// 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_TRUST_REGION_STRATEGY_H_ #define CERES_INTERNAL_TRUST_REGION_STRATEGY_H_ #include #include "ceres/internal/port.h" #include "ceres/linear_solver.h" namespace ceres { namespace internal { class LinearSolver; class SparseMatrix; // Interface for classes implementing various trust region strategies // for nonlinear least squares problems. // // The object is expected to maintain and update a trust region // radius, which it then uses to solve for the trust region step using // the jacobian matrix and residual vector. // // Here the term trust region radius is used loosely, as the strategy // is free to treat it as guidance and violate it as need be. e.g., // the LevenbergMarquardtStrategy uses the inverse of the trust region // radius to scale the damping term, which controls the step size, but // does not set a hard limit on its size. class TrustRegionStrategy { public: struct Options { TrustRegionStrategyType trust_region_strategy_type = LEVENBERG_MARQUARDT; // Linear solver used for actually solving the trust region step. LinearSolver* linear_solver = nullptr; double initial_radius = 1e4; double max_radius = 1e32; // Minimum and maximum values of the diagonal damping matrix used // by LevenbergMarquardtStrategy. The DoglegStrategy also uses // these bounds to construct a regularizing diagonal to ensure // that the Gauss-Newton step computation is of full rank. double min_lm_diagonal = 1e-6; double max_lm_diagonal = 1e32; // Further specify which dogleg method to use DoglegType dogleg_type = TRADITIONAL_DOGLEG; }; // Factory. static TrustRegionStrategy* Create(const Options& options); virtual ~TrustRegionStrategy(); // Per solve options. struct PerSolveOptions { // Forcing sequence for inexact solves. double eta = 1e-1; DumpFormatType dump_format_type = TEXTFILE; // If non-empty and dump_format_type is not CONSOLE, the trust // regions strategy will write the linear system to file(s) with // name starting with dump_filename_base. If dump_format_type is // CONSOLE then dump_filename_base will be ignored and the linear // system will be written to the standard error. std::string dump_filename_base; }; struct Summary { // If the trust region problem is, // // 1/2 x'Ax + b'x + c, // // then // // residual_norm = |Ax -b| double residual_norm = -1; // Number of iterations used by the linear solver. If a linear // solver was not called (e.g., DogLegStrategy after an // unsuccessful step), then this would be zero. int num_iterations = -1; // Status of the linear solver used to solve the Newton system. LinearSolverTerminationType termination_type = LINEAR_SOLVER_FAILURE; }; // Use the current radius to solve for the trust region step. virtual Summary ComputeStep(const PerSolveOptions& per_solve_options, SparseMatrix* jacobian, const double* residuals, double* step) = 0; // Inform the strategy that the current step has been accepted, and // that the ratio of the decrease in the non-linear objective to the // decrease in the trust region model is step_quality. virtual void StepAccepted(double step_quality) = 0; // Inform the strategy that the current step has been rejected, and // that the ratio of the decrease in the non-linear objective to the // decrease in the trust region model is step_quality. virtual void StepRejected(double step_quality) = 0; // Inform the strategy that the current step has been rejected // because it was found to be numerically invalid. // StepRejected/StepAccepted will not be called for this step, and // the strategy is free to do what it wants with this information. virtual void StepIsInvalid() = 0; // Current trust region radius. virtual double Radius() const = 0; }; } // namespace internal } // namespace ceres #endif // CERES_INTERNAL_TRUST_REGION_STRATEGY_H_