MYNT-EYE-S-SDK/3rdparty/ceres-solver-1.11.0/internal/ceres/gradient_problem_solver.cc

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2019-01-03 10:25:18 +02:00
// 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(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
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();
Solver::Options solver_options =
GradientProblemSolverOptionsToSolverOptions(options);
*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 (!solver_options.IsValid(&summary->message)) {
LOG(ERROR) << "Terminating: " << summary->message;
return;
}
// Assuming that the parameter blocks in the program have been
Minimizer::Options minimizer_options;
minimizer_options = Minimizer::Options(solver_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