class mrpt::poses::CPoint2DPDF
Overview
Declares a class that represents a Probability Distribution function (PDF) of a 2D point (x,y).
This class is just the base class for unifying many diferent ways this PDF can be implemented.
For convenience, a pose composition is also defined for any PDF derived class, changeCoordinatesReference, in the form of a method rather than an operator.
For a similar class for 6D poses (a 3D point with attitude), see CPose3DPDF
See also: probabilistic spatial representations
See also:
#include <mrpt/poses/CPoint2DPDF.h> class CPoint2DPDF: public mrpt::serialization::CSerializable, public mrpt::math::CProbabilityDensityFunction { public: // methods virtual void copyFrom(const CPoint2DPDF& o) = 0; virtual void changeCoordinatesReference(const CPose3D& newReferenceBase) = 0; virtual void bayesianFusion( const CPoint2DPDF& p1, const CPoint2DPDF& p2, const double minMahalanobisDistToDrop = 0 ) = 0; virtual std::tuple<cov_mat_t, type_value> getCovarianceAndMean() const = 0; virtual bool saveToTextFile(const std::string& file) const = 0; }; // direct descendants class CPoint2DPDFGaussian;
Inherited Members
public: // typedefs typedef CProbabilityDensityFunction<TDATA, STATE_LEN> self_t;
Methods
virtual void copyFrom(const CPoint2DPDF& o) = 0
Copy operator, translating if necesary (for example, between particles and gaussian representations)
virtual void bayesianFusion( const CPoint2DPDF& p1, const CPoint2DPDF& p2, const double minMahalanobisDistToDrop = 0 ) = 0
Bayesian fusion of two point distributions (product of two distributions->new distribution), then save the result in this object (WARNING: See implementing classes to see classes that can and cannot be mixtured!)
Parameters:
p1 |
The first distribution to fuse |
p2 |
The second distribution to fuse |
minMahalanobisDistToDrop |
If set to different of 0, the result of very separate Gaussian modes (that will result in negligible components) in SOGs will be dropped to reduce the number of modes in the output. |
virtual std::tuple<cov_mat_t, type_value> getCovarianceAndMean() const = 0
Returns an estimate of the pose covariance matrix (STATE_LENxSTATE_LEN cov matrix) and the mean, both at once.
See also:
virtual bool saveToTextFile(const std::string& file) const = 0
Save PDF’s particles to a text file.
See derived classes for more information about the format of generated files.
Returns:
false on error