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//*************************************************************************
// nonlinear
//*************************************************************************
namespace gtsam {
#include <gtsam/geometry/Cal3Bundler.h>
#include <gtsam/geometry/Cal3DS2.h>
#include <gtsam/geometry/Cal3Fisheye.h>
#include <gtsam/geometry/Cal3Unified.h>
#include <gtsam/geometry/Cal3_S2.h>
#include <gtsam/geometry/CalibratedCamera.h>
#include <gtsam/geometry/EssentialMatrix.h>
#include <gtsam/geometry/PinholeCamera.h>
#include <gtsam/geometry/Point2.h>
#include <gtsam/geometry/Point3.h>
#include <gtsam/geometry/Pose2.h>
#include <gtsam/geometry/Pose3.h>
#include <gtsam/geometry/Rot2.h>
#include <gtsam/geometry/Rot3.h>
#include <gtsam/geometry/SO3.h>
#include <gtsam/geometry/SO4.h>
#include <gtsam/geometry/SOn.h>
#include <gtsam/geometry/StereoPoint2.h>
#include <gtsam/geometry/Unit3.h>
#include <gtsam/navigation/ImuBias.h>
#include <gtsam/navigation/NavState.h>
#include <gtsam/basis/ParameterMatrix.h>
#include <gtsam/nonlinear/GraphvizFormatting.h>
class GraphvizFormatting : gtsam::DotWriter {
GraphvizFormatting();
enum Axis { X, Y, Z, NEGX, NEGY, NEGZ };
gtsam::GraphvizFormatting::Axis paperHorizontalAxis;
gtsam::GraphvizFormatting::Axis paperVerticalAxis;
double scale;
bool mergeSimilarFactors;
};
#include <gtsam/nonlinear/NonlinearFactorGraph.h>
class NonlinearFactorGraph {
NonlinearFactorGraph();
NonlinearFactorGraph(const gtsam::NonlinearFactorGraph& graph);
// FactorGraph
void print(string s = "NonlinearFactorGraph: ",
const gtsam::KeyFormatter& keyFormatter =
gtsam::DefaultKeyFormatter) const;
bool equals(const gtsam::NonlinearFactorGraph& fg, double tol) const;
size_t size() const;
bool empty() const;
void remove(size_t i);
void replace(size_t i, gtsam::NonlinearFactor* factors);
void resize(size_t size);
size_t nrFactors() const;
gtsam::NonlinearFactor* at(size_t idx) const;
void push_back(const gtsam::NonlinearFactorGraph& factors);
void push_back(gtsam::NonlinearFactor* factor);
void add(gtsam::NonlinearFactor* factor);
bool exists(size_t idx) const;
gtsam::KeySet keys() const;
gtsam::KeyVector keyVector() const;
template <T = {double,
Vector,
gtsam::Point2,
gtsam::StereoPoint2,
gtsam::Point3,
gtsam::Rot2,
gtsam::SO3,
gtsam::SO4,
gtsam::Rot3,
gtsam::Pose2,
gtsam::Pose3,
gtsam::Cal3_S2,
gtsam::Cal3Fisheye,
gtsam::Cal3Unified,
gtsam::CalibratedCamera,
gtsam::PinholeCamera<gtsam::Cal3_S2>,
gtsam::PinholeCamera<gtsam::Cal3Bundler>,
gtsam::PinholeCamera<gtsam::Cal3Fisheye>,
gtsam::PinholeCamera<gtsam::Cal3Unified>,
gtsam::imuBias::ConstantBias}>
void addPrior(size_t key, const T& prior,
const gtsam::noiseModel::Base* noiseModel);
// NonlinearFactorGraph
void printErrors(const gtsam::Values& values) const;
double error(const gtsam::Values& values) const;
double probPrime(const gtsam::Values& values) const;
gtsam::Ordering orderingCOLAMD() const;
// Ordering* orderingCOLAMDConstrained(const gtsam::Values& c, const
// std::map<gtsam::Key,int>& constraints) const;
gtsam::GaussianFactorGraph* linearize(const gtsam::Values& values) const;
gtsam::NonlinearFactorGraph clone() const;
string dot(
const gtsam::Values& values,
const gtsam::KeyFormatter& keyFormatter = gtsam::DefaultKeyFormatter,
const gtsam::GraphvizFormatting& writer = gtsam::GraphvizFormatting());
void saveGraph(
const string& s, const gtsam::Values& values,
const gtsam::KeyFormatter& keyFormatter = gtsam::DefaultKeyFormatter,
const gtsam::GraphvizFormatting& writer = gtsam::GraphvizFormatting()) const;
// enabling serialization functionality
void serialize() const;
};
#include <gtsam/nonlinear/NonlinearFactor.h>
virtual class NonlinearFactor {
// Factor base class
size_t size() const;
gtsam::KeyVector keys() const;
void print(string s = "", const gtsam::KeyFormatter& keyFormatter =
gtsam::DefaultKeyFormatter) const;
void printKeys(string s) const;
// NonlinearFactor
bool equals(const gtsam::NonlinearFactor& other, double tol) const;
double error(const gtsam::Values& c) const;
size_t dim() const;
bool active(const gtsam::Values& c) const;
gtsam::GaussianFactor* linearize(const gtsam::Values& c) const;
gtsam::NonlinearFactor* clone() const;
gtsam::NonlinearFactor* rekey(const gtsam::KeyVector& newKeys) const;
};
#include <gtsam/nonlinear/NonlinearFactor.h>
virtual class NoiseModelFactor : gtsam::NonlinearFactor {
bool equals(const gtsam::NoiseModelFactor& other, double tol) const;
gtsam::noiseModel::Base* noiseModel() const;
Vector unwhitenedError(const gtsam::Values& x) const;
Vector whitenedError(const gtsam::Values& x) const;
};
#include <gtsam/nonlinear/Values.h>
class Values {
Values();
Values(const gtsam::Values& other);
size_t size() const;
bool empty() const;
void clear();
size_t dim() const;
void print(string s = "", const gtsam::KeyFormatter& keyFormatter =
gtsam::DefaultKeyFormatter) const;
bool equals(const gtsam::Values& other, double tol) const;
void insert(const gtsam::Values& values);
void update(const gtsam::Values& values);
void insert_or_assign(const gtsam::Values& values);
void erase(size_t j);
void swap(gtsam::Values& values);
bool exists(size_t j) const;
gtsam::KeyVector keys() const;
gtsam::VectorValues zeroVectors() const;
gtsam::Values retract(const gtsam::VectorValues& delta) const;
gtsam::VectorValues localCoordinates(const gtsam::Values& cp) const;
// enabling serialization functionality
void serialize() const;
// New in 4.0, we have to specialize every insert/update/at to generate
// wrappers Instead of the old: void insert(size_t j, const gtsam::Value&
// value); void update(size_t j, const gtsam::Value& val); gtsam::Value
// at(size_t j) const;
// The order is important: Vector has to precede Point2/Point3 so `atVector`
// can work for those fixed-size vectors.
void insert(size_t j, Vector vector);
void insert(size_t j, Matrix matrix);
void insert(size_t j, const gtsam::Point2& point2);
void insert(size_t j, const gtsam::Point3& point3);
void insert(size_t j, const gtsam::Rot2& rot2);
void insert(size_t j, const gtsam::Pose2& pose2);
void insert(size_t j, const gtsam::SO3& R);
void insert(size_t j, const gtsam::SO4& Q);
void insert(size_t j, const gtsam::SOn& P);
void insert(size_t j, const gtsam::Rot3& rot3);
void insert(size_t j, const gtsam::Pose3& pose3);
void insert(size_t j, const gtsam::Unit3& unit3);
void insert(size_t j, const gtsam::Cal3_S2& cal3_s2);
void insert(size_t j, const gtsam::Cal3DS2& cal3ds2);
void insert(size_t j, const gtsam::Cal3Bundler& cal3bundler);
void insert(size_t j, const gtsam::Cal3Fisheye& cal3fisheye);
void insert(size_t j, const gtsam::Cal3Unified& cal3unified);
void insert(size_t j, const gtsam::EssentialMatrix& essential_matrix);
void insert(size_t j, const gtsam::PinholeCamera<gtsam::Cal3_S2>& camera);
void insert(size_t j, const gtsam::PinholeCamera<gtsam::Cal3Bundler>& camera);
void insert(size_t j, const gtsam::PinholeCamera<gtsam::Cal3Fisheye>& camera);
void insert(size_t j, const gtsam::PinholeCamera<gtsam::Cal3Unified>& camera);
void insert(size_t j, const gtsam::PinholePose<gtsam::Cal3_S2>& camera);
void insert(size_t j, const gtsam::PinholePose<gtsam::Cal3Bundler>& camera);
void insert(size_t j, const gtsam::PinholePose<gtsam::Cal3Fisheye>& camera);
void insert(size_t j, const gtsam::PinholePose<gtsam::Cal3Unified>& camera);
void insert(size_t j, const gtsam::imuBias::ConstantBias& constant_bias);
void insert(size_t j, const gtsam::NavState& nav_state);
void insert(size_t j, double c);
void insert(size_t j, const gtsam::ParameterMatrix<1>& X);
void insert(size_t j, const gtsam::ParameterMatrix<2>& X);
void insert(size_t j, const gtsam::ParameterMatrix<3>& X);
void insert(size_t j, const gtsam::ParameterMatrix<4>& X);
void insert(size_t j, const gtsam::ParameterMatrix<5>& X);
void insert(size_t j, const gtsam::ParameterMatrix<6>& X);
void insert(size_t j, const gtsam::ParameterMatrix<7>& X);
void insert(size_t j, const gtsam::ParameterMatrix<8>& X);
void insert(size_t j, const gtsam::ParameterMatrix<9>& X);
void insert(size_t j, const gtsam::ParameterMatrix<10>& X);
void insert(size_t j, const gtsam::ParameterMatrix<11>& X);
void insert(size_t j, const gtsam::ParameterMatrix<12>& X);
void insert(size_t j, const gtsam::ParameterMatrix<13>& X);
void insert(size_t j, const gtsam::ParameterMatrix<14>& X);
void insert(size_t j, const gtsam::ParameterMatrix<15>& X);
template <T = {gtsam::Point2,
gtsam::Point3}>
void insert(size_t j, const T& val);
void update(size_t j, const gtsam::Point2& point2);
void update(size_t j, const gtsam::Point3& point3);
void update(size_t j, const gtsam::Rot2& rot2);
void update(size_t j, const gtsam::Pose2& pose2);
void update(size_t j, const gtsam::SO3& R);
void update(size_t j, const gtsam::SO4& Q);
void update(size_t j, const gtsam::SOn& P);
void update(size_t j, const gtsam::Rot3& rot3);
void update(size_t j, const gtsam::Pose3& pose3);
void update(size_t j, const gtsam::Unit3& unit3);
void update(size_t j, const gtsam::Cal3_S2& cal3_s2);
void update(size_t j, const gtsam::Cal3DS2& cal3ds2);
void update(size_t j, const gtsam::Cal3Bundler& cal3bundler);
void update(size_t j, const gtsam::Cal3Fisheye& cal3fisheye);
void update(size_t j, const gtsam::Cal3Unified& cal3unified);
void update(size_t j, const gtsam::EssentialMatrix& essential_matrix);
void update(size_t j, const gtsam::PinholeCamera<gtsam::Cal3_S2>& camera);
void update(size_t j, const gtsam::PinholeCamera<gtsam::Cal3Bundler>& camera);
void update(size_t j, const gtsam::PinholeCamera<gtsam::Cal3Fisheye>& camera);
void update(size_t j, const gtsam::PinholeCamera<gtsam::Cal3Unified>& camera);
void update(size_t j, const gtsam::PinholePose<gtsam::Cal3_S2>& camera);
void update(size_t j, const gtsam::PinholePose<gtsam::Cal3Bundler>& camera);
void update(size_t j, const gtsam::PinholePose<gtsam::Cal3Fisheye>& camera);
void update(size_t j, const gtsam::PinholePose<gtsam::Cal3Unified>& camera);
void update(size_t j, const gtsam::imuBias::ConstantBias& constant_bias);
void update(size_t j, const gtsam::NavState& nav_state);
void update(size_t j, Vector vector);
void update(size_t j, Matrix matrix);
void update(size_t j, double c);
void update(size_t j, const gtsam::ParameterMatrix<1>& X);
void update(size_t j, const gtsam::ParameterMatrix<2>& X);
void update(size_t j, const gtsam::ParameterMatrix<3>& X);
void update(size_t j, const gtsam::ParameterMatrix<4>& X);
void update(size_t j, const gtsam::ParameterMatrix<5>& X);
void update(size_t j, const gtsam::ParameterMatrix<6>& X);
void update(size_t j, const gtsam::ParameterMatrix<7>& X);
void update(size_t j, const gtsam::ParameterMatrix<8>& X);
void update(size_t j, const gtsam::ParameterMatrix<9>& X);
void update(size_t j, const gtsam::ParameterMatrix<10>& X);
void update(size_t j, const gtsam::ParameterMatrix<11>& X);
void update(size_t j, const gtsam::ParameterMatrix<12>& X);
void update(size_t j, const gtsam::ParameterMatrix<13>& X);
void update(size_t j, const gtsam::ParameterMatrix<14>& X);
void update(size_t j, const gtsam::ParameterMatrix<15>& X);
void insert_or_assign(size_t j, const gtsam::Point2& point2);
void insert_or_assign(size_t j, const gtsam::Point3& point3);
void insert_or_assign(size_t j, const gtsam::Rot2& rot2);
void insert_or_assign(size_t j, const gtsam::Pose2& pose2);
void insert_or_assign(size_t j, const gtsam::SO3& R);
void insert_or_assign(size_t j, const gtsam::SO4& Q);
void insert_or_assign(size_t j, const gtsam::SOn& P);
void insert_or_assign(size_t j, const gtsam::Rot3& rot3);
void insert_or_assign(size_t j, const gtsam::Pose3& pose3);
void insert_or_assign(size_t j, const gtsam::Unit3& unit3);
void insert_or_assign(size_t j, const gtsam::Cal3_S2& cal3_s2);
void insert_or_assign(size_t j, const gtsam::Cal3DS2& cal3ds2);
void insert_or_assign(size_t j, const gtsam::Cal3Bundler& cal3bundler);
void insert_or_assign(size_t j, const gtsam::Cal3Fisheye& cal3fisheye);
void insert_or_assign(size_t j, const gtsam::Cal3Unified& cal3unified);
void insert_or_assign(size_t j, const gtsam::EssentialMatrix& essential_matrix);
void insert_or_assign(size_t j, const gtsam::PinholeCamera<gtsam::Cal3_S2>& camera);
void insert_or_assign(size_t j, const gtsam::PinholeCamera<gtsam::Cal3Bundler>& camera);
void insert_or_assign(size_t j, const gtsam::PinholeCamera<gtsam::Cal3Fisheye>& camera);
void insert_or_assign(size_t j, const gtsam::PinholeCamera<gtsam::Cal3Unified>& camera);
void insert_or_assign(size_t j, const gtsam::PinholePose<gtsam::Cal3_S2>& camera);
void insert_or_assign(size_t j, const gtsam::PinholePose<gtsam::Cal3Bundler>& camera);
void insert_or_assign(size_t j, const gtsam::PinholePose<gtsam::Cal3Fisheye>& camera);
void insert_or_assign(size_t j, const gtsam::PinholePose<gtsam::Cal3Unified>& camera);
void insert_or_assign(size_t j, const gtsam::imuBias::ConstantBias& constant_bias);
void insert_or_assign(size_t j, const gtsam::NavState& nav_state);
void insert_or_assign(size_t j, Vector vector);
void insert_or_assign(size_t j, Matrix matrix);
void insert_or_assign(size_t j, double c);
void insert_or_assign(size_t j, const gtsam::ParameterMatrix<1>& X);
void insert_or_assign(size_t j, const gtsam::ParameterMatrix<2>& X);
void insert_or_assign(size_t j, const gtsam::ParameterMatrix<3>& X);
void insert_or_assign(size_t j, const gtsam::ParameterMatrix<4>& X);
void insert_or_assign(size_t j, const gtsam::ParameterMatrix<5>& X);
void insert_or_assign(size_t j, const gtsam::ParameterMatrix<6>& X);
void insert_or_assign(size_t j, const gtsam::ParameterMatrix<7>& X);
void insert_or_assign(size_t j, const gtsam::ParameterMatrix<8>& X);
void insert_or_assign(size_t j, const gtsam::ParameterMatrix<9>& X);
void insert_or_assign(size_t j, const gtsam::ParameterMatrix<10>& X);
void insert_or_assign(size_t j, const gtsam::ParameterMatrix<11>& X);
void insert_or_assign(size_t j, const gtsam::ParameterMatrix<12>& X);
void insert_or_assign(size_t j, const gtsam::ParameterMatrix<13>& X);
void insert_or_assign(size_t j, const gtsam::ParameterMatrix<14>& X);
void insert_or_assign(size_t j, const gtsam::ParameterMatrix<15>& X);
template <T = {gtsam::Point2,
gtsam::Point3,
gtsam::Rot2,
gtsam::Pose2,
gtsam::SO3,
gtsam::SO4,
gtsam::SOn,
gtsam::Rot3,
gtsam::Pose3,
gtsam::Unit3,
gtsam::Cal3_S2,
gtsam::Cal3DS2,
gtsam::Cal3Bundler,
gtsam::Cal3Fisheye,
gtsam::Cal3Unified,
gtsam::EssentialMatrix,
gtsam::PinholeCamera<gtsam::Cal3_S2>,
gtsam::PinholeCamera<gtsam::Cal3Bundler>,
gtsam::PinholeCamera<gtsam::Cal3Fisheye>,
gtsam::PinholeCamera<gtsam::Cal3Unified>,
gtsam::PinholePose<gtsam::Cal3_S2>,
gtsam::PinholePose<gtsam::Cal3Bundler>,
gtsam::PinholePose<gtsam::Cal3Fisheye>,
gtsam::PinholePose<gtsam::Cal3Unified>,
gtsam::imuBias::ConstantBias,
gtsam::NavState,
Vector,
Matrix,
double,
gtsam::ParameterMatrix<1>,
gtsam::ParameterMatrix<2>,
gtsam::ParameterMatrix<3>,
gtsam::ParameterMatrix<4>,
gtsam::ParameterMatrix<5>,
gtsam::ParameterMatrix<6>,
gtsam::ParameterMatrix<7>,
gtsam::ParameterMatrix<8>,
gtsam::ParameterMatrix<9>,
gtsam::ParameterMatrix<10>,
gtsam::ParameterMatrix<11>,
gtsam::ParameterMatrix<12>,
gtsam::ParameterMatrix<13>,
gtsam::ParameterMatrix<14>,
gtsam::ParameterMatrix<15>}>
T at(size_t j);
};
#include <gtsam/nonlinear/Marginals.h>
class Marginals {
Marginals(const gtsam::NonlinearFactorGraph& graph,
const gtsam::Values& solution);
Marginals(const gtsam::GaussianFactorGraph& gfgraph,
const gtsam::Values& solution);
Marginals(const gtsam::GaussianFactorGraph& gfgraph,
const gtsam::VectorValues& solutionvec);
void print(string s = "Marginals: ", const gtsam::KeyFormatter& keyFormatter =
gtsam::DefaultKeyFormatter) const;
Matrix marginalCovariance(size_t variable) const;
Matrix marginalInformation(size_t variable) const;
gtsam::JointMarginal jointMarginalCovariance(
const gtsam::KeyVector& variables) const;
gtsam::JointMarginal jointMarginalInformation(
const gtsam::KeyVector& variables) const;
};
class JointMarginal {
Matrix at(size_t iVariable, size_t jVariable) const;
Matrix fullMatrix() const;
void print(string s = "", gtsam::KeyFormatter keyFormatter =
gtsam::DefaultKeyFormatter) const;
};
#include <gtsam/nonlinear/LinearContainerFactor.h>
virtual class LinearContainerFactor : gtsam::NonlinearFactor {
LinearContainerFactor(gtsam::GaussianFactor* factor,
const gtsam::Values& linearizationPoint);
LinearContainerFactor(gtsam::GaussianFactor* factor);
gtsam::GaussianFactor* factor() const;
// const std::optional<Values>& linearizationPoint() const;
bool isJacobian() const;
gtsam::JacobianFactor* toJacobian() const;
gtsam::HessianFactor* toHessian() const;
static gtsam::NonlinearFactorGraph ConvertLinearGraph(
const gtsam::GaussianFactorGraph& linear_graph,
const gtsam::Values& linearizationPoint);
static gtsam::NonlinearFactorGraph ConvertLinearGraph(
const gtsam::GaussianFactorGraph& linear_graph);
// enabling serialization functionality
void serializable() const;
}; // \class LinearContainerFactor
// Summarization functionality
//#include <gtsam/nonlinear/summarization.h>
//
//// Uses partial QR approach by default
// gtsam::GaussianFactorGraph summarize(
// const gtsam::NonlinearFactorGraph& graph, const gtsam::Values& values,
// const gtsam::KeySet& saved_keys);
//
// gtsam::NonlinearFactorGraph summarizeAsNonlinearContainer(
// const gtsam::NonlinearFactorGraph& graph, const gtsam::Values& values,
// const gtsam::KeySet& saved_keys);
//*************************************************************************
// Nonlinear optimizers
//*************************************************************************
#include <gtsam/nonlinear/NonlinearOptimizerParams.h>
virtual class NonlinearOptimizerParams {
NonlinearOptimizerParams();
void print(string s = "") const;
int getMaxIterations() const;
double getRelativeErrorTol() const;
double getAbsoluteErrorTol() const;
double getErrorTol() const;
string getVerbosity() const;
void setMaxIterations(int value);
void setRelativeErrorTol(double value);
void setAbsoluteErrorTol(double value);
void setErrorTol(double value);
void setVerbosity(string s);
string getLinearSolverType() const;
void setLinearSolverType(string solver);
void setIterativeParams(gtsam::IterativeOptimizationParameters* params);
void setOrdering(const gtsam::Ordering& ordering);
string getOrderingType() const;
void setOrderingType(string ordering);
bool isMultifrontal() const;
bool isSequential() const;
bool isCholmod() const;
bool isIterative() const;
// This only applies to python since matlab does not have lambda machinery.
gtsam::NonlinearOptimizerParams::IterationHook iterationHook;
};
bool checkConvergence(double relativeErrorTreshold,
double absoluteErrorTreshold, double errorThreshold,
double currentError, double newError);
bool checkConvergence(const gtsam::NonlinearOptimizerParams& params,
double currentError, double newError);
#include <gtsam/nonlinear/GaussNewtonOptimizer.h>
virtual class GaussNewtonParams : gtsam::NonlinearOptimizerParams {
GaussNewtonParams();
};
#include <gtsam/nonlinear/LevenbergMarquardtOptimizer.h>
virtual class LevenbergMarquardtParams : gtsam::NonlinearOptimizerParams {
LevenbergMarquardtParams();
bool getDiagonalDamping() const;
double getlambdaFactor() const;
double getlambdaInitial() const;
double getlambdaLowerBound() const;
double getlambdaUpperBound() const;
bool getUseFixedLambdaFactor();
string getLogFile() const;
string getVerbosityLM() const;
void setDiagonalDamping(bool flag);
void setlambdaFactor(double value);
void setlambdaInitial(double value);
void setlambdaLowerBound(double value);
void setlambdaUpperBound(double value);
void setUseFixedLambdaFactor(bool flag);
void setLogFile(string s);
void setVerbosityLM(string s);
static gtsam::LevenbergMarquardtParams LegacyDefaults();
static gtsam::LevenbergMarquardtParams CeresDefaults();
static gtsam::LevenbergMarquardtParams EnsureHasOrdering(
gtsam::LevenbergMarquardtParams params,
const gtsam::NonlinearFactorGraph& graph);
static gtsam::LevenbergMarquardtParams ReplaceOrdering(
gtsam::LevenbergMarquardtParams params, const gtsam::Ordering& ordering);
};
#include <gtsam/nonlinear/DoglegOptimizer.h>
virtual class DoglegParams : gtsam::NonlinearOptimizerParams {
DoglegParams();
double getDeltaInitial() const;
string getVerbosityDL() const;
void setDeltaInitial(double deltaInitial) const;
void setVerbosityDL(string verbosityDL) const;
};
#include <gtsam/nonlinear/GncParams.h>
enum GncLossType {
GM /*Geman McClure*/,
TLS /*Truncated least squares*/
};
template<PARAMS>
virtual class GncParams {
GncParams(const PARAMS& baseOptimizerParams);
GncParams();
PARAMS baseOptimizerParams;
gtsam::GncLossType lossType;
size_t maxIterations;
double muStep;
double relativeCostTol;
double weightsTol;
gtsam::This::Verbosity verbosity;
gtsam::KeyVector knownInliers;
gtsam::KeyVector knownOutliers;
void setLossType(const gtsam::GncLossType type);
void setMaxIterations(const size_t maxIter);
void setMuStep(const double step);
void setRelativeCostTol(double value);
void setWeightsTol(double value);
void setVerbosityGNC(const gtsam::This::Verbosity value);
void setKnownInliers(const gtsam::KeyVector& knownIn);
void setKnownOutliers(const gtsam::KeyVector& knownOut);
void print(const string& str = "GncParams: ") const;
enum Verbosity {
SILENT,
SUMMARY,
VALUES
};
};
typedef gtsam::GncParams<gtsam::GaussNewtonParams> GncGaussNewtonParams;
typedef gtsam::GncParams<gtsam::LevenbergMarquardtParams> GncLMParams;
#include <gtsam/nonlinear/NonlinearOptimizer.h>
virtual class NonlinearOptimizer {
gtsam::Values optimize();
gtsam::Values optimizeSafely();
double error() const;
int iterations() const;
gtsam::Values values() const;
gtsam::NonlinearFactorGraph graph() const;
gtsam::GaussianFactorGraph* iterate() const;
};
#include <gtsam/nonlinear/GaussNewtonOptimizer.h>
virtual class GaussNewtonOptimizer : gtsam::NonlinearOptimizer {
GaussNewtonOptimizer(const gtsam::NonlinearFactorGraph& graph,
const gtsam::Values& initialValues);
GaussNewtonOptimizer(const gtsam::NonlinearFactorGraph& graph,
const gtsam::Values& initialValues,
const gtsam::GaussNewtonParams& params);
};
#include <gtsam/nonlinear/DoglegOptimizer.h>
virtual class DoglegOptimizer : gtsam::NonlinearOptimizer {
DoglegOptimizer(const gtsam::NonlinearFactorGraph& graph,
const gtsam::Values& initialValues);
DoglegOptimizer(const gtsam::NonlinearFactorGraph& graph,
const gtsam::Values& initialValues,
const gtsam::DoglegParams& params);
double getDelta() const;
};
/* Not creating bindings to GncOptimizer since the Chi2Inv currently uses boost */
/*
#include <gtsam/nonlinear/GncOptimizer.h>
template<PARAMS>
virtual class GncOptimizer {
GncOptimizer(const gtsam::NonlinearFactorGraph& graph,
const gtsam::Values& initialValues,
const PARAMS& params);
void setInlierCostThresholds(const double inth);
const Vector& getInlierCostThresholds();
void setInlierCostThresholdsAtProbability(const double alpha);
void setWeights(const Vector w);
const Vector& getWeights();
gtsam::Values optimize();
};
typedef gtsam::GncOptimizer<gtsam::GncParams<gtsam::GaussNewtonParams>> GncGaussNewtonOptimizer;
typedef gtsam::GncOptimizer<gtsam::GncParams<gtsam::LevenbergMarquardtParams>> GncLMOptimizer;
*/
#include <gtsam/nonlinear/LevenbergMarquardtOptimizer.h>
virtual class LevenbergMarquardtOptimizer : gtsam::NonlinearOptimizer {
LevenbergMarquardtOptimizer(const gtsam::NonlinearFactorGraph& graph,
const gtsam::Values& initialValues);
LevenbergMarquardtOptimizer(const gtsam::NonlinearFactorGraph& graph,
const gtsam::Values& initialValues,
const gtsam::LevenbergMarquardtParams& params);
double lambda() const;
void print(string s = "") const;
};
#include <gtsam/nonlinear/ISAM2.h>
class ISAM2GaussNewtonParams {
ISAM2GaussNewtonParams();
void print(string s = "") const;
/** Getters and Setters for all properties */
double getWildfireThreshold() const;
void setWildfireThreshold(double wildfireThreshold);
};
class ISAM2DoglegParams {
ISAM2DoglegParams();
void print(string s = "") const;
/** Getters and Setters for all properties */
double getWildfireThreshold() const;
void setWildfireThreshold(double wildfireThreshold);
double getInitialDelta() const;
void setInitialDelta(double initialDelta);
string getAdaptationMode() const;
void setAdaptationMode(string adaptationMode);
bool isVerbose() const;
void setVerbose(bool verbose);
};
class ISAM2ThresholdMapValue {
ISAM2ThresholdMapValue(char c, Vector thresholds);
ISAM2ThresholdMapValue(const gtsam::ISAM2ThresholdMapValue& other);
};
class ISAM2ThresholdMap {
ISAM2ThresholdMap();
ISAM2ThresholdMap(const gtsam::ISAM2ThresholdMap& other);
// Note: no print function
// common STL methods
size_t size() const;
bool empty() const;
void clear();
// structure specific methods
void insert(const gtsam::ISAM2ThresholdMapValue& value) const;
};
class ISAM2Params {
ISAM2Params();
void print(string s = "") const;
/** Getters and Setters for all properties */
void setOptimizationParams(
const gtsam::ISAM2GaussNewtonParams& gauss_newton__params);
void setOptimizationParams(const gtsam::ISAM2DoglegParams& dogleg_params);
void setRelinearizeThreshold(double threshold);
void setRelinearizeThreshold(const gtsam::ISAM2ThresholdMap& threshold_map);
string getFactorization() const;
void setFactorization(string factorization);
int relinearizeSkip;
bool enableRelinearization;
bool evaluateNonlinearError;
bool cacheLinearizedFactors;
bool enableDetailedResults;
bool enablePartialRelinearizationCheck;
bool findUnusedFactorSlots;
enum Factorization { CHOLESKY, QR };
gtsam::ISAM2Params::Factorization factorization;
};
class ISAM2Clique {
// Constructors
ISAM2Clique();
// Standard Interface
Vector gradientContribution() const;
void print(string s = "",
gtsam::KeyFormatter keyFormatter = gtsam::DefaultKeyFormatter);
};
class ISAM2Result {
ISAM2Result();
void print(string s = "") const;
/** Getters and Setters for all properties */
size_t getVariablesRelinearized() const;
size_t getVariablesReeliminated() const;
gtsam::FactorIndices getNewFactorsIndices() const;
size_t getCliques() const;
double getErrorBefore() const;
double getErrorAfter() const;
};
class ISAM2 {
ISAM2();
ISAM2(const gtsam::ISAM2Params& params);
ISAM2(const gtsam::ISAM2& other);
bool equals(const gtsam::ISAM2& other, double tol) const;
void print(string s = "", const gtsam::KeyFormatter& keyFormatter =
gtsam::DefaultKeyFormatter) const;
void printStats() const;
void saveGraph(string s) const;
gtsam::ISAM2Result update();
gtsam::ISAM2Result update(const gtsam::NonlinearFactorGraph& newFactors,
const gtsam::Values& newTheta);
gtsam::ISAM2Result update(const gtsam::NonlinearFactorGraph& newFactors,
const gtsam::Values& newTheta,
const gtsam::FactorIndices& removeFactorIndices);
gtsam::ISAM2Result update(const gtsam::NonlinearFactorGraph& newFactors,
const gtsam::Values& newTheta,
const gtsam::FactorIndices& removeFactorIndices,
const gtsam::KeyGroupMap& constrainedKeys);
gtsam::ISAM2Result update(const gtsam::NonlinearFactorGraph& newFactors,
const gtsam::Values& newTheta,
const gtsam::FactorIndices& removeFactorIndices,
gtsam::KeyGroupMap& constrainedKeys,
const gtsam::KeyList& noRelinKeys);
gtsam::ISAM2Result update(const gtsam::NonlinearFactorGraph& newFactors,
const gtsam::Values& newTheta,
const gtsam::FactorIndices& removeFactorIndices,
gtsam::KeyGroupMap& constrainedKeys,
const gtsam::KeyList& noRelinKeys,
const gtsam::KeyList& extraReelimKeys);
gtsam::ISAM2Result update(const gtsam::NonlinearFactorGraph& newFactors,
const gtsam::Values& newTheta,
const gtsam::FactorIndices& removeFactorIndices,
gtsam::KeyGroupMap& constrainedKeys,
const gtsam::KeyList& noRelinKeys,
const gtsam::KeyList& extraReelimKeys,
bool force_relinearize);
gtsam::ISAM2Result update(const gtsam::NonlinearFactorGraph& newFactors,
const gtsam::Values& newTheta,
const gtsam::ISAM2UpdateParams& updateParams);
gtsam::Values getLinearizationPoint() const;
bool valueExists(gtsam::Key key) const;
gtsam::Values calculateEstimate() const;
template <VALUE = {gtsam::Point2, gtsam::Rot2, gtsam::Pose2, gtsam::Point3,
gtsam::Rot3, gtsam::Pose3, gtsam::Cal3_S2, gtsam::Cal3DS2,
gtsam::Cal3Bundler, gtsam::EssentialMatrix,
gtsam::PinholeCamera<gtsam::Cal3_S2>,
gtsam::PinholeCamera<gtsam::Cal3Bundler>,
gtsam::PinholeCamera<gtsam::Cal3Fisheye>,
gtsam::PinholeCamera<gtsam::Cal3Unified>, Vector, Matrix}>
VALUE calculateEstimate(size_t key) const;
Matrix marginalCovariance(size_t key) const;
gtsam::Values calculateBestEstimate() const;
gtsam::VectorValues getDelta() const;
double error(const gtsam::VectorValues& x) const;
gtsam::NonlinearFactorGraph getFactorsUnsafe() const;
gtsam::VariableIndex getVariableIndex() const;
const gtsam::KeySet& getFixedVariables() const;
gtsam::ISAM2Params params() const;
void printStats() const;
gtsam::VectorValues gradientAtZero() const;
string dot(const gtsam::KeyFormatter& keyFormatter =
gtsam::DefaultKeyFormatter) const;
void saveGraph(string s,
const gtsam::KeyFormatter& keyFormatter =
gtsam::DefaultKeyFormatter) const;
};
#include <gtsam/nonlinear/NonlinearISAM.h>
class NonlinearISAM {
NonlinearISAM();
NonlinearISAM(int reorderInterval);
void print(string s = "", const gtsam::KeyFormatter& keyFormatter =
gtsam::DefaultKeyFormatter) const;
void printStats() const;
void saveGraph(string s) const;
gtsam::Values estimate() const;
Matrix marginalCovariance(size_t key) const;
int reorderInterval() const;
int reorderCounter() const;
void update(const gtsam::NonlinearFactorGraph& newFactors,
const gtsam::Values& initialValues);
void reorder_relinearize();
// These might be expensive as instead of a reference the wrapper will make a
// copy
gtsam::GaussianISAM bayesTree() const;
gtsam::Values getLinearizationPoint() const;
gtsam::NonlinearFactorGraph getFactorsUnsafe() const;
};
//*************************************************************************
// Nonlinear factor types
//*************************************************************************
#include <gtsam/nonlinear/PriorFactor.h>
template <T = {double,
Vector,
gtsam::Point2,
gtsam::StereoPoint2,
gtsam::Point3,
gtsam::Rot2,
gtsam::SO3,
gtsam::SO4,
gtsam::SOn,
gtsam::Rot3,
gtsam::Pose2,
gtsam::Pose3,
gtsam::Unit3,
gtsam::Cal3_S2,
gtsam::Cal3DS2,
gtsam::Cal3Bundler,
gtsam::Cal3Fisheye,
gtsam::Cal3Unified,
gtsam::CalibratedCamera,
gtsam::PinholeCamera<gtsam::Cal3_S2>,
gtsam::PinholeCamera<gtsam::Cal3Bundler>,
gtsam::PinholeCamera<gtsam::Cal3Fisheye>,
gtsam::PinholeCamera<gtsam::Cal3Unified>,
gtsam::imuBias::ConstantBias}>
virtual class PriorFactor : gtsam::NoiseModelFactor {
PriorFactor(size_t key, const T& prior,
const gtsam::noiseModel::Base* noiseModel);
T prior() const;
// enabling serialization functionality
void serialize() const;
};
#include <gtsam/nonlinear/NonlinearEquality.h>
template <T = {gtsam::Point2, gtsam::StereoPoint2, gtsam::Point3, gtsam::Rot2,
gtsam::SO3, gtsam::SO4, gtsam::SOn, gtsam::Rot3, gtsam::Pose2,
gtsam::Pose3, gtsam::Cal3_S2, gtsam::CalibratedCamera,
gtsam::PinholeCamera<gtsam::Cal3_S2>,
gtsam::PinholeCamera<gtsam::Cal3Bundler>,
gtsam::PinholeCamera<gtsam::Cal3Fisheye>,
gtsam::PinholeCamera<gtsam::Cal3Unified>,
gtsam::imuBias::ConstantBias}>
virtual class NonlinearEquality : gtsam::NoiseModelFactor {
// Constructor - forces exact evaluation
NonlinearEquality(size_t j, const T& feasible);
// Constructor - allows inexact evaluation
NonlinearEquality(size_t j, const T& feasible, double error_gain);
// enabling serialization functionality
void serialize() const;
};
template <T = {gtsam::Point2, gtsam::StereoPoint2, gtsam::Point3, gtsam::Rot2,
gtsam::SO3, gtsam::SO4, gtsam::SOn, gtsam::Rot3, gtsam::Pose2,
gtsam::Pose3, gtsam::Cal3_S2, gtsam::CalibratedCamera,
gtsam::PinholeCamera<gtsam::Cal3_S2>,
gtsam::PinholeCamera<gtsam::Cal3Bundler>,
gtsam::PinholeCamera<gtsam::Cal3Fisheye>,
gtsam::PinholeCamera<gtsam::Cal3Unified>,
gtsam::imuBias::ConstantBias}>
virtual class NonlinearEquality2 : gtsam::NoiseModelFactor {
NonlinearEquality2(gtsam::Key key1, gtsam::Key key2, double mu = 1e4);
gtsam::Vector evaluateError(const T& x1, const T& x2);
};
} // namespace gtsam
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