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d5b93bf9ec
1. CX_SPARSE supports pre-ordering of the jacobian. 2. Add support for constrained approximate minimum degree ordering for SuiteSparse versions >= 4.2.0 3. Using 2, support for pre-ordering for SPARSE_SCHUR when used with SUITE_SPARSE. 4. Using 2, support for user orderings in SPARSE_NORMAL_CHOLESKY. 5. Minor cleanups in documentation and code all around. 6. Test update and refactoring. Change-Id: Ibfe3ac95d59d54ab14d1d60a07f767688070f29f
217 lines
9.3 KiB
C++
217 lines
9.3 KiB
C++
// Ceres Solver - A fast non-linear least squares minimizer
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// Copyright 2010, 2011, 2012 Google Inc. All rights reserved.
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// http://code.google.com/p/ceres-solver/
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//
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// Redistribution and use in source and binary forms, with or without
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// modification, are permitted provided that the following conditions are met:
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//
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// * Redistributions of source code must retain the above copyright notice,
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// this list of conditions and the following disclaimer.
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// * Redistributions in binary form must reproduce the above copyright notice,
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// this list of conditions and the following disclaimer in the documentation
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// and/or other materials provided with the distribution.
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// * Neither the name of Google Inc. nor the names of its contributors may be
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// used to endorse or promote products derived from this software without
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// specific prior written permission.
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//
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// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
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// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
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// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
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// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE
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// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
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// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
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// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
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// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
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// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
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// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
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// POSSIBILITY OF SUCH DAMAGE.
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//
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// Author: keir@google.com (Keir Mierle)
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#ifndef CERES_INTERNAL_SOLVER_IMPL_H_
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#define CERES_INTERNAL_SOLVER_IMPL_H_
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#include <set>
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#include <string>
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#include <vector>
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#include "ceres/internal/port.h"
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#include "ceres/ordered_groups.h"
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#include "ceres/problem_impl.h"
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#include "ceres/solver.h"
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namespace ceres {
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namespace internal {
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class CoordinateDescentMinimizer;
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class Evaluator;
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class LinearSolver;
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class Program;
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class TripletSparseMatrix;
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class SolverImpl {
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public:
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// Mirrors the interface in solver.h, but exposes implementation
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// details for testing internally.
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static void Solve(const Solver::Options& options,
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ProblemImpl* problem_impl,
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Solver::Summary* summary);
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static void TrustRegionSolve(const Solver::Options& options,
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ProblemImpl* problem_impl,
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Solver::Summary* summary);
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// Run the TrustRegionMinimizer for the given evaluator and configuration.
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static void TrustRegionMinimize(
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const Solver::Options &options,
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Program* program,
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CoordinateDescentMinimizer* inner_iteration_minimizer,
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Evaluator* evaluator,
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LinearSolver* linear_solver,
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double* parameters,
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Solver::Summary* summary);
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#ifndef CERES_NO_LINE_SEARCH_MINIMIZER
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static void LineSearchSolve(const Solver::Options& options,
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ProblemImpl* problem_impl,
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Solver::Summary* summary);
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// Run the LineSearchMinimizer for the given evaluator and configuration.
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static void LineSearchMinimize(const Solver::Options &options,
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Program* program,
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Evaluator* evaluator,
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double* parameters,
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Solver::Summary* summary);
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#endif // CERES_NO_LINE_SEARCH_MINIMIZER
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// Create the transformed Program, which has all the fixed blocks
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// and residuals eliminated, and in the case of automatic schur
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// ordering, has the E blocks first in the resulting program, with
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// options.num_eliminate_blocks set appropriately.
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//
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// If fixed_cost is not NULL, the residual blocks that are removed
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// are evaluated and the sum of their cost is returned in fixed_cost.
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static Program* CreateReducedProgram(Solver::Options* options,
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ProblemImpl* problem_impl,
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double* fixed_cost,
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string* error);
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// Create the appropriate linear solver, taking into account any
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// config changes decided by CreateTransformedProgram(). The
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// selected linear solver, which may be different from what the user
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// selected; consider the case that the remaining elimininated
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// blocks is zero after removing fixed blocks.
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static LinearSolver* CreateLinearSolver(Solver::Options* options,
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string* error);
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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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// for the Schur eliminator.
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static bool LexicographicallyOrderResidualBlocks(
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const int num_eliminate_blocks,
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Program* program,
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string* error);
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// Create the appropriate evaluator for the transformed program.
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static Evaluator* CreateEvaluator(
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const Solver::Options& options,
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const ProblemImpl::ParameterMap& parameter_map,
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Program* program,
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string* error);
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// Remove the fixed or unused parameter blocks and residuals
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// depending only on fixed parameters from the problem. Also updates
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// num_eliminate_blocks, since removed parameters changes the point
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// at which the eliminated blocks is valid. If fixed_cost is not
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// NULL, the residual blocks that are removed are evaluated and the
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// sum of their cost is returned in fixed_cost.
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static bool RemoveFixedBlocksFromProgram(Program* program,
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ParameterBlockOrdering* ordering,
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double* fixed_cost,
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string* error);
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static bool IsOrderingValid(const Solver::Options& options,
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const ProblemImpl* problem_impl,
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string* error);
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static bool IsParameterBlockSetIndependent(
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const set<double*>& parameter_block_ptrs,
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const vector<ResidualBlock*>& residual_blocks);
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static CoordinateDescentMinimizer* CreateInnerIterationMinimizer(
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const Solver::Options& options,
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const Program& program,
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const ProblemImpl::ParameterMap& parameter_map,
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Solver::Summary* summary);
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// If the linear solver is of Schur type, then replace it with the
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// closest equivalent linear solver. This is done when the user
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// requested a Schur type solver but the problem structure makes it
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// impossible to use one.
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//
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// If the linear solver is not of Schur type, the function is a
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// no-op.
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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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//
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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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Program* program,
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string* error);
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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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//
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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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Program* program,
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string* error);
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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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//
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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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//
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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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//
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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* parameter_block_ordering,
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Program* program,
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string* error);
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};
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} // namespace internal
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} // namespace ceres
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#endif // CERES_INTERNAL_SOLVER_IMPL_H_
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