What a Rao-Blackwellized point-mass filter's update did, per live cell and in total. More...

#include <EmrysFilter/Filters/RbPointMassFilter.h>

Public Types
using	ArrayType = Eigen::Map<Eigen::Array<Scalar, Eigen::Dynamic, 1> const>
	a per-cell array
using	allocator_type = Allocator
	where the cells and per-cell arrays come from

Public Member Functions
	RbPointMassFilterUpdate (Allocator const &allocator={})
	An empty result whose cells and arrays come from allocator.
std::span< Eigen::Index const >	cells () const
ArrayType	logLikelihoods () const
ArrayType	nis () const
Eigen::Index	innovationSize () const
allocator_type	get_allocator () const
Scalar	logLikelihood () const

Public Attributes
bool	accepted = false
	whether any cell accepted the measurement

Detailed Description

template<typename Scalar = double, typename Allocator = DefaultAllocator>
class Emrys::RbPointMassFilterUpdate< Scalar, Allocator >

What a Rao-Blackwellized point-mass filter's update did, per live cell and in total.

The arrays have one entry per cell that was alive when the update began, in the order of cells(). A cell whose update the policy rejected has log-likelihood \( -\infty \) and NIS NaN, and has been removed from the state.

The result owns its cells and arrays, in storage from Allocator. An update into a result (RbPointMassFilter::update(measurement, result)) refills that storage, so a result kept across steps allocates nothing once it has held as many cells (see Allocation).