buildGraphAt(size_t p) const | gtsam::ShonanAveraging< 3 > | |
checkOptimality(const Values &values) const | gtsam::ShonanAveraging< 3 > | |
computeA(const Values &values) const | gtsam::ShonanAveraging< 3 > | |
computeA(const Matrix &S) const | gtsam::ShonanAveraging< 3 > | |
computeA_(const Values &values) const | gtsam::ShonanAveraging< 3 > | inline |
computeLambda(const Matrix &S) const | gtsam::ShonanAveraging< 3 > | |
computeLambda(const Values &values) const | gtsam::ShonanAveraging< 3 > | |
computeLambda_(const Values &values) const | gtsam::ShonanAveraging< 3 > | inline |
computeLambda_(const Matrix &S) const | gtsam::ShonanAveraging< 3 > | inline |
computeMinEigenValue(const Values &values, Vector *minEigenVector=nullptr) const | gtsam::ShonanAveraging< 3 > | |
computeMinEigenValueAP(const Values &values, Vector *minEigenVector=nullptr) const | gtsam::ShonanAveraging< 3 > | |
computeMinEigenVector(const Values &values) const | gtsam::ShonanAveraging< 3 > | |
cost(const Values &values) const | gtsam::ShonanAveraging< 3 > | |
costAt(size_t p, const Values &values) const | gtsam::ShonanAveraging< 3 > | |
createOptimizerAt(size_t p, const Values &initial) const | gtsam::ShonanAveraging< 3 > | |
D() const | gtsam::ShonanAveraging< 3 > | inline |
denseD() const | gtsam::ShonanAveraging< 3 > | inline |
denseL() const | gtsam::ShonanAveraging< 3 > | inline |
denseQ() const | gtsam::ShonanAveraging< 3 > | inline |
initializeRandomly(std::mt19937 &rng) const | gtsam::ShonanAveraging< 3 > | |
initializeRandomly() const | gtsam::ShonanAveraging< 3 > | |
initializeRandomlyAt(size_t p, std::mt19937 &rng) const | gtsam::ShonanAveraging< 3 > | |
initializeRandomlyAt(size_t p) const | gtsam::ShonanAveraging< 3 > | |
initializeWithDescent(size_t p, const Values &values, const Vector &minEigenVector, double minEigenValue, double gradienTolerance=1e-2, double preconditionedGradNormTolerance=1e-4) const | gtsam::ShonanAveraging< 3 > | |
keys(size_t k) const | gtsam::ShonanAveraging< 3 > | inline |
L() const | gtsam::ShonanAveraging< 3 > | inline |
LiftTo(size_t p, const Values &values) | gtsam::ShonanAveraging< 3 > | inlinestatic |
LiftwithDescent(size_t p, const Values &values, const Vector &minEigenVector) | gtsam::ShonanAveraging< 3 > | static |
makeNoiseModelRobust(const Measurements &measurements, double k=1.345) const | gtsam::ShonanAveraging< 3 > | inline |
maybeRobust(const std::vector< BinaryMeasurement< T >> &measurements, bool useRobustModel=false) const | gtsam::ShonanAveraging< 3 > | inline |
measured(size_t k) const | gtsam::ShonanAveraging< 3 > | inline |
measurement(size_t k) const | gtsam::ShonanAveraging< 3 > | inline |
Measurements typedef | gtsam::ShonanAveraging< 3 > | |
nrUnknowns() const | gtsam::ShonanAveraging< 3 > | inline |
numberMeasurements() const | gtsam::ShonanAveraging< 3 > | inline |
Parameters typedef | gtsam::ShonanAveraging< 3 > | |
projectFrom(size_t p, const Values &values) const | gtsam::ShonanAveraging< 3 > | |
projectFrom(size_t p, const Values &values) const | gtsam::ShonanAveraging< 3 > | |
projectFrom(size_t p, const Values &values) const | gtsam::ShonanAveraging< 3 > | |
Q() const | gtsam::ShonanAveraging< 3 > | inline |
riemannianGradient(size_t p, const Values &values) const | gtsam::ShonanAveraging< 3 > | |
Rot typedef | gtsam::ShonanAveraging< 3 > | |
roundSolution(const Values &values) const | gtsam::ShonanAveraging< 3 > | |
roundSolutionS(const Matrix &S) const | gtsam::ShonanAveraging< 3 > | |
roundSolutionS(const Matrix &S) const | gtsam::ShonanAveraging< 3 > | |
roundSolutionS(const Matrix &S) const | gtsam::ShonanAveraging< 3 > | |
run(const Values &initialEstimate, size_t pMin=d, size_t pMax=10) const | gtsam::ShonanAveraging< 3 > | |
ShonanAveraging(const Measurements &measurements, const Parameters ¶meters=Parameters()) | gtsam::ShonanAveraging< 3 > | |
ShonanAveraging3(const Measurements &measurements, const Parameters ¶meters=Parameters()) | gtsam::ShonanAveraging3 | |
ShonanAveraging3(std::string g2oFile, const Parameters ¶meters=Parameters()) | gtsam::ShonanAveraging3 | explicit |
ShonanAveraging3(const BetweenFactorPose3s &factors, const Parameters ¶meters=Parameters()) | gtsam::ShonanAveraging3 | |
Sparse typedef | gtsam::ShonanAveraging< 3 > | |
StiefelElementMatrix(const Values &values) | gtsam::ShonanAveraging< 3 > | static |
TangentVectorValues(size_t p, const Vector &v) | gtsam::ShonanAveraging< 3 > | static |
tryOptimizingAt(size_t p, const Values &initial) const | gtsam::ShonanAveraging< 3 > | |