| // Ceres Solver - A fast non-linear least squares minimizer |
| // Copyright 2014 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: keir@google.com (Keir Mierle) |
| // sameeragarwal@google.com (Sameer Agarwal) |
| |
| #include "ceres/internal/port.h" |
| #include "ceres/solver.h" |
| |
| #include <sstream> // NOLINT |
| #include <vector> |
| |
| #include "ceres/problem.h" |
| #include "ceres/problem_impl.h" |
| #include "ceres/program.h" |
| #include "ceres/solver_impl.h" |
| #include "ceres/stringprintf.h" |
| #include "ceres/types.h" |
| #include "ceres/version.h" |
| #include "ceres/wall_time.h" |
| |
| namespace ceres { |
| namespace { |
| |
| #define OPTION_OP(x, y, OP) \ |
| if (!(options.x OP y)) { \ |
| std::stringstream ss; \ |
| ss << "Invalid configuration. "; \ |
| ss << string("Solver::Options::" #x " = ") << options.x << ". "; \ |
| ss << "Violated constraint: "; \ |
| ss << string("Solver::Options::" #x " " #OP " "#y); \ |
| *error = ss.str(); \ |
| return false; \ |
| } |
| |
| #define OPTION_OP_OPTION(x, y, OP) \ |
| if (!(options.x OP options.y)) { \ |
| std::stringstream ss; \ |
| ss << "Invalid configuration. "; \ |
| ss << string("Solver::Options::" #x " = ") << options.x << ". "; \ |
| ss << string("Solver::Options::" #y " = ") << options.y << ". "; \ |
| ss << "Violated constraint: "; \ |
| ss << string("Solver::Options::" #x ); \ |
| ss << string(#OP " Solver::Options::" #y "."); \ |
| *error = ss.str(); \ |
| return false; \ |
| } |
| |
| #define OPTION_GE(x, y) OPTION_OP(x, y, >=); |
| #define OPTION_GT(x, y) OPTION_OP(x, y, >); |
| #define OPTION_LE(x, y) OPTION_OP(x, y, <=); |
| #define OPTION_LT(x, y) OPTION_OP(x, y, <); |
| #define OPTION_LE_OPTION(x, y) OPTION_OP_OPTION(x ,y, <=) |
| #define OPTION_LT_OPTION(x, y) OPTION_OP_OPTION(x ,y, <) |
| |
| bool CommonOptionsAreValid(const Solver::Options& options, string* error) { |
| OPTION_GE(max_num_iterations, 0); |
| OPTION_GE(max_solver_time_in_seconds, 0.0); |
| OPTION_GE(function_tolerance, 0.0); |
| OPTION_GE(gradient_tolerance, 0.0); |
| OPTION_GE(parameter_tolerance, 0.0); |
| OPTION_GT(num_threads, 0); |
| OPTION_GT(num_linear_solver_threads, 0); |
| if (options.check_gradients) { |
| OPTION_GT(gradient_check_relative_precision, 0.0); |
| OPTION_GT(numeric_derivative_relative_step_size, 0.0); |
| } |
| return true; |
| } |
| |
| bool TrustRegionOptionsAreValid(const Solver::Options& options, string* error) { |
| OPTION_GT(initial_trust_region_radius, 0.0); |
| OPTION_GT(min_trust_region_radius, 0.0); |
| OPTION_GT(max_trust_region_radius, 0.0); |
| OPTION_LE_OPTION(min_trust_region_radius, max_trust_region_radius); |
| OPTION_LE_OPTION(min_trust_region_radius, initial_trust_region_radius); |
| OPTION_LE_OPTION(initial_trust_region_radius, max_trust_region_radius); |
| OPTION_GE(min_relative_decrease, 0.0); |
| OPTION_GE(min_lm_diagonal, 0.0); |
| OPTION_GE(max_lm_diagonal, 0.0); |
| OPTION_LE_OPTION(min_lm_diagonal, max_lm_diagonal); |
| OPTION_GE(max_num_consecutive_invalid_steps, 0); |
| OPTION_GT(eta, 0.0); |
| OPTION_GE(min_linear_solver_iterations, 1); |
| OPTION_GE(max_linear_solver_iterations, 1); |
| OPTION_LE_OPTION(min_linear_solver_iterations, max_linear_solver_iterations); |
| |
| if (options.use_inner_iterations) { |
| OPTION_GE(inner_iteration_tolerance, 0.0); |
| } |
| |
| if (options.use_nonmonotonic_steps) { |
| OPTION_GT(max_consecutive_nonmonotonic_steps, 0); |
| } |
| |
| if (options.preconditioner_type == CLUSTER_JACOBI && |
| options.sparse_linear_algebra_library_type != SUITE_SPARSE) { |
| *error = "CLUSTER_JACOBI requires " |
| "Solver::Options::sparse_linear_algebra_library_type to be " |
| "SUITE_SPARSE"; |
| return false; |
| } |
| |
| if (options.preconditioner_type == CLUSTER_TRIDIAGONAL && |
| options.sparse_linear_algebra_library_type != SUITE_SPARSE) { |
| *error = "CLUSTER_TRIDIAGONAL requires " |
| "Solver::Options::sparse_linear_algebra_library_type to be " |
| "SUITE_SPARSE"; |
| return false; |
| } |
| |
| #ifdef CERES_NO_LAPACK |
| if (options.dense_linear_algebra_library_type == LAPACK) { |
| if (options.linear_solver_type == DENSE_NORMAL_CHOLESKY) { |
| *error = "Can't use DENSE_NORMAL_CHOLESKY with LAPACK because " |
| "LAPACK was not enabled when Ceres was built."; |
| return false; |
| } |
| |
| if (options.linear_solver_type == DENSE_QR) { |
| *error = "Can't use DENSE_QR with LAPACK because " |
| "LAPACK was not enabled when Ceres was built."; |
| return false; |
| } |
| |
| if (options.linear_solver_type == DENSE_SCHUR) { |
| *error = "Can't use DENSE_SCHUR with LAPACK because " |
| "LAPACK was not enabled when Ceres was built."; |
| return false; |
| } |
| } |
| #endif |
| |
| #ifdef CERES_NO_SUITESPARSE |
| if (options.sparse_linear_algebra_library_type == SUITE_SPARSE) { |
| if (options.linear_solver_type == SPARSE_NORMAL_CHOLESKY) { |
| *error = "Can't use SPARSE_NORMAL_CHOLESKY with SUITESPARSE because " |
| "SuiteSparse was not enabled when Ceres was built."; |
| return false; |
| } |
| |
| if (options.linear_solver_type == SPARSE_SCHUR) { |
| *error = "Can't use SPARSE_SCHUR with SUITESPARSE because " |
| "SuiteSparse was not enabled when Ceres was built."; |
| return false; |
| } |
| |
| if (options.preconditioner_type == CLUSTER_JACOBI) { |
| *error = "CLUSTER_JACOBI preconditioner not supported. " |
| "SuiteSparse was not enabled when Ceres was built."; |
| return false; |
| } |
| |
| if (options.preconditioner_type == CLUSTER_TRIDIAGONAL) { |
| *error = "CLUSTER_TRIDIAGONAL preconditioner not supported. " |
| "SuiteSparse was not enabled when Ceres was built."; |
| return false; |
| } |
| } |
| #endif |
| |
| #ifdef CERES_NO_CXSPARSE |
| if (options.sparse_linear_algebra_library_type == CX_SPARSE) { |
| if (options.linear_solver_type == SPARSE_NORMAL_CHOLESKY) { |
| *error = "Can't use SPARSE_NORMAL_CHOLESKY with CX_SPARSE because " |
| "CXSparse was not enabled when Ceres was built."; |
| return false; |
| } |
| |
| if (options.linear_solver_type == SPARSE_SCHUR) { |
| *error = "Can't use SPARSE_SCHUR with CX_SPARSE because " |
| "CXSparse was not enabled when Ceres was built."; |
| return false; |
| } |
| } |
| #endif |
| |
| if (options.trust_region_strategy_type == DOGLEG) { |
| if (options.linear_solver_type == ITERATIVE_SCHUR || |
| options.linear_solver_type == CGNR) { |
| *error = "DOGLEG only supports exact factorization based linear " |
| "solvers. If you want to use an iterative solver please " |
| "use LEVENBERG_MARQUARDT as the trust_region_strategy_type"; |
| return false; |
| } |
| } |
| |
| if (options.trust_region_minimizer_iterations_to_dump.size() > 0 && |
| options.trust_region_problem_dump_format_type != CONSOLE && |
| options.trust_region_problem_dump_directory.empty()) { |
| *error = "Solver::Options::trust_region_problem_dump_directory is empty."; |
| return false; |
| } |
| |
| if (options.dynamic_sparsity && |
| options.linear_solver_type != SPARSE_NORMAL_CHOLESKY) { |
| *error = "Dynamic sparsity is only supported with SPARSE_NORMAL_CHOLESKY."; |
| return false; |
| } |
| |
| return true; |
| } |
| |
| bool LineSearchOptionsAreValid(const Solver::Options& options, string* error) { |
| OPTION_GT(max_lbfgs_rank, 0); |
| OPTION_GT(min_line_search_step_size, 0.0); |
| OPTION_GT(max_line_search_step_contraction, 0.0); |
| OPTION_LT(max_line_search_step_contraction, 1.0); |
| OPTION_LT_OPTION(max_line_search_step_contraction, |
| min_line_search_step_contraction); |
| OPTION_LE(min_line_search_step_contraction, 1.0); |
| OPTION_GT(max_num_line_search_step_size_iterations, 0); |
| OPTION_GT(line_search_sufficient_function_decrease, 0.0); |
| OPTION_LT_OPTION(line_search_sufficient_function_decrease, |
| line_search_sufficient_curvature_decrease); |
| OPTION_LT(line_search_sufficient_curvature_decrease, 1.0); |
| OPTION_GT(max_line_search_step_expansion, 1.0); |
| |
| if ((options.line_search_direction_type == ceres::BFGS || |
| options.line_search_direction_type == ceres::LBFGS) && |
| options.line_search_type != ceres::WOLFE) { |
| |
| *error = |
| string("Invalid configuration: Solver::Options::line_search_type = ") |
| + string(LineSearchTypeToString(options.line_search_type)) |
| + string(". When using (L)BFGS, " |
| "Solver::Options::line_search_type must be set to WOLFE."); |
| return false; |
| } |
| |
| // Warn user if they have requested BISECTION interpolation, but constraints |
| // on max/min step size change during line search prevent bisection scaling |
| // from occurring. Warn only, as this is likely a user mistake, but one which |
| // does not prevent us from continuing. |
| LOG_IF(WARNING, |
| (options.line_search_interpolation_type == ceres::BISECTION && |
| (options.max_line_search_step_contraction > 0.5 || |
| options.min_line_search_step_contraction < 0.5))) |
| << "Line search interpolation type is BISECTION, but specified " |
| << "max_line_search_step_contraction: " |
| << options.max_line_search_step_contraction << ", and " |
| << "min_line_search_step_contraction: " |
| << options.min_line_search_step_contraction |
| << ", prevent bisection (0.5) scaling, continuing with solve regardless."; |
| |
| return true; |
| } |
| |
| #undef OPTION_OP |
| #undef OPTION_OP_OPTION |
| #undef OPTION_GT |
| #undef OPTION_GE |
| #undef OPTION_LE |
| #undef OPTION_LT |
| #undef OPTION_LE_OPTION |
| #undef OPTION_LT_OPTION |
| |
| void StringifyOrdering(const vector<int>& ordering, string* report) { |
| if (ordering.size() == 0) { |
| internal::StringAppendF(report, "AUTOMATIC"); |
| return; |
| } |
| |
| for (int i = 0; i < ordering.size() - 1; ++i) { |
| internal::StringAppendF(report, "%d, ", ordering[i]); |
| } |
| internal::StringAppendF(report, "%d", ordering.back()); |
| } |
| |
| } // namespace |
| |
| bool Solver::Options::IsValid(string* error) const { |
| if (!CommonOptionsAreValid(*this, error)) { |
| return false; |
| } |
| |
| if (minimizer_type == TRUST_REGION) { |
| return TrustRegionOptionsAreValid(*this, error); |
| } |
| |
| CHECK_EQ(minimizer_type, LINE_SEARCH); |
| return LineSearchOptionsAreValid(*this, error); |
| } |
| |
| Solver::~Solver() {} |
| |
| void Solver::Solve(const Solver::Options& options, |
| Problem* problem, |
| Solver::Summary* summary) { |
| double start_time_seconds = internal::WallTimeInSeconds(); |
| CHECK_NOTNULL(problem); |
| CHECK_NOTNULL(summary); |
| |
| *summary = Summary(); |
| if (!options.IsValid(&summary->message)) { |
| LOG(ERROR) << "Terminating: " << summary->message; |
| return; |
| } |
| |
| internal::ProblemImpl* problem_impl = problem->problem_impl_.get(); |
| internal::SolverImpl::Solve(options, problem_impl, summary); |
| summary->total_time_in_seconds = |
| internal::WallTimeInSeconds() - start_time_seconds; |
| } |
| |
| void Solve(const Solver::Options& options, |
| Problem* problem, |
| Solver::Summary* summary) { |
| Solver solver; |
| solver.Solve(options, problem, summary); |
| } |
| |
| Solver::Summary::Summary() |
| // Invalid values for most fields, to ensure that we are not |
| // accidentally reporting default values. |
| : minimizer_type(TRUST_REGION), |
| termination_type(FAILURE), |
| message("ceres::Solve was not called."), |
| initial_cost(-1.0), |
| final_cost(-1.0), |
| fixed_cost(-1.0), |
| num_successful_steps(-1), |
| num_unsuccessful_steps(-1), |
| num_inner_iteration_steps(-1), |
| preprocessor_time_in_seconds(-1.0), |
| minimizer_time_in_seconds(-1.0), |
| postprocessor_time_in_seconds(-1.0), |
| total_time_in_seconds(-1.0), |
| linear_solver_time_in_seconds(-1.0), |
| residual_evaluation_time_in_seconds(-1.0), |
| jacobian_evaluation_time_in_seconds(-1.0), |
| inner_iteration_time_in_seconds(-1.0), |
| num_parameter_blocks(-1), |
| num_parameters(-1), |
| num_effective_parameters(-1), |
| num_residual_blocks(-1), |
| num_residuals(-1), |
| num_parameter_blocks_reduced(-1), |
| num_parameters_reduced(-1), |
| num_effective_parameters_reduced(-1), |
| num_residual_blocks_reduced(-1), |
| num_residuals_reduced(-1), |
| num_threads_given(-1), |
| num_threads_used(-1), |
| num_linear_solver_threads_given(-1), |
| num_linear_solver_threads_used(-1), |
| linear_solver_type_given(SPARSE_NORMAL_CHOLESKY), |
| linear_solver_type_used(SPARSE_NORMAL_CHOLESKY), |
| inner_iterations_given(false), |
| inner_iterations_used(false), |
| preconditioner_type(IDENTITY), |
| visibility_clustering_type(CANONICAL_VIEWS), |
| trust_region_strategy_type(LEVENBERG_MARQUARDT), |
| dense_linear_algebra_library_type(EIGEN), |
| sparse_linear_algebra_library_type(SUITE_SPARSE), |
| line_search_direction_type(LBFGS), |
| line_search_type(ARMIJO), |
| line_search_interpolation_type(BISECTION), |
| nonlinear_conjugate_gradient_type(FLETCHER_REEVES), |
| max_lbfgs_rank(-1) { |
| } |
| |
| using internal::StringAppendF; |
| using internal::StringPrintf; |
| |
| string Solver::Summary::BriefReport() const { |
| return StringPrintf("Ceres Solver Report: " |
| "Iterations: %d, " |
| "Initial cost: %e, " |
| "Final cost: %e, " |
| "Termination: %s", |
| num_successful_steps + num_unsuccessful_steps, |
| initial_cost, |
| final_cost, |
| TerminationTypeToString(termination_type)); |
| }; |
| |
| string Solver::Summary::FullReport() const { |
| string report = |
| "\n" |
| "Ceres Solver v" CERES_VERSION_STRING " Solve Report\n" |
| "----------------------------------\n"; |
| |
| StringAppendF(&report, "%45s %21s\n", "Original", "Reduced"); |
| StringAppendF(&report, "Parameter blocks % 25d% 25d\n", |
| num_parameter_blocks, num_parameter_blocks_reduced); |
| StringAppendF(&report, "Parameters % 25d% 25d\n", |
| num_parameters, num_parameters_reduced); |
| if (num_effective_parameters_reduced != num_parameters_reduced) { |
| StringAppendF(&report, "Effective parameters% 25d% 25d\n", |
| num_effective_parameters, num_effective_parameters_reduced); |
| } |
| StringAppendF(&report, "Residual blocks % 25d% 25d\n", |
| num_residual_blocks, num_residual_blocks_reduced); |
| StringAppendF(&report, "Residual % 25d% 25d\n", |
| num_residuals, num_residuals_reduced); |
| |
| if (minimizer_type == TRUST_REGION) { |
| // TRUST_SEARCH HEADER |
| StringAppendF(&report, "\nMinimizer %19s\n", |
| "TRUST_REGION"); |
| |
| if (linear_solver_type_used == DENSE_NORMAL_CHOLESKY || |
| linear_solver_type_used == DENSE_SCHUR || |
| linear_solver_type_used == DENSE_QR) { |
| StringAppendF(&report, "\nDense linear algebra library %15s\n", |
| DenseLinearAlgebraLibraryTypeToString( |
| dense_linear_algebra_library_type)); |
| } |
| |
| if (linear_solver_type_used == SPARSE_NORMAL_CHOLESKY || |
| linear_solver_type_used == SPARSE_SCHUR || |
| (linear_solver_type_used == ITERATIVE_SCHUR && |
| (preconditioner_type == CLUSTER_JACOBI || |
| preconditioner_type == CLUSTER_TRIDIAGONAL))) { |
| StringAppendF(&report, "\nSparse linear algebra library %15s\n", |
| SparseLinearAlgebraLibraryTypeToString( |
| sparse_linear_algebra_library_type)); |
| } |
| |
| StringAppendF(&report, "Trust region strategy %19s", |
| TrustRegionStrategyTypeToString( |
| trust_region_strategy_type)); |
| if (trust_region_strategy_type == DOGLEG) { |
| if (dogleg_type == TRADITIONAL_DOGLEG) { |
| StringAppendF(&report, " (TRADITIONAL)"); |
| } else { |
| StringAppendF(&report, " (SUBSPACE)"); |
| } |
| } |
| StringAppendF(&report, "\n"); |
| StringAppendF(&report, "\n"); |
| |
| StringAppendF(&report, "%45s %21s\n", "Given", "Used"); |
| StringAppendF(&report, "Linear solver %25s%25s\n", |
| LinearSolverTypeToString(linear_solver_type_given), |
| LinearSolverTypeToString(linear_solver_type_used)); |
| |
| if (linear_solver_type_given == CGNR || |
| linear_solver_type_given == ITERATIVE_SCHUR) { |
| StringAppendF(&report, "Preconditioner %25s%25s\n", |
| PreconditionerTypeToString(preconditioner_type), |
| PreconditionerTypeToString(preconditioner_type)); |
| } |
| |
| if (preconditioner_type == CLUSTER_JACOBI || |
| preconditioner_type == CLUSTER_TRIDIAGONAL) { |
| StringAppendF(&report, "Visibility clustering%24s%25s\n", |
| VisibilityClusteringTypeToString( |
| visibility_clustering_type), |
| VisibilityClusteringTypeToString( |
| visibility_clustering_type)); |
| } |
| StringAppendF(&report, "Threads % 25d% 25d\n", |
| num_threads_given, num_threads_used); |
| StringAppendF(&report, "Linear solver threads % 23d% 25d\n", |
| num_linear_solver_threads_given, |
| num_linear_solver_threads_used); |
| |
| if (IsSchurType(linear_solver_type_used)) { |
| string given; |
| StringifyOrdering(linear_solver_ordering_given, &given); |
| string used; |
| StringifyOrdering(linear_solver_ordering_used, &used); |
| StringAppendF(&report, |
| "Linear solver ordering %22s %24s\n", |
| given.c_str(), |
| used.c_str()); |
| } |
| |
| if (inner_iterations_given) { |
| StringAppendF(&report, |
| "Use inner iterations %20s %20s\n", |
| inner_iterations_given ? "True" : "False", |
| inner_iterations_used ? "True" : "False"); |
| } |
| |
| if (inner_iterations_used) { |
| string given; |
| StringifyOrdering(inner_iteration_ordering_given, &given); |
| string used; |
| StringifyOrdering(inner_iteration_ordering_used, &used); |
| StringAppendF(&report, |
| "Inner iteration ordering %20s %24s\n", |
| given.c_str(), |
| used.c_str()); |
| } |
| } else { |
| // LINE_SEARCH HEADER |
| StringAppendF(&report, "\nMinimizer %19s\n", "LINE_SEARCH"); |
| |
| |
| 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, "%45s %21s\n", "Given", "Used"); |
| StringAppendF(&report, "Threads % 25d% 25d\n", |
| num_threads_given, num_threads_used); |
| } |
| |
| 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", |
| num_successful_steps + num_unsuccessful_steps); |
| |
| // Successful/Unsuccessful steps only matter in the case of the |
| // trust region solver. Line search terminates when it encounters |
| // the first unsuccessful step. |
| if (minimizer_type == TRUST_REGION) { |
| StringAppendF(&report, "Successful steps % 14d\n", |
| num_successful_steps); |
| StringAppendF(&report, "Unsuccessful steps % 14d\n", |
| num_unsuccessful_steps); |
| } |
| if (inner_iterations_used) { |
| StringAppendF(&report, "Steps with inner iterations % 14d\n", |
| num_inner_iteration_steps); |
| } |
| |
| StringAppendF(&report, "\nTime (in seconds):\n"); |
| StringAppendF(&report, "Preprocessor %25.3f\n", |
| preprocessor_time_in_seconds); |
| |
| StringAppendF(&report, "\n Residual evaluation %23.3f\n", |
| residual_evaluation_time_in_seconds); |
| StringAppendF(&report, " Jacobian evaluation %23.3f\n", |
| jacobian_evaluation_time_in_seconds); |
| |
| if (minimizer_type == TRUST_REGION) { |
| StringAppendF(&report, " Linear solver %23.3f\n", |
| linear_solver_time_in_seconds); |
| } |
| |
| if (inner_iterations_used) { |
| StringAppendF(&report, " Inner iterations %23.3f\n", |
| inner_iteration_time_in_seconds); |
| } |
| |
| StringAppendF(&report, "Minimizer %25.3f\n\n", |
| minimizer_time_in_seconds); |
| |
| StringAppendF(&report, "Postprocessor %24.3f\n", |
| postprocessor_time_in_seconds); |
| |
| StringAppendF(&report, "Total %25.3f\n\n", |
| total_time_in_seconds); |
| |
| StringAppendF(&report, "Termination: %25s (%s)\n", |
| TerminationTypeToString(termination_type), message.c_str()); |
| return report; |
| }; |
| |
| bool Solver::Summary::IsSolutionUsable() const { |
| return (termination_type == CONVERGENCE || |
| termination_type == NO_CONVERGENCE || |
| termination_type == USER_SUCCESS); |
| } |
| |
| } // namespace ceres |
