| 123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899100101102103104105106107108109110111112113114115116117118119120121122123124125126127128129130131132133134135136137138139140141142143144145146147148149150151152153154155156157158159160161162 | // Ceres Solver - A fast non-linear least squares minimizer// Copyright 2017 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)#include "ceres/sparse_cholesky.h"#include "ceres/accelerate_sparse.h"#include "ceres/cxsparse.h"#include "ceres/eigensparse.h"#include "ceres/float_cxsparse.h"#include "ceres/float_suitesparse.h"#include "ceres/iterative_refiner.h"#include "ceres/suitesparse.h"namespace ceres {namespace internal {std::unique_ptr<SparseCholesky> SparseCholesky::Create(    const LinearSolver::Options& options) {  const OrderingType ordering_type = options.use_postordering ? AMD : NATURAL;  std::unique_ptr<SparseCholesky> sparse_cholesky;  switch (options.sparse_linear_algebra_library_type) {    case SUITE_SPARSE:#ifndef CERES_NO_SUITESPARSE      if (options.use_mixed_precision_solves) {        sparse_cholesky = FloatSuiteSparseCholesky::Create(ordering_type);      } else {        sparse_cholesky = SuiteSparseCholesky::Create(ordering_type);      }      break;#else      LOG(FATAL) << "Ceres was compiled without support for SuiteSparse.";#endif    case EIGEN_SPARSE:#ifdef CERES_USE_EIGEN_SPARSE      if (options.use_mixed_precision_solves) {        sparse_cholesky = FloatEigenSparseCholesky::Create(ordering_type);      } else {        sparse_cholesky = EigenSparseCholesky::Create(ordering_type);      }      break;#else      LOG(FATAL) << "Ceres was compiled without support for "                 << "Eigen's sparse Cholesky factorization routines.";#endif    case CX_SPARSE:#ifndef CERES_NO_CXSPARSE      if (options.use_mixed_precision_solves) {        sparse_cholesky = FloatCXSparseCholesky::Create(ordering_type);      } else {        sparse_cholesky = CXSparseCholesky::Create(ordering_type);      }      break;#else      LOG(FATAL) << "Ceres was compiled without support for CXSparse.";#endif    case ACCELERATE_SPARSE:#ifndef CERES_NO_ACCELERATE_SPARSE      if (options.use_mixed_precision_solves) {        sparse_cholesky = AppleAccelerateCholesky<float>::Create(ordering_type);      } else {        sparse_cholesky = AppleAccelerateCholesky<double>::Create(ordering_type);      }      break;#else      LOG(FATAL) << "Ceres was compiled without support for Apple's Accelerate "                 << "framework solvers.";#endif    default:      LOG(FATAL) << "Unknown sparse linear algebra library type : "                 << SparseLinearAlgebraLibraryTypeToString(                        options.sparse_linear_algebra_library_type);  }  if (options.max_num_refinement_iterations > 0) {    std::unique_ptr<IterativeRefiner> refiner(        new IterativeRefiner(options.max_num_refinement_iterations));    sparse_cholesky = std::unique_ptr<SparseCholesky>(new RefinedSparseCholesky(        std::move(sparse_cholesky), std::move(refiner)));  }  return sparse_cholesky;}SparseCholesky::~SparseCholesky() {}LinearSolverTerminationType SparseCholesky::FactorAndSolve(    CompressedRowSparseMatrix* lhs,    const double* rhs,    double* solution,    std::string* message) {  LinearSolverTerminationType termination_type = Factorize(lhs, message);  if (termination_type == LINEAR_SOLVER_SUCCESS) {    termination_type = Solve(rhs, solution, message);  }  return termination_type;}RefinedSparseCholesky::RefinedSparseCholesky(    std::unique_ptr<SparseCholesky> sparse_cholesky,    std::unique_ptr<IterativeRefiner> iterative_refiner)    : sparse_cholesky_(std::move(sparse_cholesky)),      iterative_refiner_(std::move(iterative_refiner)) {}RefinedSparseCholesky::~RefinedSparseCholesky() {}CompressedRowSparseMatrix::StorageType RefinedSparseCholesky::StorageType()    const {  return sparse_cholesky_->StorageType();}LinearSolverTerminationType RefinedSparseCholesky::Factorize(    CompressedRowSparseMatrix* lhs, std::string* message) {  lhs_ = lhs;  return sparse_cholesky_->Factorize(lhs, message);}LinearSolverTerminationType RefinedSparseCholesky::Solve(const double* rhs,                                                         double* solution,                                                         std::string* message) {  CHECK(lhs_ != nullptr);  auto termination_type = sparse_cholesky_->Solve(rhs, solution, message);  if (termination_type != LINEAR_SOLVER_SUCCESS) {    return termination_type;  }  iterative_refiner_->Refine(*lhs_, rhs, sparse_cholesky_.get(), solution);  return LINEAR_SOLVER_SUCCESS;}}  // namespace internal}  // namespace ceres
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