Class CPoint2DPDF
Defined in File CPoint2DPDF.h
Inheritance Relationships
Base Types
public mrpt::serialization::CSerializablepublic mrpt::math::CProbabilityDensityFunction< CPoint2D, 2 >
Derived Type
public mrpt::poses::CPoint2DPDFGaussian(Class CPoint2DPDFGaussian)
Class Documentation
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class CPoint2DPDF : public mrpt::serialization::CSerializable, public mrpt::math::CProbabilityDensityFunction<CPoint2D, 2>
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 different 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
Subclassed by mrpt::poses::CPoint2DPDFGaussian
Public Types
Public Functions
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CPoint2DPDF() = default
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CPoint2DPDF(const CPoint2DPDF&) = default
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CPoint2DPDF(CPoint2DPDF&&) = default
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CPoint2DPDF &operator=(const CPoint2DPDF&) = default
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CPoint2DPDF &operator=(CPoint2DPDF&&) = default
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virtual ~CPoint2DPDF() = default
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virtual void copyFrom(const CPoint2DPDF &o) = 0
Copy operator, translating if necessary (for example, between particles and gaussian representations)
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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.
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CPoint2DPDF() = default