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