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// Ceres Solver - A fast non-linear least squares minimizer
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// Copyright 2010, 2011, 2012 Google Inc. All rights reserved.
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// http://code.google.com/p/ceres-solver/
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// Redistribution and use in source and binary forms, with or without
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// modification, are permitted provided that the following conditions are met:
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// * Redistributions of source code must retain the above copyright notice,
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// this list of conditions and the following disclaimer.
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// * Redistributions in binary form must reproduce the above copyright notice,
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// this list of conditions and the following disclaimer in the documentation
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// and/or other materials provided with the distribution.
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// * Neither the name of Google Inc. nor the names of its contributors may be
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// used to endorse or promote products derived from this software without
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// specific prior written permission.
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// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
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// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
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// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
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// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE
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// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
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// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
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// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
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// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
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// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
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// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
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// POSSIBILITY OF SUCH DAMAGE.
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// Author: sameeragarwal@google.com (Sameer Agarwal)
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#include "ceres/iterative_schur_complement_solver.h"
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#include <glog/logging.h>
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#include "Eigen/Dense"
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#include "ceres/block_sparse_matrix.h"
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#include "ceres/block_structure.h"
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#include "ceres/conjugate_gradients_solver.h"
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#include "ceres/implicit_schur_complement.h"
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#include "ceres/internal/eigen.h"
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#include "ceres/internal/scoped_ptr.h"
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#include "ceres/linear_solver.h"
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#include "ceres/triplet_sparse_matrix.h"
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#include "ceres/types.h"
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#include "ceres/visibility_based_preconditioner.h"
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IterativeSchurComplementSolver::IterativeSchurComplementSolver(
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const LinearSolver::Options& options)
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IterativeSchurComplementSolver::~IterativeSchurComplementSolver() {
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LinearSolver::Summary IterativeSchurComplementSolver::SolveImpl(
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BlockSparseMatrixBase* A,
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const LinearSolver::PerSolveOptions& per_solve_options,
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CHECK_NOTNULL(A->block_structure());
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// Initialize a ImplicitSchurComplement object.
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if (schur_complement_ == NULL) {
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schur_complement_.reset(
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new ImplicitSchurComplement(options_.num_eliminate_blocks,
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options_.preconditioner_type == JACOBI));
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schur_complement_->Init(*A, per_solve_options.D, b);
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// Initialize the solution to the Schur complement system to zero.
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// TODO(sameeragarwal): There maybe a better initialization than an
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// all zeros solution. Explore other cheap starting points.
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reduced_linear_system_solution_.resize(schur_complement_->num_rows());
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reduced_linear_system_solution_.setZero();
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// Instantiate a conjugate gradient solver that runs on the Schur complement
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// matrix with the block diagonal of the matrix F'F as the preconditioner.
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LinearSolver::Options cg_options;
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cg_options.max_num_iterations = options_.max_num_iterations;
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ConjugateGradientsSolver cg_solver(cg_options);
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LinearSolver::PerSolveOptions cg_per_solve_options;
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cg_per_solve_options.r_tolerance = per_solve_options.r_tolerance;
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cg_per_solve_options.q_tolerance = per_solve_options.q_tolerance;
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bool is_preconditioner_good = false;
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switch (options_.preconditioner_type) {
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is_preconditioner_good = true;
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// We need to strip the constness of the block_diagonal_FtF_inverse
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// matrix here because the only other way to initialize the struct
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// cg_solve_options would be to add a constructor to it. We know
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// that the only method ever called on the preconditioner is the
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// RightMultiply which is a const method so we don't need to worry
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// about the object getting modified.
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cg_per_solve_options.preconditioner =
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const_cast<BlockSparseMatrix*>(
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schur_complement_->block_diagonal_FtF_inverse());
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is_preconditioner_good = true;
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case CLUSTER_TRIDIAGONAL:
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if (visibility_based_preconditioner_.get() == NULL) {
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visibility_based_preconditioner_.reset(
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new VisibilityBasedPreconditioner(*A->block_structure(), options_));
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is_preconditioner_good =
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visibility_based_preconditioner_->Update(*A, per_solve_options.D);
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cg_per_solve_options.preconditioner =
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visibility_based_preconditioner_.get();
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LOG(FATAL) << "Unknown Preconditioner Type";
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LinearSolver::Summary cg_summary;
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cg_summary.num_iterations = 0;
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cg_summary.termination_type = FAILURE;
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if (is_preconditioner_good) {
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cg_summary = cg_solver.Solve(schur_complement_.get(),
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schur_complement_->rhs().data(),
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cg_per_solve_options,
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reduced_linear_system_solution_.data());
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if (cg_summary.termination_type != FAILURE) {
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schur_complement_->BackSubstitute(
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reduced_linear_system_solution_.data(), x);
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VLOG(2) << "CG Iterations : " << cg_summary.num_iterations;
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} // namespace internal
added
removed
internal/ceres/iterative_schur_complement_solver.cc
