internal/ceres/solver_impl.h - ceres-solver - Git at Google

 // Ceres Solver - A fast non-linear least squares minimizer
 // Copyright 2010, 2011, 2012 Google Inc. All rights reserved.
 // http://code.google.com/p/ceres-solver/
 //
 // Redistribution and use in source and binary forms, with or without
 // modification, are permitted provided that the following conditions are met:
 //
 // * Redistributions of source code must retain the above copyright notice,
 //   this list of conditions and the following disclaimer.
 // * Redistributions in binary form must reproduce the above copyright notice,
 //   this list of conditions and the following disclaimer in the documentation
 //   and/or other materials provided with the distribution.
 // * Neither the name of Google Inc. nor the names of its contributors may be
 //   used to endorse or promote products derived from this software without
 //   specific prior written permission.
 //
 // THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
 // AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
 // IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
 // ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE
 // LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
 // CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
 // SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
 // INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
 // CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
 // ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
 // POSSIBILITY OF SUCH DAMAGE.
 //
 // Author: keir@google.com (Keir Mierle)

 #ifndef CERES_INTERNAL_SOLVER_IMPL_H_
 #define CERES_INTERNAL_SOLVER_IMPL_H_

 #include <set>
 #include <string>
 #include <vector>
 #include "ceres/internal/port.h"
 #include "ceres/ordered_groups.h"
 #include "ceres/problem_impl.h"
 #include "ceres/solver.h"

 namespace ceres {
 namespace internal {

 class CoordinateDescentMinimizer;
 class Evaluator;
 class LinearSolver;
 class Program;
 class TripletSparseMatrix;

 class SolverImpl {
  public:
   // Mirrors the interface in solver.h, but exposes implementation
   // details for testing internally.
   static void Solve(const Solver::Options& options,
                     ProblemImpl* problem_impl,
                     Solver::Summary* summary);

   static void TrustRegionSolve(const Solver::Options& options,
                                ProblemImpl* problem_impl,
                                Solver::Summary* summary);

   // Run the TrustRegionMinimizer for the given evaluator and configuration.
   static void TrustRegionMinimize(
       const Solver::Options &options,
       Program* program,
       CoordinateDescentMinimizer* inner_iteration_minimizer,
       Evaluator* evaluator,
       LinearSolver* linear_solver,
       double* parameters,
       Solver::Summary* summary);

 #ifndef CERES_NO_LINE_SEARCH_MINIMIZER
   static void LineSearchSolve(const Solver::Options& options,
                               ProblemImpl* problem_impl,
                               Solver::Summary* summary);

   // Run the LineSearchMinimizer for the given evaluator and configuration.
   static void LineSearchMinimize(const Solver::Options &options,
                                  Program* program,
                                  Evaluator* evaluator,
                                  double* parameters,
                                  Solver::Summary* summary);
 #endif  // CERES_NO_LINE_SEARCH_MINIMIZER

   // Create the transformed Program, which has all the fixed blocks
   // and residuals eliminated, and in the case of automatic schur
   // ordering, has the E blocks first in the resulting program, with
   // options.num_eliminate_blocks set appropriately.
   //
   // If fixed_cost is not NULL, the residual blocks that are removed
   // are evaluated and the sum of their cost is returned in fixed_cost.
   static Program* CreateReducedProgram(Solver::Options* options,
                                        ProblemImpl* problem_impl,
                                        double* fixed_cost,
                                        string* error);

   // Create the appropriate linear solver, taking into account any
   // config changes decided by CreateTransformedProgram(). The
   // selected linear solver, which may be different from what the user
   // selected; consider the case that the remaining elimininated
   // blocks is zero after removing fixed blocks.
   static LinearSolver* CreateLinearSolver(Solver::Options* options,
                                           string* error);

   // Reorder the residuals for program, if necessary, so that the
   // residuals involving e block (i.e., the first num_eliminate_block
   // parameter blocks) occur together. This is a necessary condition
   // for the Schur eliminator.
   static bool LexicographicallyOrderResidualBlocks(
       const int num_eliminate_blocks,
       Program* program,
       string* error);

   // Create the appropriate evaluator for the transformed program.
   static Evaluator* CreateEvaluator(
       const Solver::Options& options,
       const ProblemImpl::ParameterMap& parameter_map,
       Program* program,
       string* error);

   // Remove the fixed or unused parameter blocks and residuals
   // depending only on fixed parameters from the problem. Also updates
   // num_eliminate_blocks, since removed parameters changes the point
   // at which the eliminated blocks is valid.  If fixed_cost is not
   // NULL, the residual blocks that are removed are evaluated and the
   // sum of their cost is returned in fixed_cost.
   static bool RemoveFixedBlocksFromProgram(Program* program,
                                            ParameterBlockOrdering* ordering,
                                            double* fixed_cost,
                                            string* error);

   static bool IsOrderingValid(const Solver::Options& options,
                               const ProblemImpl* problem_impl,
                               string* error);

   static bool IsParameterBlockSetIndependent(
       const set<double*>& parameter_block_ptrs,
       const vector<ResidualBlock*>& residual_blocks);

   static CoordinateDescentMinimizer* CreateInnerIterationMinimizer(
       const Solver::Options& options,
       const Program& program,
       const ProblemImpl::ParameterMap& parameter_map,
       Solver::Summary* summary);

   // If the linear solver is of Schur type, then replace it with the
   // closest equivalent linear solver. This is done when the user
   // requested a Schur type solver but the problem structure makes it
   // impossible to use one.
   //
   // If the linear solver is not of Schur type, the function is a
   // no-op.
   static void AlternateLinearSolverForSchurTypeLinearSolver(
       Solver::Options* options);

   // Create a TripletSparseMatrix which contains the zero-one
   // structure corresponding to the block sparsity of the transpose of
   // the Jacobian matrix.
   //
   // Caller owns the result.
   static TripletSparseMatrix* CreateJacobianBlockSparsityTranspose(
       const Program* program);

   // Reorder the parameter blocks in program using the ordering
   static bool ApplyUserOrdering(
       const ProblemImpl::ParameterMap& parameter_map,
       const ParameterBlockOrdering* parameter_block_ordering,
       Program* program,
       string* error);

   // Sparse cholesky factorization routines when doing the sparse
   // cholesky factorization of the Jacobian matrix, reorders its
   // columns to reduce the fill-in. Compute this permutation and
   // re-order the parameter blocks.
   //
   // If the parameter_block_ordering contains more than one
   // elimination group and support for constrained fill-reducing
   // ordering is available in the sparse linear algebra library
   // (SuiteSparse version >= 4.2.0) then the fill reducing
   // ordering will take it into account, otherwise it will be ignored.
   static bool ReorderProgramForSparseNormalCholesky(
       const SparseLinearAlgebraLibraryType sparse_linear_algebra_library_type,
       const ParameterBlockOrdering* parameter_block_ordering,
       Program* program,
       string* error);

   // Schur type solvers require that all parameter blocks eliminated
   // by the Schur eliminator occur before others and the residuals be
   // sorted in lexicographic order of their parameter blocks.
   //
   // If the parameter_block_ordering only contains one elimination
   // group then a maximal independent set is computed and used as the
   // first elimination group, otherwise the user's ordering is used.
   //
   // If the linear solver type is SPARSE_SCHUR and support for
   // constrained fill-reducing ordering is available in the sparse
   // linear algebra library (SuiteSparse version >= 4.2.0) then
   // columns of the schur complement matrix are ordered to reduce the
   // fill-in the Cholesky factorization.
   //
   // Upon return, ordering contains the parameter block ordering that
   // was used to order the program.
   static bool ReorderProgramForSchurTypeLinearSolver(
       const LinearSolverType linear_solver_type,
       const SparseLinearAlgebraLibraryType sparse_linear_algebra_library_type,
       const ProblemImpl::ParameterMap& parameter_map,
       ParameterBlockOrdering* parameter_block_ordering,
       Program* program,
       string* error);
 };

 }  // namespace internal
 }  // namespace ceres

 #endif  // CERES_INTERNAL_SOLVER_IMPL_H_
	// Ceres Solver - A fast non-linear least squares minimizer
	// Copyright 2010, 2011, 2012 Google Inc. All rights reserved.
	// http://code.google.com/p/ceres-solver/
	//
	// Redistribution and use in source and binary forms, with or without
	// modification, are permitted provided that the following conditions are met:
	//
	// * Redistributions of source code must retain the above copyright notice,
	// this list of conditions and the following disclaimer.
	// * Redistributions in binary form must reproduce the above copyright notice,
	// this list of conditions and the following disclaimer in the documentation
	// and/or other materials provided with the distribution.
	// * Neither the name of Google Inc. nor the names of its contributors may be
	// used to endorse or promote products derived from this software without
	// specific prior written permission.
	//
	// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
	// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
	// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
	// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE
	// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
	// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
	// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
	// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
	// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
	// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
	// POSSIBILITY OF SUCH DAMAGE.
	//
	// Author: keir@google.com (Keir Mierle)

	#ifndef CERES_INTERNAL_SOLVER_IMPL_H_
	#define CERES_INTERNAL_SOLVER_IMPL_H_

	#include <set>
	#include <string>
	#include <vector>
	#include "ceres/internal/port.h"
	#include "ceres/ordered_groups.h"
	#include "ceres/problem_impl.h"
	#include "ceres/solver.h"

	namespace ceres {
	namespace internal {

	class CoordinateDescentMinimizer;
	class Evaluator;
	class LinearSolver;
	class Program;
	class TripletSparseMatrix;

	class SolverImpl {
	public:
	// Mirrors the interface in solver.h, but exposes implementation
	// details for testing internally.
	static void Solve(const Solver::Options& options,
	ProblemImpl* problem_impl,
	Solver::Summary* summary);

	static void TrustRegionSolve(const Solver::Options& options,
	ProblemImpl* problem_impl,
	Solver::Summary* summary);

	// Run the TrustRegionMinimizer for the given evaluator and configuration.
	static void TrustRegionMinimize(
	const Solver::Options &options,
	Program* program,
	CoordinateDescentMinimizer* inner_iteration_minimizer,
	Evaluator* evaluator,
	LinearSolver* linear_solver,
	double* parameters,
	Solver::Summary* summary);

	#ifndef CERES_NO_LINE_SEARCH_MINIMIZER
	static void LineSearchSolve(const Solver::Options& options,
	ProblemImpl* problem_impl,
	Solver::Summary* summary);

	// Run the LineSearchMinimizer for the given evaluator and configuration.
	static void LineSearchMinimize(const Solver::Options &options,
	Program* program,
	Evaluator* evaluator,
	double* parameters,
	Solver::Summary* summary);
	#endif // CERES_NO_LINE_SEARCH_MINIMIZER

	// Create the transformed Program, which has all the fixed blocks
	// and residuals eliminated, and in the case of automatic schur
	// ordering, has the E blocks first in the resulting program, with
	// options.num_eliminate_blocks set appropriately.
	//
	// If fixed_cost is not NULL, the residual blocks that are removed
	// are evaluated and the sum of their cost is returned in fixed_cost.
	static Program* CreateReducedProgram(Solver::Options* options,
	ProblemImpl* problem_impl,
	double* fixed_cost,
	string* error);

	// Create the appropriate linear solver, taking into account any
	// config changes decided by CreateTransformedProgram(). The
	// selected linear solver, which may be different from what the user
	// selected; consider the case that the remaining elimininated
	// blocks is zero after removing fixed blocks.
	static LinearSolver* CreateLinearSolver(Solver::Options* options,
	string* error);

	// Reorder the residuals for program, if necessary, so that the
	// residuals involving e block (i.e., the first num_eliminate_block
	// parameter blocks) occur together. This is a necessary condition
	// for the Schur eliminator.
	static bool LexicographicallyOrderResidualBlocks(
	const int num_eliminate_blocks,
	Program* program,
	string* error);

	// Create the appropriate evaluator for the transformed program.
	static Evaluator* CreateEvaluator(
	const Solver::Options& options,
	const ProblemImpl::ParameterMap& parameter_map,
	Program* program,
	string* error);

	// Remove the fixed or unused parameter blocks and residuals
	// depending only on fixed parameters from the problem. Also updates
	// num_eliminate_blocks, since removed parameters changes the point
	// at which the eliminated blocks is valid. If fixed_cost is not
	// NULL, the residual blocks that are removed are evaluated and the
	// sum of their cost is returned in fixed_cost.
	static bool RemoveFixedBlocksFromProgram(Program* program,
	ParameterBlockOrdering* ordering,
	double* fixed_cost,
	string* error);

	static bool IsOrderingValid(const Solver::Options& options,
	const ProblemImpl* problem_impl,
	string* error);

	static bool IsParameterBlockSetIndependent(
	const set<double*>& parameter_block_ptrs,
	const vector<ResidualBlock*>& residual_blocks);

	static CoordinateDescentMinimizer* CreateInnerIterationMinimizer(
	const Solver::Options& options,
	const Program& program,
	const ProblemImpl::ParameterMap& parameter_map,
	Solver::Summary* summary);

	// If the linear solver is of Schur type, then replace it with the
	// closest equivalent linear solver. This is done when the user
	// requested a Schur type solver but the problem structure makes it
	// impossible to use one.
	//
	// If the linear solver is not of Schur type, the function is a
	// no-op.
	static void AlternateLinearSolverForSchurTypeLinearSolver(
	Solver::Options* options);

	// Create a TripletSparseMatrix which contains the zero-one
	// structure corresponding to the block sparsity of the transpose of
	// the Jacobian matrix.
	//
	// Caller owns the result.
	static TripletSparseMatrix* CreateJacobianBlockSparsityTranspose(
	const Program* program);

	// Reorder the parameter blocks in program using the ordering
	static bool ApplyUserOrdering(
	const ProblemImpl::ParameterMap& parameter_map,
	const ParameterBlockOrdering* parameter_block_ordering,
	Program* program,
	string* error);

	// Sparse cholesky factorization routines when doing the sparse
	// cholesky factorization of the Jacobian matrix, reorders its
	// columns to reduce the fill-in. Compute this permutation and
	// re-order the parameter blocks.
	//
	// If the parameter_block_ordering contains more than one
	// elimination group and support for constrained fill-reducing
	// ordering is available in the sparse linear algebra library
	// (SuiteSparse version >= 4.2.0) then the fill reducing
	// ordering will take it into account, otherwise it will be ignored.
	static bool ReorderProgramForSparseNormalCholesky(
	const SparseLinearAlgebraLibraryType sparse_linear_algebra_library_type,
	const ParameterBlockOrdering* parameter_block_ordering,
	Program* program,
	string* error);

	// Schur type solvers require that all parameter blocks eliminated
	// by the Schur eliminator occur before others and the residuals be
	// sorted in lexicographic order of their parameter blocks.
	//
	// If the parameter_block_ordering only contains one elimination
	// group then a maximal independent set is computed and used as the
	// first elimination group, otherwise the user's ordering is used.
	//
	// If the linear solver type is SPARSE_SCHUR and support for
	// constrained fill-reducing ordering is available in the sparse
	// linear algebra library (SuiteSparse version >= 4.2.0) then
	// columns of the schur complement matrix are ordered to reduce the
	// fill-in the Cholesky factorization.
	//
	// Upon return, ordering contains the parameter block ordering that
	// was used to order the program.
	static bool ReorderProgramForSchurTypeLinearSolver(
	const LinearSolverType linear_solver_type,
	const SparseLinearAlgebraLibraryType sparse_linear_algebra_library_type,
	const ProblemImpl::ParameterMap& parameter_map,
	ParameterBlockOrdering* parameter_block_ordering,
	Program* program,
	string* error);
	};

	} // namespace internal
	} // namespace ceres

	#endif // CERES_INTERNAL_SOLVER_IMPL_H_