLinearAlgebraLibraryType sparse_linear_algebra_library_type,
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const ParameterBlockOrdering* parameter_block_ordering,
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// Schur type solvers require that all parameter blocks eliminated
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// by the Schur eliminator occur before others and the residuals be
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// sorted in lexicographic order of their parameter blocks.
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// If ordering has atleast two groups, then apply the ordering,
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// otherwise compute a new ordering using a Maximal Independent Set
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// algorithm and apply it.
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// If the parameter_block_ordering only contains one elimination
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// group then a maximal independent set is computed and used as the
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// first elimination group, otherwise the user's ordering is used.
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// If the linear solver type is SPARSE_SCHUR and support for
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// constrained fill-reducing ordering is available in the sparse
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// linear algebra library (SuiteSparse version >= 4.2.0) then
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// columns of the schur complement matrix are ordered to reduce the
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// fill-in the Cholesky factorization.
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// Upon return, ordering contains the parameter block ordering that
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// was used to order the program.
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static bool ReorderProgramForSchurTypeLinearSolver(
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const LinearSolverType linear_solver_type,
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const SparseLinearAlgebraLibraryType sparse_linear_algebra_library_type,
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const ProblemImpl::ParameterMap& parameter_map,
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ParameterBlockOrdering* ordering,
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ParameterBlockOrdering* parameter_block_ordering,
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Program* program,
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// CHOLMOD when doing the sparse cholesky factorization of the
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// Jacobian matrix, reorders its columns to reduce the
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// fill-in. Compute this permutation and re-order the parameter
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static void ReorderProgramForSparseNormalCholesky(Program* program);
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// Create a TripletSparseMatrix which contains the zero-one
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// structure corresponding to the block sparsity of the transpose of
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// the Jacobian matrix.
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// Caller owns the result.
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static TripletSparseMatrix* CreateJacobianBlockSparsityTranspose(
195
const Program* program);
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// array contains a list of (possibly repeating) non-negative
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// integers. Let us assume that we have constructed another array
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// `p` by sorting and uniqueing the entries of array.
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// CompactifyArray replaces each entry in "array" with its position
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static void CompactifyArray(vector<int>* array);
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} // namespace internal
added
removed
extern/libmv/third_party/ceres/internal/ceres/solver_impl.h
