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| TransformBtwRobotsUnaryFactor () |
| | default constructor - only use for serialization
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| TransformBtwRobotsUnaryFactor (Key key, const VALUE &measured, Key keyA, Key keyB, const gtsam::Values &valA, const gtsam::Values &valB, const SharedGaussian &model) |
| | Constructor.
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virtual gtsam::NonlinearFactor::shared_ptr | clone () const |
| | Clone.
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| virtual void | print (const std::string &s, const KeyFormatter &keyFormatter=DefaultKeyFormatter) const |
| | implement functions needed for Testable More...
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virtual bool | equals (const NonlinearFactor &f, double tol=1e-9) const |
| | equals
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void | setValAValB (const gtsam::Values &valA, const gtsam::Values &valB) |
| | implement functions needed to derive from Factor
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| virtual double | error (const gtsam::Values &x) const |
| | Calculate the error of the factor This is typically equal to log-likelihood, e.g. More...
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virtual boost::shared_ptr< gtsam::GaussianFactor > | linearize (const gtsam::Values &x) const |
| | Linearize a non-linearFactorN to get a gtsam::GaussianFactor, \( Ax-b \approx h(x+\delta x)-z = h(x) + A \delta x - z \) Hence \( b = z - h(x) = - \mathtt{error\_vector}(x) \).
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gtsam::Vector | whitenedError (const gtsam::Values &x, boost::optional< std::vector< gtsam::Matrix > & > H=boost::none) const |
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gtsam::Vector | unwhitenedError (const gtsam::Values &x) const |
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std::size_t | size () const |
| | number of variables attached to this factor
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virtual size_t | dim () const |
| | get the dimension of the factor (number of rows on linearization)
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◆ error()
Calculate the error of the factor This is typically equal to log-likelihood, e.g.
\( 0.5(h(x)-z)^2/sigma^2 \) in case of Gaussian. You can override this for systems with unusual noise models.
Implements gtsam::NonlinearFactor.
◆ print()
The documentation for this class was generated from the following files: