@saehrimnir/druidjs / Annoy

Class: Annoy<T>

Defined in: knn/Annoy.js:45

Annoy-style (Approximate Nearest Neighbors Oh Yeah) implementation using Random Projection Trees.

This implementation builds multiple random projection trees where each tree randomly selects two points and splits the space based on a hyperplane equidistant between them.

Key features:

• Multiple random projection trees for better recall
• Each tree uses random hyperplanes for splitting
• Priority queue search for better recall
• Combines results from all trees

Best suited for:

• High-dimensional data
• Approximate nearest neighbor search
• Large datasets
• When high recall is needed with approximate methods

Template

T

See

• https://github.com/spotify/annoy
• https://erikbern.com/2015/09/24/nearest-neighbors-and-vector-models-epilogue-curse-of-dimensionality.html

Extends

• KNN

Type Parameters

Type Parameter	Description
T extends number[] | Float64Array

Constructors

Constructor

new Annoy<T>(elements: T[], parameters?: Partial<ParametersAnnoy>): Annoy<T>;

Defined in: knn/Annoy.js:53

Creates a new Annoy-style index with random projection trees.

Parameters

Parameter	Type	Description
elements	T[]	Elements to index
parameters?	Partial<ParametersAnnoy>	Anything left out falls back to the documented default.

Returns

Annoy<T>

Overrides

KNN.constructor

Properties

Property	Type	Inherited from	Defined in
_elements	T[]	KNN._elements	knn/KNN.js:16
_maxPointsPerLeaf	number	-	knn/Annoy.js:76
_metric	Metric	-	knn/Annoy.js:74
_numTrees	number	-	knn/Annoy.js:75
_parameters	ParametersAnnoy	KNN._parameters	knn/KNN.js:18
_randomizer	Randomizer	KNN._randomizer	knn/Annoy.js:78
_seed	number	-	knn/Annoy.js:77
_type	"array" | "typed"	KNN._type	knn/KNN.js:20

Accessors

num_nodes

Get Signature

get num_nodes(): number;

Defined in: knn/Annoy.js:103

Get the total number of nodes in all trees.

Returns

number

---

num_trees

Get Signature

get num_trees(): number;

Defined in: knn/Annoy.js:95

Get the number of trees in the index.

Returns

number

Methods

add()

add(elements: T[]): Annoy<T>;

Defined in: knn/Annoy.js:126

Add elements to the Annoy index.

Parameters

Parameter	Type	Description
elements	T[]	-

Returns

Annoy<T>

---

search()

search(query: T, k?: number): {
  distance: number;
  element: T;
  index: number;
}[];

Defined in: knn/Annoy.js:281

Search for k approximate nearest neighbors.

Parameters

Parameter	Type	Default value	Description
query	T	undefined	-
k?	number	5	-

Returns

{ distance: number; element: T; index: number; }[]

Overrides

KNN.search

---

search_by_index()

search_by_index(i: number, k?: number): {
  distance: number;
  element: T;
  index: number;
}[];

Defined in: knn/KNN.js:77

Searches the k nearest neighbors of the element stored at index i.

The queried element is never part of the result. It is trivially its own closest neighbor at distance 0, which is never what a caller asking "what is this point near?" wants, so every caller used to strip it back out — each in its own, subtly different way. Note the asymmetry with search: an arbitrary query point has no "self" to exclude, so there k means "k results", while here it means "k neighbors".

The self match is removed by index — not by position, and not by looking for a zero distance. Position is wrong because an approximate index may order ties differently or miss the element altogether (one extra candidate is requested to cover that), and a zero distance is wrong because genuine duplicate points share it and must survive.

Parameters

Parameter	Type	Default value	Description
i	number	undefined	Index of the query element.
k?	number	5	Number of neighbors to return. Default is 5

Returns

{ distance: number; element: T; index: number; }[]

The k nearest other elements, closest first. Empty when i is out of range.

Inherited from

KNN.search_by_index

---

search_index()

search_index(i: number, k?: number): {
  distance: number;
  element: T;
  index: number;
}[];

Defined in: knn/Annoy.js:402

Alias for search_by_index for backward compatibility.

Parameters

Parameter	Type	Default value	Description
i	number	undefined	Index of the query element
k?	number	5	Number of nearest neighbors to return

Returns

{ distance: number; element: T; index: number; }[]