Emrys::MeasurementUpdate< Space, MeasurementSpace, Count, Scalar_, Allocator > Struct Template Reference

The result of update(): weighted branches, one per noise component, and the observation's log-likelihood. More...

#include <EmrysFilter/Models/MeasurementUpdate.h>

Public Types
using	Scalar = Scalar_
	the scalar type
using	SpaceType = Space
	the state's space
using	MeasurementSpaceType = MeasurementSpace
	the measurement space
using	BranchType = UpdateBranch<Space, MeasurementSpace, Scalar>
	one branch
using	allocator_type = Allocator
	where a run-time number of branches comes from
using	Container
	The branches' container: an array when their number is known at compile time, and otherwise a buffer from Allocator.

Public Member Functions
	MeasurementUpdate ()=default
	no branches
	MeasurementUpdate (Container branches, Scalar mixtureLogLikelihood=0)
	The branches branches of an observation whose log-likelihood, where they are more than the one a single noise component gives, is mixtureLogLikelihood.
Scalar	logLikelihood () const
Eigen::Index	innovationSize () const
Allocator	get_allocator () const

Public Attributes
Container	branches
	one per noise component, weights summing to one

Static Public Attributes
static constexpr std::size_t	BranchCount = Count
	the number of branches, or std::dynamic_extent

Detailed Description

template<typename Space, typename MeasurementSpace, std::size_t Count = std::dynamic_extent, typename Scalar_ = double, typename Allocator = DefaultAllocator>
struct Emrys::MeasurementUpdate< Space, MeasurementSpace, Count, Scalar_, Allocator >

The result of update(): weighted branches, one per noise component, and the observation's log-likelihood.

A single Gaussian noise gives one branch.

Template Parameters

Space	the state's space
MeasurementSpace	the measurement space
Count	number of branches if known at compile time, otherwise std::dynamic_extent
Scalar_	the scalar type
Allocator	where a run-time number of branches comes from (see Allocation)

Member Typedef Documentation

Container

template<typename Space, typename MeasurementSpace, std::size_t Count = std::dynamic_extent, typename Scalar_ = double, typename Allocator = DefaultAllocator>

using Emrys::MeasurementUpdate< Space, MeasurementSpace, Count, Scalar_, Allocator >::Container

Initial value:

std::conditional_t<
       Count == std::dynamic_extent,
       internal::Buffer<BranchType, Allocator>,
       std::array<BranchType, Count>>

The branches' container: an array when their number is known at compile time, and otherwise a buffer from Allocator.

Member Function Documentation

get_allocator()

template<typename Space, typename MeasurementSpace, std::size_t Count = std::dynamic_extent, typename Scalar_ = double, typename Allocator = DefaultAllocator>

Allocator Emrys::MeasurementUpdate< Space, MeasurementSpace, Count, Scalar_, Allocator >::get_allocator ( ) const

inlinenodiscard

Returns

the allocator a run-time number of branches comes from, or a default-constructed one for an array of them

innovationSize()

template<typename Space, typename MeasurementSpace, std::size_t Count = std::dynamic_extent, typename Scalar_ = double, typename Allocator = DefaultAllocator>

Eigen::Index Emrys::MeasurementUpdate< Space, MeasurementSpace, Count, Scalar_, Allocator >::innovationSize ( ) const

inlinenodiscard

Returns

the difference dimension of the innovation, the degrees of freedom of each NIS

logLikelihood()

template<typename Space, typename MeasurementSpace, std::size_t Count = std::dynamic_extent, typename Scalar_ = double, typename Allocator = DefaultAllocator>

Scalar Emrys::MeasurementUpdate< Space, MeasurementSpace, Count, Scalar_, Allocator >::logLikelihood ( ) const

inlinenodiscard

Returns

the observation's log-likelihood, \( \log p(z) = \log \sum_k w_k \, p(z \mid k) \)

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The documentation for this struct was generated from the following file:

• EmrysFilter/Models/MeasurementUpdate.h