Squashed 'third_party/ceres/' content from commit e51e9b4
Change-Id: I763587619d57e594d3fa158dc3a7fe0b89a1743b
git-subtree-dir: third_party/ceres
git-subtree-split: e51e9b46f6ca88ab8b2266d0e362771db6d98067
diff --git a/internal/ceres/subset_preconditioner.cc b/internal/ceres/subset_preconditioner.cc
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+// 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/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);
+ 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