Struct hnsw::Hnsw

pub struct Hnsw<Met, T, R, const M: usize, const M0: usize> { /* fields omitted */ }

This provides a HNSW implementation for any distance function.

The type T must implement space::Metric to get implementations.

Implementations

impl<Met, T, R, const M: usize, const M0: usize> Hnsw<Met, T, R, M, M0> where
    R: RngCore + SeedableRng, 

pub fn new(metric: Met) -> Self

Creates a new HNSW with a PRNG which is default seeded to produce deterministic behavior.

pub fn new_params(metric: Met, params: Params) -> Self

Creates a new HNSW with a default seeded PRNG and with the specified params.

impl<Met, T, R, const M: usize, const M0: usize> Hnsw<Met, T, R, M, M0> where
    R: RngCore,
    Met: Metric<T>, 

pub fn new_prng(metric: Met, prng: R) -> Self

Creates a HNSW with the passed prng.

pub fn new_params_and_prng(metric: Met, params: Params, prng: R) -> Self

Creates a HNSW with the passed params and prng.

pub fn insert(&mut self, q: T, searcher: &mut Searcher<Met::Unit>) -> usize

Inserts a feature into the HNSW.

pub fn nearest<'a>(
    &self,
    q: &T,
    ef: usize,
    searcher: &mut Searcher<Met::Unit>,
    dest: &'a mut [Neighbor<Met::Unit>]
) -> &'a mut [Neighbor<Met::Unit>]

Does a k-NN search where q is the query element and it attempts to put up to M nearest neighbors into dest. ef is the candidate pool size. ef can be increased to get better recall at the expense of speed. If ef is less than dest.len() then dest will only be filled with ef elements.

Returns a slice of the filled neighbors.

pub fn feature(&self, item: usize) -> &T

Extract the feature for a given item returned by [HNSW::nearest].

The item must be retrieved from [HNSW::search_layer].

pub fn layer_feature(&self, level: usize, item: usize) -> &T

Extract the feature from a particular level for a given item returned by [HNSW::search_layer].

pub fn layer_item_id(&self, level: usize, item: usize) -> usize

Retrieve the item ID for a given layer item returned by [HNSW::search_layer].

pub fn layers(&self) -> usize

pub fn len(&self) -> usize

pub fn layer_len(&self, level: usize) -> usize

pub fn is_empty(&self) -> bool

pub fn layer_is_empty(&self, level: usize) -> bool

pub fn search_layer<'a>(
    &self,
    q: &T,
    ef: usize,
    level: usize,
    searcher: &mut Searcher<Met::Unit>,
    dest: &'a mut [Neighbor<Met::Unit>]
) -> &'a mut [Neighbor<Met::Unit>]

Performs the same algorithm as [HNSW::nearest], but stops on a particular layer of the network and returns the unique index on that layer rather than the item index.

If this is passed a level of 0, then this has the exact same functionality as [HNSW::nearest] since the unique indices at layer 0 are the item indices.

Trait Implementations

impl<Met: Clone, T: Clone, R: Clone, const M: usize, const M0: usize> Clone for Hnsw<Met, T, R, M, M0>

fn clone(&self) -> Hnsw<Met, T, R, M, M0>

Returns a copy of the value.

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

Performs copy-assignment from source.

impl<Met, T, R, const M: usize, const M0: usize> Default for Hnsw<Met, T, R, M, M0> where
    R: RngCore + SeedableRng,
    Met: Default, 

fn default() -> Self

Returns the “default value” for a type.

impl<'de, Met, T, R, const M: usize, const M0: usize> Deserialize<'de> for Hnsw<Met, T, R, M, M0> where
    Met: Deserialize<'de>,
    T: Deserialize<'de>,
    R: Deserialize<'de>, 

fn deserialize<__D>(__deserializer: __D) -> Result<Self, __D::Error> where
    __D: Deserializer<'de>, 

Deserialize this value from the given Serde deserializer.

impl<Met, T, R, const M: usize, const M0: usize> Knn for Hnsw<Met, T, R, M, M0> where
    R: RngCore,
    Met: Metric<T>, 

type Ix = usize

type Metric = Met

type Point = T

type KnnIter = Vec<Neighbor<Met::Unit>>

fn knn(&self, query: &T, num: usize) -> Self::KnnIter

Get num nearest neighbors of target.

fn nn(
    &self,
    query: &Self::Point
) -> Option<Neighbor<<Self::Metric as Metric<Self::Point>>::Unit, Self::Ix>>

Get the nearest neighbor of target.

impl<Met, T, R, const M: usize, const M0: usize> KnnPoints for Hnsw<Met, T, R, M, M0> where
    R: RngCore,
    Met: Metric<T>, 

fn get_point(&self, index: usize) -> &T

Get a point using a neighbor index returned by Knn::knn or Knn::nn.

fn knn_points(
    &self,
    query: &Self::Point,
    num: usize
) -> Vec<(Neighbor<<Self::Metric as Metric<Self::Point>>::Unit, Self::Ix>, &Self::Point), Global>

Get num nearest neighbor points of target.

fn nn_point(
    &self,
    query: &Self::Point
) -> Option<(Neighbor<<Self::Metric as Metric<Self::Point>>::Unit, Self::Ix>, &Self::Point)>

Get the nearest neighbor point of target.

impl<Met, T, R, const M: usize, const M0: usize> Serialize for Hnsw<Met, T, R, M, M0> where
    Met: Serialize,
    T: Serialize,
    R: Serialize, 

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

Serialize this value into the given Serde serializer.