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+// Ceres Solver - A fast non-linear least squares minimizer
+// Copyright 2016 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_MINIMIZER_H_
+#define CERES_INTERNAL_TRUST_REGION_MINIMIZER_H_
+
+#include <memory>
+#include "ceres/internal/eigen.h"
+#include "ceres/minimizer.h"
+#include "ceres/solver.h"
+#include "ceres/sparse_matrix.h"
+#include "ceres/trust_region_step_evaluator.h"
+#include "ceres/trust_region_strategy.h"
+#include "ceres/types.h"
+
+namespace ceres {
+namespace internal {
+
+// Generic trust region minimization algorithm.
+//
+// For example usage, see SolverImpl::Minimize.
+class TrustRegionMinimizer : public Minimizer {
+ public:
+ ~TrustRegionMinimizer();
+
+ // This method is not thread safe.
+ virtual void Minimize(const Minimizer::Options& options,
+ double* parameters,
+ Solver::Summary* solver_summary);
+
+ private:
+ void Init(const Minimizer::Options& options,
+ double* parameters,
+ Solver::Summary* solver_summary);
+ bool IterationZero();
+ bool FinalizeIterationAndCheckIfMinimizerCanContinue();
+ bool ComputeTrustRegionStep();
+
+ bool EvaluateGradientAndJacobian(bool new_evaluation_point);
+ void ComputeCandidatePointAndEvaluateCost();
+
+ void DoLineSearch(const Vector& x,
+ const Vector& gradient,
+ const double cost,
+ Vector* delta);
+ void DoInnerIterationsIfNeeded();
+
+ bool ParameterToleranceReached();
+ bool FunctionToleranceReached();
+ bool GradientToleranceReached();
+ bool MaxSolverTimeReached();
+ bool MaxSolverIterationsReached();
+ bool MinTrustRegionRadiusReached();
+
+ bool IsStepSuccessful();
+ void HandleUnsuccessfulStep();
+ bool HandleSuccessfulStep();
+ bool HandleInvalidStep();
+
+ Minimizer::Options options_;
+
+ // These pointers are shortcuts to objects passed to the
+ // TrustRegionMinimizer. The TrustRegionMinimizer does not own them.
+ double* parameters_;
+ Solver::Summary* solver_summary_;
+ Evaluator* evaluator_;
+ SparseMatrix* jacobian_;
+ TrustRegionStrategy* strategy_;
+
+ std::unique_ptr<TrustRegionStepEvaluator> step_evaluator_;
+
+ bool is_not_silent_;
+ bool inner_iterations_are_enabled_;
+ bool inner_iterations_were_useful_;
+
+ // Summary of the current iteration.
+ IterationSummary iteration_summary_;
+
+ // Dimensionality of the problem in the ambient space.
+ int num_parameters_;
+ // Dimensionality of the problem in the tangent space. This is the
+ // number of columns in the Jacobian.
+ int num_effective_parameters_;
+ // Length of the residual vector, also the number of rows in the Jacobian.
+ int num_residuals_;
+
+ // Current point.
+ Vector x_;
+ // Residuals at x_;
+ Vector residuals_;
+ // Gradient at x_.
+ Vector gradient_;
+ // Solution computed by the inner iterations.
+ Vector inner_iteration_x_;
+ // model_residuals = J * trust_region_step
+ Vector model_residuals_;
+ Vector negative_gradient_;
+ // projected_gradient_step = Plus(x, -gradient), an intermediate
+ // quantity used to compute the projected gradient norm.
+ Vector projected_gradient_step_;
+ // The step computed by the trust region strategy. If Jacobi scaling
+ // is enabled, this is a vector in the scaled space.
+ Vector trust_region_step_;
+ // The current proposal for how far the trust region algorithm
+ // thinks we should move. In the most basic case, it is just the
+ // trust_region_step_ with the Jacobi scaling undone. If bounds
+ // constraints are present, then it is the result of the projected
+ // line search.
+ Vector delta_;
+ // candidate_x = Plus(x, delta)
+ Vector candidate_x_;
+ // Scaling vector to scale the columns of the Jacobian.
+ Vector jacobian_scaling_;
+
+ // Euclidean norm of x_.
+ double x_norm_;
+ // Cost at x_.
+ double x_cost_;
+ // Minimum cost encountered up till now.
+ double minimum_cost_;
+ // How much did the trust region strategy reduce the cost of the
+ // linearized Gauss-Newton model.
+ double model_cost_change_;
+ // Cost at candidate_x_.
+ double candidate_cost_;
+
+ // Time at which the minimizer was started.
+ double start_time_in_secs_;
+ // Time at which the current iteration was started.
+ double iteration_start_time_in_secs_;
+ // Number of consecutive steps where the minimizer loop computed a
+ // numerically invalid step.
+ int num_consecutive_invalid_steps_;
+};
+
+} // namespace internal
+} // namespace ceres
+
+#endif // CERES_INTERNAL_TRUST_REGION_MINIMIZER_H_