22/** Declares a class that represents a Probability Distribution function (PDF) of a 2D point (x,y).
23 * This class is just the base class for unifying many diferent
24 * ways this PDF can be implemented.
25 *
26 * For convenience, a pose composition is also defined for any
27 * PDF derived class, changeCoordinatesReference, in the form of a method rather than an operator.
28 *
29 * For a similar class for 6D poses (a 3D point with attitude), see CPose3DPDF
30 *
31 * See also the tutorial on <a href="http://www.mrpt.org/Probability_Density_Distributions_Over_Spatial_Representations" >probabilistic spatial representations in the MRPT</a>.
44 /** 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!)
45 * \param p1 The first distribution to fuse
46 * \param p2 The second distribution to fuse
47 * \param 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.