| // Ceres Solver - A fast non-linear least squares minimizer | 
 | // Copyright 2015 Google Inc. All rights reserved. | 
 | // http://ceres-solver.org/ | 
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 | // Author: sameeragarwal@google.com (Sameer Agarwal) | 
 |  | 
 | #ifndef CERES_INTERNAL_TRUST_REGION_STRATEGY_H_ | 
 | #define CERES_INTERNAL_TRUST_REGION_STRATEGY_H_ | 
 |  | 
 | #include <string> | 
 | #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 { | 
 |     Options() | 
 |         : trust_region_strategy_type(LEVENBERG_MARQUARDT), | 
 |           initial_radius(1e4), | 
 |           max_radius(1e32), | 
 |           min_lm_diagonal(1e-6), | 
 |           max_lm_diagonal(1e32), | 
 |           dogleg_type(TRADITIONAL_DOGLEG) { | 
 |     } | 
 |  | 
 |     TrustRegionStrategyType trust_region_strategy_type; | 
 |     // Linear solver used for actually solving the trust region step. | 
 |     LinearSolver* linear_solver; | 
 |     double initial_radius; | 
 |     double max_radius; | 
 |  | 
 |     // 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; | 
 |     double max_lm_diagonal; | 
 |  | 
 |     // Further specify which dogleg method to use | 
 |     DoglegType dogleg_type; | 
 |   }; | 
 |  | 
 |   // Per solve options. | 
 |   struct PerSolveOptions { | 
 |     PerSolveOptions() | 
 |         : eta(0), | 
 |           dump_format_type(TEXTFILE) { | 
 |     } | 
 |  | 
 |     // Forcing sequence for inexact solves. | 
 |     double eta; | 
 |  | 
 |     DumpFormatType dump_format_type; | 
 |  | 
 |     // 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 { | 
 |     Summary() | 
 |         : residual_norm(0.0), | 
 |           num_iterations(-1), | 
 |           termination_type(LINEAR_SOLVER_FAILURE) { | 
 |     } | 
 |  | 
 |     // If the trust region problem is, | 
 |     // | 
 |     //   1/2 x'Ax + b'x + c, | 
 |     // | 
 |     // then | 
 |     // | 
 |     //   residual_norm = |Ax -b| | 
 |     double residual_norm; | 
 |  | 
 |     // 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; | 
 |  | 
 |     // Status of the linear solver used to solve the Newton system. | 
 |     LinearSolverTerminationType termination_type; | 
 |   }; | 
 |  | 
 |   virtual ~TrustRegionStrategy(); | 
 |  | 
 |   // 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; | 
 |  | 
 |   // Factory. | 
 |   static TrustRegionStrategy* Create(const Options& options); | 
 | }; | 
 |  | 
 | }  // namespace internal | 
 | }  // namespace ceres | 
 |  | 
 | #endif  // CERES_INTERNAL_TRUST_REGION_STRATEGY_H_ |