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| ShonanAveraging3 (const BetweenFactorPose3s &factors, const Parameters ¶meters=Parameters()) |
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| ShonanAveraging3 (const Measurements &measurements, const Parameters ¶meters=Parameters()) |
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| ShonanAveraging3 (std::string g2oFile, const Parameters ¶meters=Parameters()) |
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std::vector< BinaryMeasurement< T > > | maybeRobust (const std::vector< BinaryMeasurement< T >> &measurements, bool useRobustModel=false) const |
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Values | projectFrom (size_t p, const Values &values) const |
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Values | projectFrom (size_t p, const Values &values) const |
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Values | roundSolutionS (const Matrix &S) const |
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Values | roundSolutionS (const Matrix &S) const |
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| ShonanAveraging (const Measurements &measurements, const Parameters ¶meters=Parameters()) |
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size_t | nrUnknowns () const |
| Return number of unknowns. More...
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size_t | numberMeasurements () const |
| Return number of measurements. More...
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const BinaryMeasurement< Rot > & | measurement (size_t k) const |
| k^th binary measurement More...
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Measurements | makeNoiseModelRobust (const Measurements &measurements, double k=1.345) const |
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const Rot & | measured (size_t k) const |
| k^th measurement, as a Rot. More...
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const KeyVector & | keys (size_t k) const |
| Keys for k^th measurement, as a vector of Key values. More...
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double | cost (const Values &values) const |
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Values | initializeRandomly (std::mt19937 &rng) const |
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Values | initializeRandomly () const |
| Random initialization for wrapper, fixed random seed. More...
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std::pair< Values, double > | run (const Values &initialEstimate, size_t pMin=d, size_t pMax=10) const |
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Sparse | computeLambda (const Matrix &S) const |
| Version that takes pxdN Stiefel manifold elements. More...
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Matrix | computeLambda_ (const Values &values) const |
| Dense versions of computeLambda for wrapper/testing. More...
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Matrix | computeLambda_ (const Matrix &S) const |
| Dense versions of computeLambda for wrapper/testing. More...
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Sparse | computeA (const Values &values) const |
| Compute A matrix whose Eigenvalues we will examine. More...
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Sparse | computeA (const Matrix &S) const |
| Version that takes pxdN Stiefel manifold elements. More...
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Matrix | computeA_ (const Values &values) const |
| Dense version of computeA for wrapper/testing. More...
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double | computeMinEigenValue (const Values &values, Vector *minEigenVector=nullptr) const |
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double | computeMinEigenValueAP (const Values &values, Vector *minEigenVector=nullptr) const |
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Values | roundSolutionS (const Matrix &S) const |
| Project pxdN Stiefel manifold matrix S to Rot3^N. More...
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Matrix | riemannianGradient (size_t p, const Values &values) const |
| Calculate the riemannian gradient of F(values) at values. More...
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Values | initializeWithDescent (size_t p, const Values &values, const Vector &minEigenVector, double minEigenValue, double gradienTolerance=1e-2, double preconditionedGradNormTolerance=1e-4) const |
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Sparse | computeLambda (const Values &values) const |
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NonlinearFactorGraph | buildGraphAt (size_t p) const |
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Values | initializeRandomlyAt (size_t p, std::mt19937 &rng) const |
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Values | initializeRandomlyAt (size_t p) const |
| Version of initializeRandomlyAt with fixed random seed. More...
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double | costAt (size_t p, const Values &values) const |
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std::pair< double, Vector > | computeMinEigenVector (const Values &values) const |
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bool | checkOptimality (const Values &values) const |
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std::shared_ptr< LevenbergMarquardtOptimizer > | createOptimizerAt (size_t p, const Values &initial) const |
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Values | tryOptimizingAt (size_t p, const Values &initial) const |
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Values | projectFrom (size_t p, const Values &values) const |
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Values | roundSolution (const Values &values) const |
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Definition at line 438 of file ShonanAveraging.h.