| 123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899100101102103104105106107108109110111112113114115116117118119120121122123124125126127128129130131132133134135136137138139140141142143144145146147 | // Ceres Solver - A fast non-linear least squares minimizer// Copyright 2018 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/port.h"#ifndef CERES_NO_ACCELERATE_SPARSE#include <memory>#include <string>#include <vector>#include "ceres/linear_solver.h"#include "ceres/sparse_cholesky.h"#include "Accelerate.h"namespace ceres {namespace internal {class CompressedRowSparseMatrix;class TripletSparseMatrix;template<typename Scalar>struct SparseTypesTrait {};template<>struct SparseTypesTrait<double> {  typedef DenseVector_Double DenseVector;  typedef SparseMatrix_Double SparseMatrix;  typedef SparseOpaqueSymbolicFactorization SymbolicFactorization;  typedef SparseOpaqueFactorization_Double NumericFactorization;};template<>struct SparseTypesTrait<float> {  typedef DenseVector_Float DenseVector;  typedef SparseMatrix_Float SparseMatrix;  typedef SparseOpaqueSymbolicFactorization SymbolicFactorization;  typedef SparseOpaqueFactorization_Float NumericFactorization;};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(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 : 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_;};}}#endif  // CERES_NO_ACCELERATE_SPARSE#endif  // CERES_INTERNAL_ACCELERATE_SPARSE_H_
 |