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// Ceres Solver - A fast non-linear least squares minimizer
// Copyright 2010, 2011, 2012 Google Inc. All rights reserved.
// http://code.google.com/p/ceres-solver/
//
// 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/iterative_schur_complement_solver.h"
#include <algorithm>
#include <cstring>
#include <vector>
#include "Eigen/Dense"
#include "ceres/block_sparse_matrix.h"
#include "ceres/block_structure.h"
#include "ceres/conjugate_gradients_solver.h"
#include "ceres/implicit_schur_complement.h"
#include "ceres/internal/eigen.h"
#include "ceres/internal/scoped_ptr.h"
#include "ceres/linear_solver.h"
#include "ceres/preconditioner.h"
#include "ceres/schur_jacobi_preconditioner.h"
#include "ceres/triplet_sparse_matrix.h"
#include "ceres/types.h"
#include "ceres/visibility_based_preconditioner.h"
#include "ceres/wall_time.h"
#include "glog/logging.h"
namespace ceres {
namespace internal {
IterativeSchurComplementSolver::IterativeSchurComplementSolver(
const LinearSolver::Options& options)
: options_(options) {
}
IterativeSchurComplementSolver::~IterativeSchurComplementSolver() {
}
LinearSolver::Summary IterativeSchurComplementSolver::SolveImpl(
BlockSparseMatrix* A,
const double* b,
const LinearSolver::PerSolveOptions& per_solve_options,
double* x) {
EventLogger event_logger("IterativeSchurComplementSolver::Solve");
CHECK_NOTNULL(A->block_structure());
// Initialize a ImplicitSchurComplement object.
if (schur_complement_ == NULL) {
schur_complement_.reset(
new ImplicitSchurComplement(options_.elimination_groups[0],
options_.preconditioner_type == JACOBI));
}
schur_complement_->Init(*A, per_solve_options.D, b);
const int num_schur_complement_blocks =
A->block_structure()->cols.size() - options_.elimination_groups[0];
if (num_schur_complement_blocks == 0) {
VLOG(2) << "No parameter blocks left in the schur complement.";
LinearSolver::Summary cg_summary;
cg_summary.num_iterations = 0;
cg_summary.termination_type = TOLERANCE;
schur_complement_->BackSubstitute(NULL, x);
return cg_summary;
}
// Initialize the solution to the Schur complement system to zero.
//
// TODO(sameeragarwal): There maybe a better initialization than an
// all zeros solution. Explore other cheap starting points.
reduced_linear_system_solution_.resize(schur_complement_->num_rows());
reduced_linear_system_solution_.setZero();
// Instantiate a conjugate gradient solver that runs on the Schur complement
// matrix with the block diagonal of the matrix F'F as the preconditioner.
LinearSolver::Options cg_options;
cg_options.max_num_iterations = options_.max_num_iterations;
ConjugateGradientsSolver cg_solver(cg_options);
LinearSolver::PerSolveOptions cg_per_solve_options;
cg_per_solve_options.r_tolerance = per_solve_options.r_tolerance;
cg_per_solve_options.q_tolerance = per_solve_options.q_tolerance;
Preconditioner::Options preconditioner_options;
preconditioner_options.type = options_.preconditioner_type;
preconditioner_options.sparse_linear_algebra_library_type =
options_.sparse_linear_algebra_library_type;
preconditioner_options.num_threads = options_.num_threads;
preconditioner_options.row_block_size = options_.row_block_size;
preconditioner_options.e_block_size = options_.e_block_size;
preconditioner_options.f_block_size = options_.f_block_size;
preconditioner_options.elimination_groups = options_.elimination_groups;
switch (options_.preconditioner_type) {
case IDENTITY:
break;
case JACOBI:
preconditioner_.reset(
new SparseMatrixPreconditionerWrapper(
schur_complement_->block_diagonal_FtF_inverse()));
break;
case SCHUR_JACOBI:
if (preconditioner_.get() == NULL) {
preconditioner_.reset(
new SchurJacobiPreconditioner(*A->block_structure(),
preconditioner_options));
}
break;
case CLUSTER_JACOBI:
case CLUSTER_TRIDIAGONAL:
if (preconditioner_.get() == NULL) {
preconditioner_.reset(
new VisibilityBasedPreconditioner(*A->block_structure(),
preconditioner_options));
}
break;
default:
LOG(FATAL) << "Unknown Preconditioner Type";
}
bool preconditioner_update_was_successful = true;
if (preconditioner_.get() != NULL) {
preconditioner_update_was_successful =
preconditioner_->Update(*A, per_solve_options.D);
cg_per_solve_options.preconditioner = preconditioner_.get();
}
event_logger.AddEvent("Setup");
LinearSolver::Summary cg_summary;
cg_summary.num_iterations = 0;
cg_summary.termination_type = FAILURE;
if (preconditioner_update_was_successful) {
cg_summary = cg_solver.Solve(schur_complement_.get(),
schur_complement_->rhs().data(),
cg_per_solve_options,
reduced_linear_system_solution_.data());
if (cg_summary.termination_type != FAILURE) {
schur_complement_->BackSubstitute(
reduced_linear_system_solution_.data(), x);
}
}
VLOG(2) << "CG Iterations : " << cg_summary.num_iterations;
event_logger.AddEvent("Solve");
return cg_summary;
}
} // namespace internal
} // namespace ceres
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