| // Ceres Solver - A fast non-linear least squares minimizer | 
 | // Copyright 2017 Google Inc. All rights reserved. | 
 | // http://ceres-solver.org/ | 
 | // | 
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 | // | 
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 | // POSSIBILITY OF SUCH DAMAGE. | 
 | // | 
 | // Author: sameeragarwal@google.com (Sameer Agarwal) | 
 |  | 
 | #include "ceres/subset_preconditioner.h" | 
 |  | 
 | #include <memory> | 
 | #include <string> | 
 | #include "ceres/compressed_row_sparse_matrix.h" | 
 | #include "ceres/inner_product_computer.h" | 
 | #include "ceres/linear_solver.h" | 
 | #include "ceres/sparse_cholesky.h" | 
 | #include "ceres/types.h" | 
 |  | 
 | namespace ceres { | 
 | namespace internal { | 
 |  | 
 | SubsetPreconditioner::SubsetPreconditioner( | 
 |     const Preconditioner::Options& options, const BlockSparseMatrix& A) | 
 |     : options_(options), num_cols_(A.num_cols()) { | 
 |   CHECK_GE(options_.subset_preconditioner_start_row_block, 0) | 
 |       << "Congratulations, you found a bug in Ceres. Please report it."; | 
 |  | 
 |   LinearSolver::Options sparse_cholesky_options; | 
 |   sparse_cholesky_options.sparse_linear_algebra_library_type = | 
 |       options_.sparse_linear_algebra_library_type; | 
 |   sparse_cholesky_options.use_postordering = | 
 |       options_.use_postordering; | 
 |   sparse_cholesky_ = SparseCholesky::Create(sparse_cholesky_options); | 
 | } | 
 |  | 
 | SubsetPreconditioner::~SubsetPreconditioner() {} | 
 |  | 
 | void SubsetPreconditioner::RightMultiply(const double* x, double* y) const { | 
 |   CHECK(x != nullptr); | 
 |   CHECK(y != nullptr); | 
 |   std::string message; | 
 |   sparse_cholesky_->Solve(x, y, &message); | 
 | } | 
 |  | 
 | bool SubsetPreconditioner::UpdateImpl(const BlockSparseMatrix& A, | 
 |                                       const double* D) { | 
 |   BlockSparseMatrix* m = const_cast<BlockSparseMatrix*>(&A); | 
 |   const CompressedRowBlockStructure* bs = m->block_structure(); | 
 |  | 
 |   // A = [P] | 
 |   //     [Q] | 
 |  | 
 |   // Now add D to A if needed. | 
 |   if (D != NULL) { | 
 |     // A = [P] | 
 |     //     [Q] | 
 |     //     [D] | 
 |     std::unique_ptr<BlockSparseMatrix> regularizer( | 
 |         BlockSparseMatrix::CreateDiagonalMatrix(D, bs->cols)); | 
 |     m->AppendRows(*regularizer); | 
 |   } | 
 |  | 
 |   if (inner_product_computer_.get() == NULL) { | 
 |     inner_product_computer_.reset(InnerProductComputer::Create( | 
 |         *m, | 
 |         options_.subset_preconditioner_start_row_block, | 
 |         bs->rows.size(), | 
 |         sparse_cholesky_->StorageType())); | 
 |   } | 
 |  | 
 |   // Compute inner_product = [Q'*Q + D'*D] | 
 |   inner_product_computer_->Compute(); | 
 |  | 
 |   // Unappend D if needed. | 
 |   if (D != NULL) { | 
 |     // A = [P] | 
 |     //     [Q] | 
 |     m->DeleteRowBlocks(bs->cols.size()); | 
 |   } | 
 |  | 
 |   std::string message; | 
 |   // Compute L. s.t., LL' = Q'*Q + D'*D | 
 |   const LinearSolverTerminationType termination_type = | 
 |       sparse_cholesky_->Factorize(inner_product_computer_->mutable_result(), | 
 |                                   &message); | 
 |   if (termination_type != LINEAR_SOLVER_SUCCESS) { | 
 |     LOG(ERROR) << "Preconditioner factorization failed: " << message; | 
 |     return false; | 
 |   } | 
 |  | 
 |   return true; | 
 | } | 
 |  | 
 | }  // namespace internal | 
 | }  // namespace ceres |