// Ceres Solver - A fast non-linear least squares minimizer // Copyright 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) #ifndef CERES_INTERNAL_LEVENBERG_MARQUARDT_STRATEGY_H_ #define CERES_INTERNAL_LEVENBERG_MARQUARDT_STRATEGY_H_ #include "ceres/internal/eigen.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 LevenbergMarquardtStrategy : public TrustRegionStrategy { public: explicit LevenbergMarquardtStrategy( const TrustRegionStrategy::Options& options); virtual ~LevenbergMarquardtStrategy(); // TrustRegionStrategy interface virtual TrustRegionStrategy::Summary ComputeStep( const TrustRegionStrategy::PerSolveOptions& per_solve_options, SparseMatrix* jacobian, const double* residuals, double* step); virtual void StepAccepted(double step_quality); virtual void StepRejected(double step_quality); virtual void StepIsInvalid() { // 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); } virtual double Radius() const; 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_ = diagonal_ / radius_; }; } // namespace internal } // namespace ceres #endif // CERES_INTERNAL_LEVENBERG_MARQUARDT_STRATEGY_H_