|  | // 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) | 
|  |  | 
|  | #include "ceres/gradient_problem_solver.h" | 
|  |  | 
|  | #include "ceres/callbacks.h" | 
|  | #include "ceres/gradient_problem.h" | 
|  | #include "ceres/gradient_problem_evaluator.h" | 
|  | #include "ceres/internal/eigen.h" | 
|  | #include "ceres/internal/port.h" | 
|  | #include "ceres/map_util.h" | 
|  | #include "ceres/minimizer.h" | 
|  | #include "ceres/solver.h" | 
|  | #include "ceres/solver_utils.h" | 
|  | #include "ceres/stringprintf.h" | 
|  | #include "ceres/types.h" | 
|  | #include "ceres/wall_time.h" | 
|  |  | 
|  | namespace ceres { | 
|  | using internal::StringPrintf; | 
|  | using internal::StringAppendF; | 
|  | using std::string; | 
|  |  | 
|  | namespace { | 
|  |  | 
|  | Solver::Options GradientProblemSolverOptionsToSolverOptions( | 
|  | const GradientProblemSolver::Options& options) { | 
|  | #define COPY_OPTION(x) solver_options.x = options.x | 
|  |  | 
|  | Solver::Options solver_options; | 
|  | solver_options.minimizer_type = LINE_SEARCH; | 
|  | COPY_OPTION(line_search_direction_type); | 
|  | COPY_OPTION(line_search_type); | 
|  | COPY_OPTION(nonlinear_conjugate_gradient_type); | 
|  | COPY_OPTION(max_lbfgs_rank); | 
|  | COPY_OPTION(use_approximate_eigenvalue_bfgs_scaling); | 
|  | COPY_OPTION(line_search_interpolation_type); | 
|  | COPY_OPTION(min_line_search_step_size); | 
|  | COPY_OPTION(line_search_sufficient_function_decrease); | 
|  | COPY_OPTION(max_line_search_step_contraction); | 
|  | COPY_OPTION(min_line_search_step_contraction); | 
|  | COPY_OPTION(max_num_line_search_step_size_iterations); | 
|  | COPY_OPTION(max_num_line_search_direction_restarts); | 
|  | COPY_OPTION(line_search_sufficient_curvature_decrease); | 
|  | COPY_OPTION(max_line_search_step_expansion); | 
|  | COPY_OPTION(max_num_iterations); | 
|  | COPY_OPTION(max_solver_time_in_seconds); | 
|  | COPY_OPTION(parameter_tolerance); | 
|  | COPY_OPTION(function_tolerance); | 
|  | COPY_OPTION(gradient_tolerance); | 
|  | COPY_OPTION(logging_type); | 
|  | COPY_OPTION(minimizer_progress_to_stdout); | 
|  | COPY_OPTION(callbacks); | 
|  | return solver_options; | 
|  | #undef COPY_OPTION | 
|  | } | 
|  |  | 
|  |  | 
|  | }  // namespace | 
|  |  | 
|  | bool GradientProblemSolver::Options::IsValid(std::string* error) const { | 
|  | const Solver::Options solver_options = | 
|  | GradientProblemSolverOptionsToSolverOptions(*this); | 
|  | return solver_options.IsValid(error); | 
|  | } | 
|  |  | 
|  | GradientProblemSolver::~GradientProblemSolver() { | 
|  | } | 
|  |  | 
|  | void GradientProblemSolver::Solve(const GradientProblemSolver::Options& options, | 
|  | const GradientProblem& problem, | 
|  | double* parameters_ptr, | 
|  | GradientProblemSolver::Summary* summary) { | 
|  | using internal::scoped_ptr; | 
|  | using internal::WallTimeInSeconds; | 
|  | using internal::Minimizer; | 
|  | using internal::GradientProblemEvaluator; | 
|  | using internal::LoggingCallback; | 
|  | using internal::SetSummaryFinalCost; | 
|  |  | 
|  | double start_time = WallTimeInSeconds(); | 
|  |  | 
|  | *CHECK_NOTNULL(summary) = Summary(); | 
|  | summary->num_parameters                    = problem.NumParameters(); | 
|  | summary->num_local_parameters              = problem.NumLocalParameters(); | 
|  | summary->line_search_direction_type        = options.line_search_direction_type;         //  NOLINT | 
|  | summary->line_search_interpolation_type    = options.line_search_interpolation_type;     //  NOLINT | 
|  | summary->line_search_type                  = options.line_search_type; | 
|  | summary->max_lbfgs_rank                    = options.max_lbfgs_rank; | 
|  | summary->nonlinear_conjugate_gradient_type = options.nonlinear_conjugate_gradient_type;  //  NOLINT | 
|  |  | 
|  | // Check validity | 
|  | if (!options.IsValid(&summary->message)) { | 
|  | LOG(ERROR) << "Terminating: " << summary->message; | 
|  | return; | 
|  | } | 
|  |  | 
|  | // TODO(sameeragarwal): This is a bit convoluted, we should be able | 
|  | // to convert to minimizer options directly, but this will do for | 
|  | // now. | 
|  | Minimizer::Options minimizer_options = | 
|  | Minimizer::Options(GradientProblemSolverOptionsToSolverOptions(options)); | 
|  | minimizer_options.evaluator.reset(new GradientProblemEvaluator(problem)); | 
|  |  | 
|  | scoped_ptr<IterationCallback> logging_callback; | 
|  | if (options.logging_type != SILENT) { | 
|  | logging_callback.reset( | 
|  | new LoggingCallback(LINE_SEARCH, options.minimizer_progress_to_stdout)); | 
|  | minimizer_options.callbacks.insert(minimizer_options.callbacks.begin(), | 
|  | logging_callback.get()); | 
|  | } | 
|  |  | 
|  | scoped_ptr<Minimizer> minimizer(Minimizer::Create(LINE_SEARCH)); | 
|  | Vector solution(problem.NumParameters()); | 
|  | VectorRef parameters(parameters_ptr, problem.NumParameters()); | 
|  | solution = parameters; | 
|  |  | 
|  | Solver::Summary solver_summary; | 
|  | solver_summary.fixed_cost = 0.0; | 
|  | solver_summary.preprocessor_time_in_seconds = 0.0; | 
|  | solver_summary.postprocessor_time_in_seconds = 0.0; | 
|  | solver_summary.line_search_polynomial_minimization_time_in_seconds = 0.0; | 
|  |  | 
|  | minimizer->Minimize(minimizer_options, solution.data(), &solver_summary); | 
|  |  | 
|  | summary->termination_type = solver_summary.termination_type; | 
|  | summary->message          = solver_summary.message; | 
|  | summary->initial_cost     = solver_summary.initial_cost; | 
|  | summary->final_cost       = solver_summary.final_cost; | 
|  | summary->iterations       = solver_summary.iterations; | 
|  | summary->line_search_polynomial_minimization_time_in_seconds = | 
|  | solver_summary.line_search_polynomial_minimization_time_in_seconds; | 
|  |  | 
|  | if (summary->IsSolutionUsable()) { | 
|  | parameters = solution; | 
|  | SetSummaryFinalCost(summary); | 
|  | } | 
|  |  | 
|  | const std::map<string, double>& evaluator_time_statistics = | 
|  | minimizer_options.evaluator->TimeStatistics(); | 
|  | summary->cost_evaluation_time_in_seconds = | 
|  | FindWithDefault(evaluator_time_statistics, "Evaluator::Residual", 0.0); | 
|  | summary->gradient_evaluation_time_in_seconds = | 
|  | FindWithDefault(evaluator_time_statistics, "Evaluator::Jacobian", 0.0); | 
|  |  | 
|  | summary->total_time_in_seconds = WallTimeInSeconds() - start_time; | 
|  | } | 
|  |  | 
|  | // Invalid values for most fields, to ensure that we are not | 
|  | // accidentally reporting default values. | 
|  | GradientProblemSolver::Summary::Summary() | 
|  | : termination_type(FAILURE), | 
|  | message("ceres::GradientProblemSolve was not called."), | 
|  | initial_cost(-1.0), | 
|  | final_cost(-1.0), | 
|  | total_time_in_seconds(-1.0), | 
|  | cost_evaluation_time_in_seconds(-1.0), | 
|  | gradient_evaluation_time_in_seconds(-1.0), | 
|  | line_search_polynomial_minimization_time_in_seconds(-1.0), | 
|  | num_parameters(-1), | 
|  | num_local_parameters(-1), | 
|  | line_search_direction_type(LBFGS), | 
|  | line_search_type(ARMIJO), | 
|  | line_search_interpolation_type(BISECTION), | 
|  | nonlinear_conjugate_gradient_type(FLETCHER_REEVES), | 
|  | max_lbfgs_rank(-1) { | 
|  | } | 
|  |  | 
|  | bool GradientProblemSolver::Summary::IsSolutionUsable() const { | 
|  | return internal::IsSolutionUsable(*this); | 
|  | } | 
|  |  | 
|  | string GradientProblemSolver::Summary::BriefReport() const { | 
|  | return StringPrintf("Ceres GradientProblemSolver Report: " | 
|  | "Iterations: %d, " | 
|  | "Initial cost: %e, " | 
|  | "Final cost: %e, " | 
|  | "Termination: %s", | 
|  | static_cast<int>(iterations.size()), | 
|  | initial_cost, | 
|  | final_cost, | 
|  | TerminationTypeToString(termination_type)); | 
|  | } | 
|  |  | 
|  | string GradientProblemSolver::Summary::FullReport() const { | 
|  | using internal::VersionString; | 
|  |  | 
|  | string report = string("\nSolver Summary (v " + VersionString() + ")\n\n"); | 
|  |  | 
|  | StringAppendF(&report, "Parameters          % 25d\n", num_parameters); | 
|  | if (num_local_parameters != num_parameters) { | 
|  | StringAppendF(&report, "Local parameters    % 25d\n", | 
|  | num_local_parameters); | 
|  | } | 
|  |  | 
|  | string line_search_direction_string; | 
|  | if (line_search_direction_type == LBFGS) { | 
|  | line_search_direction_string = StringPrintf("LBFGS (%d)", max_lbfgs_rank); | 
|  | } else if (line_search_direction_type == NONLINEAR_CONJUGATE_GRADIENT) { | 
|  | line_search_direction_string = | 
|  | NonlinearConjugateGradientTypeToString( | 
|  | nonlinear_conjugate_gradient_type); | 
|  | } else { | 
|  | line_search_direction_string = | 
|  | LineSearchDirectionTypeToString(line_search_direction_type); | 
|  | } | 
|  |  | 
|  | StringAppendF(&report, "Line search direction     %19s\n", | 
|  | line_search_direction_string.c_str()); | 
|  |  | 
|  | const string line_search_type_string = | 
|  | StringPrintf("%s %s", | 
|  | LineSearchInterpolationTypeToString( | 
|  | line_search_interpolation_type), | 
|  | LineSearchTypeToString(line_search_type)); | 
|  | StringAppendF(&report, "Line search type          %19s\n", | 
|  | line_search_type_string.c_str()); | 
|  | StringAppendF(&report, "\n"); | 
|  |  | 
|  | StringAppendF(&report, "\nCost:\n"); | 
|  | StringAppendF(&report, "Initial        % 30e\n", initial_cost); | 
|  | if (termination_type != FAILURE && | 
|  | termination_type != USER_FAILURE) { | 
|  | StringAppendF(&report, "Final          % 30e\n", final_cost); | 
|  | StringAppendF(&report, "Change         % 30e\n", | 
|  | initial_cost - final_cost); | 
|  | } | 
|  |  | 
|  | StringAppendF(&report, "\nMinimizer iterations         % 16d\n", | 
|  | static_cast<int>(iterations.size())); | 
|  |  | 
|  | StringAppendF(&report, "\nTime (in seconds):\n"); | 
|  |  | 
|  | StringAppendF(&report, "\n  Cost evaluation     %23.4f\n", | 
|  | cost_evaluation_time_in_seconds); | 
|  | StringAppendF(&report, "  Gradient evaluation %23.4f\n", | 
|  | gradient_evaluation_time_in_seconds); | 
|  | StringAppendF(&report, "  Polynomial minimization   %17.4f\n", | 
|  | line_search_polynomial_minimization_time_in_seconds); | 
|  |  | 
|  | StringAppendF(&report, "Total               %25.4f\n\n", | 
|  | total_time_in_seconds); | 
|  |  | 
|  | StringAppendF(&report, "Termination:        %25s (%s)\n", | 
|  | TerminationTypeToString(termination_type), message.c_str()); | 
|  | return report; | 
|  | } | 
|  |  | 
|  | void Solve(const GradientProblemSolver::Options& options, | 
|  | const GradientProblem& problem, | 
|  | double* parameters, | 
|  | GradientProblemSolver::Summary* summary) { | 
|  | GradientProblemSolver solver; | 
|  | solver.Solve(options, problem, parameters, summary); | 
|  | } | 
|  |  | 
|  | }  // namespace ceres |