diff options
Diffstat (limited to 'extern/ceres/internal/ceres/schur_complement_solver.h')
| -rw-r--r-- | extern/ceres/internal/ceres/schur_complement_solver.h | 102 |
1 files changed, 35 insertions, 67 deletions
diff --git a/extern/ceres/internal/ceres/schur_complement_solver.h b/extern/ceres/internal/ceres/schur_complement_solver.h index 714dafc5b0c..87f04785794 100644 --- a/extern/ceres/internal/ceres/schur_complement_solver.h +++ b/extern/ceres/internal/ceres/schur_complement_solver.h @@ -31,22 +31,19 @@ #ifndef CERES_INTERNAL_SCHUR_COMPLEMENT_SOLVER_H_ #define CERES_INTERNAL_SCHUR_COMPLEMENT_SOLVER_H_ +#include <memory> #include <set> #include <utility> #include <vector> -#include "ceres/internal/port.h" - +#include "ceres/block_random_access_diagonal_matrix.h" #include "ceres/block_random_access_matrix.h" #include "ceres/block_sparse_matrix.h" #include "ceres/block_structure.h" -#include "ceres/cxsparse.h" +#include "ceres/internal/port.h" #include "ceres/linear_solver.h" #include "ceres/schur_eliminator.h" -#include "ceres/suitesparse.h" -#include "ceres/internal/scoped_ptr.h" #include "ceres/types.h" -#include "ceres/block_random_access_diagonal_matrix.h" #ifdef CERES_USE_EIGEN_SPARSE #include "Eigen/SparseCholesky" @@ -57,6 +54,7 @@ namespace ceres { namespace internal { class BlockSparseMatrix; +class SparseCholesky; // Base class for Schur complement based linear least squares // solvers. It assumes that the input linear system Ax = b can be @@ -96,33 +94,37 @@ class BlockSparseMatrix; // be used for problems with upto a few hundred cameras. // // SparseSchurComplementSolver: For problems where the Schur -// complement matrix is large and sparse. It requires that -// CHOLMOD/SuiteSparse be installed, as it uses CHOLMOD to find a -// sparse Cholesky factorization of the Schur complement. This solver -// can be used for solving structure from motion problems with tens of -// thousands of cameras, though depending on the exact sparsity -// structure, it maybe better to use an iterative solver. +// complement matrix is large and sparse. It requires that Ceres be +// build with at least one sparse linear algebra library, as it +// computes a sparse Cholesky factorization of the Schur complement. +// +// This solver can be used for solving structure from motion problems +// with tens of thousands of cameras, though depending on the exact +// sparsity structure, it maybe better to use an iterative solver. // // The two solvers can be instantiated by calling // LinearSolver::CreateLinearSolver with LinearSolver::Options::type // set to DENSE_SCHUR and SPARSE_SCHUR -// respectively. LinearSolver::Options::elimination_groups[0] should be -// at least 1. +// respectively. LinearSolver::Options::elimination_groups[0] should +// be at least 1. class SchurComplementSolver : public BlockSparseMatrixSolver { public: explicit SchurComplementSolver(const LinearSolver::Options& options) : options_(options) { CHECK_GT(options.elimination_groups.size(), 1); CHECK_GT(options.elimination_groups[0], 0); + CHECK(options.context != NULL); } + SchurComplementSolver(const SchurComplementSolver&) = delete; + void operator=(const SchurComplementSolver&) = delete; // LinearSolver methods virtual ~SchurComplementSolver() {} - virtual LinearSolver::Summary SolveImpl( + LinearSolver::Summary SolveImpl( BlockSparseMatrix* A, const double* b, const LinearSolver::PerSolveOptions& per_solve_options, - double* x); + double* x) override; protected: const LinearSolver::Options& options() const { return options_; } @@ -140,11 +142,9 @@ class SchurComplementSolver : public BlockSparseMatrixSolver { LinearSolver::Options options_; - scoped_ptr<SchurEliminatorBase> eliminator_; - scoped_ptr<BlockRandomAccessMatrix> lhs_; - scoped_array<double> rhs_; - - CERES_DISALLOW_COPY_AND_ASSIGN(SchurComplementSolver); + std::unique_ptr<SchurEliminatorBase> eliminator_; + std::unique_ptr<BlockRandomAccessMatrix> lhs_; + std::unique_ptr<double[]> rhs_; }; // Dense Cholesky factorization based solver. @@ -152,72 +152,40 @@ class DenseSchurComplementSolver : public SchurComplementSolver { public: explicit DenseSchurComplementSolver(const LinearSolver::Options& options) : SchurComplementSolver(options) {} + DenseSchurComplementSolver(const DenseSchurComplementSolver&) = delete; + void operator=(const DenseSchurComplementSolver&) = delete; + virtual ~DenseSchurComplementSolver() {} private: - virtual void InitStorage(const CompressedRowBlockStructure* bs); - virtual LinearSolver::Summary SolveReducedLinearSystem( + void InitStorage(const CompressedRowBlockStructure* bs) final; + LinearSolver::Summary SolveReducedLinearSystem( const LinearSolver::PerSolveOptions& per_solve_options, - double* solution); - - CERES_DISALLOW_COPY_AND_ASSIGN(DenseSchurComplementSolver); + double* solution) final; }; // Sparse Cholesky factorization based solver. class SparseSchurComplementSolver : public SchurComplementSolver { public: explicit SparseSchurComplementSolver(const LinearSolver::Options& options); + SparseSchurComplementSolver(const SparseSchurComplementSolver&) = delete; + void operator=(const SparseSchurComplementSolver&) = delete; + virtual ~SparseSchurComplementSolver(); private: - virtual void InitStorage(const CompressedRowBlockStructure* bs); - virtual LinearSolver::Summary SolveReducedLinearSystem( - const LinearSolver::PerSolveOptions& per_solve_options, - double* solution); - LinearSolver::Summary SolveReducedLinearSystemUsingSuiteSparse( + void InitStorage(const CompressedRowBlockStructure* bs) final; + LinearSolver::Summary SolveReducedLinearSystem( const LinearSolver::PerSolveOptions& per_solve_options, - double* solution); - LinearSolver::Summary SolveReducedLinearSystemUsingCXSparse( - const LinearSolver::PerSolveOptions& per_solve_options, - double* solution); - LinearSolver::Summary SolveReducedLinearSystemUsingEigen( - const LinearSolver::PerSolveOptions& per_solve_options, - double* solution); + double* solution) final; LinearSolver::Summary SolveReducedLinearSystemUsingConjugateGradients( const LinearSolver::PerSolveOptions& per_solve_options, double* solution); // Size of the blocks in the Schur complement. std::vector<int> blocks_; - - SuiteSparse ss_; - // Symbolic factorization of the reduced linear system. Precomputed - // once and reused in subsequent calls. - cholmod_factor* factor_; - - CXSparse cxsparse_; - // Cached factorization - cs_dis* cxsparse_factor_; - -#ifdef CERES_USE_EIGEN_SPARSE - - // The preprocessor gymnastics here are dealing with the fact that - // before version 3.2.2, Eigen did not support a third template - // parameter to specify the ordering. -#if EIGEN_VERSION_AT_LEAST(3,2,2) - typedef Eigen::SimplicialLDLT<Eigen::SparseMatrix<double>, Eigen::Lower, - Eigen::NaturalOrdering<int> > - SimplicialLDLT; -#else - typedef Eigen::SimplicialLDLT<Eigen::SparseMatrix<double>, Eigen::Lower> - SimplicialLDLT; -#endif - - scoped_ptr<SimplicialLDLT> simplicial_ldlt_; -#endif - - scoped_ptr<BlockRandomAccessDiagonalMatrix> preconditioner_; - CERES_DISALLOW_COPY_AND_ASSIGN(SparseSchurComplementSolver); + std::unique_ptr<SparseCholesky> sparse_cholesky_; + std::unique_ptr<BlockRandomAccessDiagonalMatrix> preconditioner_; }; } // namespace internal |