Public Member Functions | List of all members
gtsam::ShonanAveraging2 Class Reference

#include <ShonanAveraging.h>

Inheritance diagram for gtsam::ShonanAveraging2:
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Public Member Functions

 ShonanAveraging2 (const Measurements &measurements, const Parameters &parameters=Parameters())
 
 ShonanAveraging2 (std::string g2oFile, const Parameters &parameters=Parameters())
 
- Public Member Functions inherited from gtsam::ShonanAveraging< 2 >
std::vector< BinaryMeasurement< T > > maybeRobust (const std::vector< BinaryMeasurement< T >> &measurements, bool useRobustModel=false) const
 
 ShonanAveraging (const Measurements &measurements, const Parameters &parameters=Parameters())
 
size_t nrUnknowns () const
 Return number of unknowns. More...
 
size_t nrMeasurements () const
 Return number of measurements. More...
 
const BinaryMeasurement< Rot > & measurement (size_t k) const
 k^th binary measurement More...
 
Measurements makeNoiseModelRobust (const Measurements &measurements, double k=1.345) const
 
const Rotmeasured (size_t k) const
 k^th measurement, as a Rot. More...
 
const KeyVectorkeys (size_t k) const
 Keys for k^th measurement, as a vector of Key values. More...
 
double cost (const Values &values) const
 
Values initializeRandomly (std::mt19937 &rng) const
 
Values initializeRandomly () const
 Random initialization for wrapper, fixed random seed. More...
 
std::pair< Values, double > run (const Values &initialEstimate, size_t pMin=d, size_t pMax=10) const
 
Sparse D () const
 Sparse version of D. More...
 
Matrix denseD () const
 Dense version of D. More...
 
Sparse Q () const
 Sparse version of Q. More...
 
Matrix denseQ () const
 Dense version of Q. More...
 
Sparse L () const
 Sparse version of L. More...
 
Matrix denseL () const
 Dense version of L. More...
 
Sparse computeLambda (const Matrix &S) const
 Version that takes pxdN Stiefel manifold elements. More...
 
Matrix computeLambda_ (const Values &values) const
 Dense versions of computeLambda for wrapper/testing. More...
 
Matrix computeLambda_ (const Matrix &S) const
 Dense versions of computeLambda for wrapper/testing. More...
 
Sparse computeA (const Values &values) const
 Compute A matrix whose Eigenvalues we will examine. More...
 
Sparse computeA (const Matrix &S) const
 Version that takes pxdN Stiefel manifold elements. More...
 
Matrix computeA_ (const Values &values) const
 Dense version of computeA for wrapper/testing. More...
 
double computeMinEigenValue (const Values &values, Vector *minEigenVector=nullptr) const
 
double computeMinEigenValueAP (const Values &values, Vector *minEigenVector=nullptr) const
 
Values roundSolutionS (const Matrix &S) const
 Project pxdN Stiefel manifold matrix S to Rot3^N. More...
 
Matrix riemannianGradient (size_t p, const Values &values) const
 Calculate the riemannian gradient of F(values) at values. More...
 
Values initializeWithDescent (size_t p, const Values &values, const Vector &minEigenVector, double minEigenValue, double gradienTolerance=1e-2, double preconditionedGradNormTolerance=1e-4) const
 
Sparse computeLambda (const Values &values) const
 
NonlinearFactorGraph buildGraphAt (size_t p) const
 
Values initializeRandomlyAt (size_t p, std::mt19937 &rng) const
 
Values initializeRandomlyAt (size_t p) const
 Version of initializeRandomlyAt with fixed random seed. More...
 
double costAt (size_t p, const Values &values) const
 
std::pair< double, VectorcomputeMinEigenVector (const Values &values) const
 
bool checkOptimality (const Values &values) const
 
boost::shared_ptr< LevenbergMarquardtOptimizercreateOptimizerAt (size_t p, const Values &initial) const
 
Values tryOptimizingAt (size_t p, const Values &initial) const
 
Values projectFrom (size_t p, const Values &values) const
 
Values roundSolution (const Values &values) const
 

Additional Inherited Members

- Public Types inherited from gtsam::ShonanAveraging< 2 >
using Measurements = std::vector< BinaryMeasurement< Rot >>
 
using Parameters = ShonanAveragingParameters< d >
 
using Rot = typename Parameters::Rot
 
using Sparse = Eigen::SparseMatrix< double >
 
- Static Public Member Functions inherited from gtsam::ShonanAveraging< 2 >
static Matrix StiefelElementMatrix (const Values &values)
 Project to pxdN Stiefel manifold. More...
 
static VectorValues TangentVectorValues (size_t p, const Vector &v)
 Create a VectorValues with eigenvector v_i. More...
 
static Values LiftwithDescent (size_t p, const Values &values, const Vector &minEigenVector)
 
static Values LiftTo (size_t p, const Values &values)
 Lift Values of type T to SO(p) More...
 

Detailed Description

Definition at line 427 of file ShonanAveraging.h.

Constructor & Destructor Documentation

gtsam::ShonanAveraging2::ShonanAveraging2 ( const Measurements measurements,
const Parameters parameters = Parameters() 
)

Definition at line 937 of file ShonanAveraging.cpp.

gtsam::ShonanAveraging2::ShonanAveraging2 ( std::string  g2oFile,
const Parameters parameters = Parameters() 
)
explicit

Definition at line 942 of file ShonanAveraging.cpp.


The documentation for this class was generated from the following files:


gtsam
Author(s):
autogenerated on Sat May 8 2021 02:58:27