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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: alexs.mac@gmail.com (Alex Stewart)
- #ifndef CERES_INTERNAL_ACCELERATE_SPARSE_H_
- #define CERES_INTERNAL_ACCELERATE_SPARSE_H_
- // This include must come before any #ifndef check on Ceres compile options.
- #include "ceres/internal/config.h"
- #ifndef CERES_NO_ACCELERATE_SPARSE
- #include <memory>
- #include <string>
- #include <vector>
- #include "Accelerate.h"
- #include "ceres/linear_solver.h"
- #include "ceres/sparse_cholesky.h"
- namespace ceres {
- namespace internal {
- class CompressedRowSparseMatrix;
- class TripletSparseMatrix;
- template <typename Scalar>
- struct SparseTypesTrait {};
- template <>
- struct SparseTypesTrait<double> {
- using DenseVector = DenseVector_Double;
- using SparseMatrix = SparseMatrix_Double;
- using SymbolicFactorization = SparseOpaqueSymbolicFactorization;
- using NumericFactorization = SparseOpaqueFactorization_Double;
- };
- template <>
- struct SparseTypesTrait<float> {
- using DenseVector = DenseVector_Float;
- using SparseMatrix = SparseMatrix_Float;
- using SymbolicFactorization = SparseOpaqueSymbolicFactorization;
- using NumericFactorization = SparseOpaqueFactorization_Float;
- };
- template <typename Scalar>
- class AccelerateSparse {
- public:
- using DenseVector = typename SparseTypesTrait<Scalar>::DenseVector;
- // Use ASSparseMatrix to avoid collision with ceres::internal::SparseMatrix.
- using ASSparseMatrix = typename SparseTypesTrait<Scalar>::SparseMatrix;
- using SymbolicFactorization =
- typename SparseTypesTrait<Scalar>::SymbolicFactorization;
- using NumericFactorization =
- typename SparseTypesTrait<Scalar>::NumericFactorization;
- // Solves a linear system given its symbolic (reference counted within
- // NumericFactorization) and numeric factorization.
- void Solve(NumericFactorization* numeric_factor,
- DenseVector* rhs_and_solution);
- // Note: Accelerate's API passes/returns its objects by value, but as the
- // objects contain pointers to the underlying data these copies are
- // all shallow (in some cases Accelerate also reference counts the
- // objects internally).
- ASSparseMatrix CreateSparseMatrixTransposeView(CompressedRowSparseMatrix* A);
- // Computes a symbolic factorisation of A that can be used in Solve().
- SymbolicFactorization AnalyzeCholesky(OrderingType ordering_type,
- ASSparseMatrix* A);
- // Compute the numeric Cholesky factorization of A, given its
- // symbolic factorization.
- NumericFactorization Cholesky(ASSparseMatrix* A,
- SymbolicFactorization* symbolic_factor);
- // Reuse the NumericFactorization from a previous matrix with the same
- // symbolic factorization to represent a new numeric factorization.
- void Cholesky(ASSparseMatrix* A, NumericFactorization* numeric_factor);
- private:
- std::vector<long> column_starts_;
- std::vector<uint8_t> solve_workspace_;
- std::vector<uint8_t> factorization_workspace_;
- // Storage for the values of A if Scalar != double (necessitating a copy).
- Eigen::Matrix<Scalar, Eigen::Dynamic, 1> values_;
- };
- // An implementation of SparseCholesky interface using Apple's Accelerate
- // framework.
- template <typename Scalar>
- class AppleAccelerateCholesky final : public SparseCholesky {
- public:
- // Factory
- static std::unique_ptr<SparseCholesky> Create(OrderingType ordering_type);
- // SparseCholesky interface.
- virtual ~AppleAccelerateCholesky();
- CompressedRowSparseMatrix::StorageType StorageType() const;
- LinearSolverTerminationType Factorize(CompressedRowSparseMatrix* lhs,
- std::string* message) final;
- LinearSolverTerminationType Solve(const double* rhs,
- double* solution,
- std::string* message) final;
- private:
- AppleAccelerateCholesky(const OrderingType ordering_type);
- void FreeSymbolicFactorization();
- void FreeNumericFactorization();
- const OrderingType ordering_type_;
- AccelerateSparse<Scalar> as_;
- std::unique_ptr<typename AccelerateSparse<Scalar>::SymbolicFactorization>
- symbolic_factor_;
- std::unique_ptr<typename AccelerateSparse<Scalar>::NumericFactorization>
- numeric_factor_;
- // Copy of rhs/solution if Scalar != double (necessitating a copy).
- Eigen::Matrix<Scalar, Eigen::Dynamic, 1> scalar_rhs_and_solution_;
- };
- } // namespace internal
- } // namespace ceres
- #endif // CERES_NO_ACCELERATE_SPARSE
- #endif // CERES_INTERNAL_ACCELERATE_SPARSE_H_
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