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- // Ceres Solver - A fast non-linear least squares minimizer
- // Copyright 2023 Google Inc. All rights reserved.
- // http://ceres-solver.org/
- //
- // 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: sameeragarwal@google.com (Sameer Agarwal)
- #ifndef CERES_INTERNAL_SPARSE_CHOLESKY_H_
- #define CERES_INTERNAL_SPARSE_CHOLESKY_H_
- // This include must come before any #ifndef check on Ceres compile options.
- // clang-format off
- #include "ceres/internal/config.h"
- // clang-format on
- #include <memory>
- #include "ceres/internal/disable_warnings.h"
- #include "ceres/internal/export.h"
- #include "ceres/linear_solver.h"
- #include "glog/logging.h"
- namespace ceres::internal {
- // An interface that abstracts away the internal details of various
- // sparse linear algebra libraries and offers a simple API for solving
- // symmetric positive definite linear systems using a sparse Cholesky
- // factorization.
- //
- // Instances of SparseCholesky are expected to cache the symbolic
- // factorization of the linear system. They do this on the first call
- // to Factorize or FactorAndSolve. Subsequent calls to Factorize and
- // FactorAndSolve are expected to have the same sparsity structure.
- //
- // Example usage:
- //
- // std::unique_ptr<SparseCholesky>
- // sparse_cholesky(SparseCholesky::Create(SUITE_SPARSE, AMD));
- //
- // CompressedRowSparseMatrix lhs = ...;
- // std::string message;
- // CHECK_EQ(sparse_cholesky->Factorize(&lhs, &message),
- // LinearSolverTerminationType::SUCCESS);
- // Vector rhs = ...;
- // Vector solution = ...;
- // CHECK_EQ(sparse_cholesky->Solve(rhs.data(), solution.data(), &message),
- // LinearSolverTerminationType::SUCCESS);
- class CERES_NO_EXPORT SparseCholesky {
- public:
- static std::unique_ptr<SparseCholesky> Create(
- const LinearSolver::Options& options);
- virtual ~SparseCholesky();
- // Due to the symmetry of the linear system, sparse linear algebra
- // libraries only use one half of the input matrix. Whether it is
- // the upper or the lower triangular part of the matrix depends on
- // the library and the re-ordering strategy being used. This
- // function tells the user the storage type expected of the input
- // matrix for the sparse linear algebra library and reordering
- // strategy used.
- virtual CompressedRowSparseMatrix::StorageType StorageType() const = 0;
- // Computes the numeric factorization of the given matrix. If this
- // is the first call to Factorize, first the symbolic factorization
- // will be computed and cached and the numeric factorization will be
- // computed based on that.
- //
- // Subsequent calls to Factorize will use that symbolic
- // factorization assuming that the sparsity of the matrix has
- // remained constant.
- virtual LinearSolverTerminationType Factorize(CompressedRowSparseMatrix* lhs,
- std::string* message) = 0;
- // Computes the solution to the equation
- //
- // lhs * solution = rhs
- virtual LinearSolverTerminationType Solve(const double* rhs,
- double* solution,
- std::string* message) = 0;
- // Convenience method which combines a call to Factorize and
- // Solve. Solve is only called if Factorize returns
- // LinearSolverTerminationType::SUCCESS.
- LinearSolverTerminationType FactorAndSolve(CompressedRowSparseMatrix* lhs,
- const double* rhs,
- double* solution,
- std::string* message);
- };
- class SparseIterativeRefiner;
- // Computes an initial solution using the given instance of
- // SparseCholesky, and then refines it using the SparseIterativeRefiner.
- class CERES_NO_EXPORT RefinedSparseCholesky final : public SparseCholesky {
- public:
- RefinedSparseCholesky(
- std::unique_ptr<SparseCholesky> sparse_cholesky,
- std::unique_ptr<SparseIterativeRefiner> iterative_refiner);
- ~RefinedSparseCholesky() override;
- CompressedRowSparseMatrix::StorageType StorageType() const override;
- LinearSolverTerminationType Factorize(CompressedRowSparseMatrix* lhs,
- std::string* message) override;
- LinearSolverTerminationType Solve(const double* rhs,
- double* solution,
- std::string* message) override;
- private:
- std::unique_ptr<SparseCholesky> sparse_cholesky_;
- std::unique_ptr<SparseIterativeRefiner> iterative_refiner_;
- CompressedRowSparseMatrix* lhs_ = nullptr;
- };
- } // namespace ceres::internal
- #include "ceres/internal/reenable_warnings.h"
- #endif // CERES_INTERNAL_SPARSE_CHOLESKY_H_
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