gtsam/gtsam/nonlinear/DoglegOptimizer.h

131 lines
4.1 KiB
C++

/* ----------------------------------------------------------------------------
* GTSAM Copyright 2010, Georgia Tech Research Corporation,
* Atlanta, Georgia 30332-0415
* All Rights Reserved
* Authors: Frank Dellaert, et al. (see THANKS for the full author list)
* See LICENSE for the license information
* -------------------------------------------------------------------------- */
/**
* @file DoglegOptimizer.h
* @brief
* @author Richard Roberts
* @date Feb 26, 2012
*/
#pragma once
#include <gtsam/nonlinear/NonlinearOptimizer.h>
namespace gtsam {
class DoglegOptimizer;
/** Parameters for Levenberg-Marquardt optimization. Note that this parameters
* class inherits from NonlinearOptimizerParams, which specifies the parameters
* common to all nonlinear optimization algorithms. This class also contains
* all of those parameters.
*/
class GTSAM_EXPORT DoglegParams : public NonlinearOptimizerParams {
public:
/** See DoglegParams::dlVerbosity */
enum VerbosityDL {
SILENT,
VERBOSE
};
double deltaInitial; ///< The initial trust region radius (default: 10.0)
VerbosityDL verbosityDL; ///< The verbosity level for Dogleg (default: SILENT), see also NonlinearOptimizerParams::verbosity
DoglegParams() :
deltaInitial(1.0), verbosityDL(SILENT) {}
~DoglegParams() override {}
void print(const std::string& str = "") const override {
NonlinearOptimizerParams::print(str);
std::cout << " deltaInitial: " << deltaInitial << "\n";
std::cout.flush();
}
double getDeltaInitial() const { return deltaInitial; }
std::string getVerbosityDL() const { return verbosityDLTranslator(verbosityDL); }
void setDeltaInitial(double deltaInitial) { this->deltaInitial = deltaInitial; }
void setVerbosityDL(const std::string& verbosityDL) { this->verbosityDL = verbosityDLTranslator(verbosityDL); }
private:
VerbosityDL verbosityDLTranslator(const std::string& verbosityDL) const;
std::string verbosityDLTranslator(VerbosityDL verbosityDL) const;
};
/**
* This class performs Dogleg nonlinear optimization
*/
class GTSAM_EXPORT DoglegOptimizer : public NonlinearOptimizer {
protected:
DoglegParams params_;
public:
typedef boost::shared_ptr<DoglegOptimizer> shared_ptr;
/// @name Standard interface
/// @{
/** Standard constructor, requires a nonlinear factor graph, initial
* variable assignments, and optimization parameters. For convenience this
* version takes plain objects instead of shared pointers, but internally
* copies the objects.
* @param graph The nonlinear factor graph to optimize
* @param initialValues The initial variable assignments
* @param params The optimization parameters
*/
DoglegOptimizer(const NonlinearFactorGraph& graph, const Values& initialValues,
const DoglegParams& params = DoglegParams());
/** Standard constructor, requires a nonlinear factor graph, initial
* variable assignments, and optimization parameters. For convenience this
* version takes plain objects instead of shared pointers, but internally
* copies the objects.
* @param graph The nonlinear factor graph to optimize
* @param initialValues The initial variable assignments
*/
DoglegOptimizer(const NonlinearFactorGraph& graph, const Values& initialValues,
const Ordering& ordering);
/// @}
/// @name Advanced interface
/// @{
/** Virtual destructor */
~DoglegOptimizer() override {}
/**
* Perform a single iteration, returning GaussianFactorGraph corresponding to
* the linearized factor graph.
*/
GaussianFactorGraph::shared_ptr iterate() override;
/** Read-only access the parameters */
const DoglegParams& params() const { return params_; }
/** Access the current trust region radius delta */
double getDelta() const;
/// @}
protected:
/** Access the parameters (base class version) */
const NonlinearOptimizerParams& _params() const override { return params_; }
/** Internal function for computing a COLAMD ordering if no ordering is specified */
DoglegParams ensureHasOrdering(DoglegParams params, const NonlinearFactorGraph& graph) const;
};
}