blob: 12cd463c1529c6b5c2317608a0e1269a71211348 [file] [log] [blame]
// Ceres Solver - A fast non-linear least squares minimizer
// Copyright 2015 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)
#ifndef CERES_INTERNAL_LEVENBERG_MARQUARDT_STRATEGY_H_
#define CERES_INTERNAL_LEVENBERG_MARQUARDT_STRATEGY_H_
#include "ceres/internal/eigen.h"
#include "ceres/internal/port.h"
#include "ceres/trust_region_strategy.h"
namespace ceres {
namespace internal {
// Levenberg-Marquardt step computation and trust region sizing
// strategy based on on "Methods for Nonlinear Least Squares" by
// K. Madsen, H.B. Nielsen and O. Tingleff. Available to download from
//
// http://www2.imm.dtu.dk/pubdb/views/edoc_download.php/3215/pdf/imm3215.pdf
class CERES_EXPORT_INTERNAL LevenbergMarquardtStrategy
: public TrustRegionStrategy {
public:
explicit LevenbergMarquardtStrategy(
const TrustRegionStrategy::Options& options);
virtual ~LevenbergMarquardtStrategy();
// TrustRegionStrategy interface
TrustRegionStrategy::Summary ComputeStep(
const TrustRegionStrategy::PerSolveOptions& per_solve_options,
SparseMatrix* jacobian,
const double* residuals,
double* step) final;
void StepAccepted(double step_quality) final;
void StepRejected(double step_quality) final;
void StepIsInvalid() final {
// Treat the current step as a rejected step with no increase in
// solution quality. Since rejected steps lead to decrease in the
// size of the trust region, the next time ComputeStep is called,
// this will lead to a better conditioned system.
StepRejected(0.0);
}
double Radius() const final;
private:
LinearSolver* linear_solver_;
double radius_;
double max_radius_;
const double min_diagonal_;
const double max_diagonal_;
double decrease_factor_;
bool reuse_diagonal_;
Vector diagonal_; // diagonal_ = diag(J'J)
// Scaled copy of diagonal_. Stored here as optimization to prevent
// allocations in every iteration and reuse when a step fails and
// ComputeStep is called again.
Vector lm_diagonal_; // lm_diagonal_ = sqrt(diagonal_ / radius_);
};
} // namespace internal
} // namespace ceres
#endif // CERES_INTERNAL_LEVENBERG_MARQUARDT_STRATEGY_H_