Struct BayesianSet

pub struct BayesianSet {
    set: HashSet<Vec2D<i32>>,
    curr_slice: SquareSlice,
    measurements: Vec<BeaconMeas>,
}

Represents a discrete binary Bayesian set used for probabilistic mapping and spatial estimation.

Maintains a collection of coordinates (set) within a certain region (curr_slice) that satisfy constraints derived from beacon measurements. Utilizes these measurements to estimate positions and optimize spatial packing of regions.

Fields

set: HashSet<Vec2D<i32>>

The current set of coordinates that satisfy constraints.

curr_slice: SquareSlice

The square slice of the map currently being evaluated.

measurements: Vec<BeaconMeas>

A collection of beacon measurements contributing to the set’s constraints.

Implementations

impl BayesianSet

const K_FAC_MAX: I32F32

Maximum scale factor for noise calculations.

const K_FAC_MIN: I32F32

Minimum scale factor for noise calculations.

pub const STD_DIST_SAFETY: I32F32

Safety buffer for standard deviation in distance calculations.

pub const MAX_DIST: I32F32

Maximum allowable distance for measurements.

const MIN_DIST: I32F32

Minimum allowable distance for measurements.

pub const K_ADD: I32F32

Constant noise offset.

pub const MAX_RES_UNCERTAINTY_RAD: f32 = 75f32

Maximum resolution for uncertainty radius, used in hexagonal packing.

const MAX_ITEMS: NonZero<usize>

Maximum number of items to retrieve during a nearest neighbor search.

fn get_dists(d_noisy: I32F32) -> (I32F32, I32F32)

Computes the minimum and maximum distances for a given noisy distance value.

Arguments

• d_noisy - The noisy distance value (I32F32).

Returns

A tuple containing the minimum and maximum distances.

pub fn new(meas: BeaconMeas) -> Self

Creates a new BayesianSet from an initial beacon measurement.

Arguments

• meas - The initial beacon measurement.

Returns

A new BayesianSet instance.

pub fn update(&mut self, meas: &BeaconMeas)

Updates the current Bayesian set based on a new beacon measurement.

Arguments

• meas - The new beacon measurement to incorporate.

pub fn is_in_set(&self, pos: Vec2D<i32>) -> bool

Checks if a given position is part of the current set.

Arguments

• pos - The position to check.

Returns

true if the position is in the set, otherwise false.

pub fn guess_estimate(&self) -> usize

Estimates the number of 75px guesses required to cover the current coordinate set.

Returns

An estimate of regions needed.

pub fn pack_perfect_circles(&self) -> Vec<Vec2D<I32F32>>

Packs the set’s coordinates into circular regions with minimal overlap.

Returns

A Vec of circle centers represented as Vec2D<I32F32>.

fn assign_points_to_hexes( &self, h_c_tree: &ImmutableKdTree<f64, 2>, h_c: &[Vec2D<f64>], ) -> HashMap<Vec2D<i32>, HashSet<Vec2D<i32>>>

Assigns points in the set to the nearest hexagonal grid center.

Arguments

• h_c_tree - Immutable k-d tree of hex centers.
• h_c - Hexagonal centers as a vector.

Returns

A HashMap mapping each hex center to the points that it covers.

fn select_minimal_circles( assignments: HashMap<Vec2D<i32>, HashSet<Vec2D<i32>>>, ) -> Vec<Vec2D<i32>>

Selects minimal circle centers to cover the assigned points.

Arguments

• assignments - A map of hex centers to their assigned points.

Returns

A vector of selected hex centers that cover the points.

Trait Implementations

impl Clone for BayesianSet

fn clone(&self) -> BayesianSet

Returns a copy of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for BayesianSet

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Serialize for BayesianSet

fn serialize<__S>(&self, __serializer: __S) -> Result<__S::Ok, __S::Error>

where __S: Serializer,

Serialize this value into the given Serde serializer.