OpenKalman::SphericalSimplex< Parameters > Struct Template Reference

Spherical simplex sigma points, as implemented in, e.g., Simon J. More...

#include <SphericalSimplex.hpp>

Inheritance diagram for OpenKalman::SphericalSimplex< Parameters >:

Collaboration diagram for OpenKalman::SphericalSimplex< Parameters >:

Static Public Member Functions
template<std::size_t dim>
static constexpr auto	unscaled_W0 ()
template<std::size_t dim>
static constexpr auto	unscaled_W ()
template<typename... Dist, std::enable_if_t<(gaussian_distribution< Dist > and ...) and(sizeof...(Dist) > 0>
static constexpr auto	sample_points (const Dist &...ds)
	Calculate the scaled and translated sigma points, given a prior distribution and noise terms. More...
Static Public Member Functions inherited from OpenKalman::internal::ScaledSigmaPointsBase< SphericalSimplex< Parameters > >
static auto	weighted_means (YMeans &&y_means)
static auto	covariance (const X &x_deviations, const Y &y_deviations)
	Calculate the posterior covariance, given prior and posterior deviations from the sigma points. More...

Static Public Attributes
template<std::size_t dim>
static constexpr size_t	sigma_point_count = dim + 2
	Number of sigma points. More...
static constexpr auto	alpha = Parameters::alpha
	The alpha parameter. More...
static constexpr auto	beta = Parameters::beta
	The beta parameter. More...

Detailed Description

template<typename Parameters = SphericalSimplexParameters>
struct OpenKalman::SphericalSimplex< Parameters >

Spherical simplex sigma points, as implemented in, e.g., Simon J.

Julier. The spherical simplex unscented tests. In Proceedings of American Control Conference, Denver, Colorado, pages 2430–2434, 2003.

Member Function Documentation

sample_points()

template<typename Parameters = SphericalSimplexParameters>

template<typename... Dist, std::enable_if_t<(gaussian_distribution< Dist > and ...) and(sizeof...(Dist) > 0>

static constexpr auto OpenKalman::SphericalSimplex< Parameters >::sample_points ( const Dist &...  ds )

inlinestatic

Calculate the scaled and translated sigma points, given a prior distribution and noise terms.

The mean of the sample points is effectively translated the origin.

Template Parameters

Dist	The prior distribution and any optional noise distributions.

Returns

A tuple of sigma point matrices, one matrix for each input and noise distribution. Each column of these matrices corresponds to a sigma point.

Member Data Documentation

alpha

template<typename Parameters = SphericalSimplexParameters>

constexpr auto OpenKalman::SphericalSimplex< Parameters >::alpha = Parameters::alpha

static

The alpha parameter.

Note

Used by base class.

beta

template<typename Parameters = SphericalSimplexParameters>

constexpr auto OpenKalman::SphericalSimplex< Parameters >::beta = Parameters::beta

static

The beta parameter.

Note

Used by base class.

sigma_point_count

template<typename Parameters = SphericalSimplexParameters>

template<std::size_t dim>

constexpr size_t OpenKalman::SphericalSimplex< Parameters >::sigma_point_count = dim + 2

static

Number of sigma points.

Template Parameters

dim	Number of dimensions of the input variable.

Note

Used by base class.

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

• OpenKalman/transforms/sample-points/SphericalSimplex.hpp