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