### Extend Float with AnnoyOperable

Source: https://github.com/jbadger3/swiftannoy/blob/master/docs/Extensions.html

This extension allows Float types to conform to the AnnoyOperable protocol. No specific setup is required beyond importing the SwiftAnnoy library.

```swift
extension Float: AnnoyOperable
```

--------------------------------

### onDiskBuild(url:)

Source: https://github.com/jbadger3/swiftannoy/blob/master/docs/Classes/AnnoyIndex.html

Configures the index to be built on disk instead of in memory.

```APIDOC
## onDiskBuild(url:)

### Description
Prepares the index to be built on disk rather than in RAM. Should be set before adding items to the index.

### Declaration
Swift
```swift
public func onDiskBuild(url: URL)
```

### Parameters
#### Path Parameters
- **url** (URL) - A file destination URL for the index.
```

--------------------------------

### save(url:prefault:)

Source: https://github.com/jbadger3/swiftannoy/blob/master/docs/Classes/AnnoyIndex.html

Saves the current index to a file and then immediately loads it from disk.

```APIDOC
## save(url:prefault:)

### Description
Saves the current index to a file then immediately loads (memory maps) the index from disk.

### Throws
`AnnoyIndexError.saveFailed`

### Parameters
- **url** (URL) - The URL of the file to save the index to.
- **prefault** (Bool) - Whether to prefault the index from disk. Defaults to false.
```

--------------------------------

### build(numTrees:)

Source: https://github.com/jbadger3/swiftannoy/blob/master/docs/Classes/AnnoyIndex.html

Builds the index to allow for fast approximate nearest neighbors lookup.

```APIDOC
## build(numTrees:)

### Description
Builds the index to allow for fast approximate nearest neighbors lookup. Using a larger number of trees to build the index will take longer, but will also lead to better accuracy during querying. You may need to experiment to find the right balance.

### Throws
`AnnoyIndexError.buildFailed`

### Parameters
- **numTrees** (Int) - The number of trees to use to build the index.
```

--------------------------------

### AnnoyIndex Initialization

Source: https://github.com/jbadger3/swiftannoy/blob/master/docs/Classes/AnnoyIndex.html

Initializes a new AnnoyIndex with a specified item length and distance metric.

```APIDOC
## init(itemLength:metric:)

### Description
Initializes a new AnnoyIndex with a specified item length and distance metric.

### Parameters
- **itemLength** (Int) - The vector length (Array.count) of each item stored in the index .
- **metric** (DistanceMetric) - The metric to be used to measure the distance between items. One of .angular, .dotProduct, .euclidean, or .manhattan. Defaults to .euclidean.
```

--------------------------------

### Build the Annoy Index

Source: https://github.com/jbadger3/swiftannoy/blob/master/docs/index.html

Build the Annoy index to enable querying. The numTrees parameter affects accuracy, build time, space, and search time.

```swift
try? index.build(numTrees: 1)
```

--------------------------------

### load(url:)

Source: https://github.com/jbadger3/swiftannoy/blob/master/docs/Classes/AnnoyIndex.html

Loads a previously saved Annoy index from a given URL.

```APIDOC
## load(url:)

### Description
Loads a previously saved index.

### Declaration
Swift
```swift
public func load(url: URL) throws
```

### Throws
AnnoyIndexError.loadFailed
```

--------------------------------

### Load Annoy Index

Source: https://github.com/jbadger3/swiftannoy/blob/master/README.md

Loads a previously saved Annoy index from a file URL. The index must be built before saving.

```swift
let fileURL = FileManager.default.temporaryDirectory.appending(path: "index.annoy")
try? index.load(fileURL)
```

--------------------------------

### Create an Annoy Index

Source: https://github.com/jbadger3/swiftannoy/blob/master/docs/index.html

Instantiate an AnnoyIndex with a specified item length and distance metric. Supported types are Float and Double.

```swift
let index = AnnoyIndex<Double>(itemLength: 2, metric: .euclidean)
```

--------------------------------

### addItems(items:)

Source: https://github.com/jbadger3/swiftannoy/blob/master/docs/Classes/AnnoyIndex.html

Adds multiple new items to the index.

```APIDOC
## addItems(items:)

### Description
Adds multiple new items to the index.

### Throws
`AnnoyIndexError.addIemFailed`

### Parameters
- **items** ([[T]]) - An Array of vectors to add to the index.
```

--------------------------------

### Add Items to Annoy Index

Source: https://github.com/jbadger3/swiftannoy/blob/master/docs/index.html

Populate an Annoy index using either addItem for single items or addItems for multiple items. Indices must be added in chronological order.

```swift
var item0 = [1.0, 1.0]
var item1 = [3.0, 4.0]
var item2 = [6.0, 8.0]
var items = [[item0, item1, item2]]

// add one item
try? index.addItem(index: 0, vector: &item0)

// add multple items
try? index.addItems(items: &items)
```

--------------------------------

### getNNsForItem(item:neighbors:search_k:)

Source: https://github.com/jbadger3/swiftannoy/blob/master/docs/Classes/AnnoyIndex.html

Gathers the approximate nearest neighbors for a given item in the index.

```APIDOC
## getNNsForItem(item:neighbors:search_k:)

### Description
Gathers the approximate nearest neighbors for an item.

### Declaration
Swift
```swift
public func getNNsForItem(item: Int, neighbors: Int, search_k: Int = -1) -> (indices: [Int], distances: [T])?
```

### Parameters
#### Path Parameters
- **item** (Int) - The index of the item of interest.
- **neighbors** (Int) - The number of neighbors to return.
- **search_k** (Int) - The number of nodes to inspect during search. search_k defaults to n * n_trees * D where n is the number of approximate nearest neighbors and D is a constant determined by Annoy based on the distance metric. In general, increasing search_k increases search time, but will give more accurate results.

### Return Value
A tuple of arrays containing the item indicies and distances.
```

--------------------------------

### unbuild()

Source: https://github.com/jbadger3/swiftannoy/blob/master/docs/Classes/AnnoyIndex.html

Unbuilds the current AnnoyIndex, allowing additional items to be added or for the index to be rebuilt.

```APIDOC
## unbuild()

### Description
Unbuilds the current AnnoyIndex which allows additional items to be added or for the index to be rebuilt with a different number of trees.

### Throws
`AnnoyIndexError.UnbuildFailed`
```

--------------------------------

### Save Annoy Index

Source: https://github.com/jbadger3/swiftannoy/blob/master/README.md

Saves the current state of the Annoy index to a specified file URL. Ensure the file path is valid.

```swift
let fileURL = FileManager.default.temporaryDirectory.appending(path: "index.annoy")
try? index.save(fileURL)
```

--------------------------------

### setVerbos(boolVal:)

Source: https://github.com/jbadger3/swiftannoy/blob/master/docs/Classes/AnnoyIndex.html

Enables or disables verbose output for Annoy operations.

```APIDOC
## setVerbos(boolVal:)

### Description
When set to true provides additional information about operations carried out by Annoy via stdout.

### Declaration
Swift
```swift
public func setVerbos(boolVal: Bool)
```
```

--------------------------------

### Query Annoy Index by Vector

Source: https://github.com/jbadger3/swiftannoy/blob/master/README.md

Finds the nearest neighbors for a given vector. Requires the index to be built first.

```swift
// by vector
var vector = [3.0, 4.0]
let results2 = index.getNNsForVector(vector: &vector, neighbors: 3)
print(results2)
"Optional((indices: [2, 0, 1], distances: [0.0, 3.605551275463989, 3.605551275463989]))"
```

--------------------------------

### Query Annoy Index by Item

Source: https://github.com/jbadger3/swiftannoy/blob/master/README.md

Finds the nearest neighbors for a given item index. Requires the index to be built first.

```swift
// by item
let results =  index.getNNsForItem(item: 3, neighbors: 3)
print(results)
"Optional((indices: [3, 2, 0], distances: [0.0, 5.0, 8.602325267042627]))"
```

--------------------------------

### AnnoyIndexError LocalizedError Implementation

Source: https://github.com/jbadger3/swiftannoy/blob/master/docs/Enums/AnnoyIndexError.html

Provides a localized description for AnnoyIndex errors, conforming to the LocalizedError protocol.

```swift
public var errorDescription: String? { get }
```

--------------------------------

### AnnoyIndex

Source: https://github.com/jbadger3/swiftannoy/blob/master/docs/Classes.html

The primary generic class used to create an index. It is generic over a type T that conforms to the AnnoyOperable protocol.

```APIDOC
## Class AnnoyIndex<T: AnnoyOperable>

### Description

The primary generic class used to create an index.

### Declaration

```swift
public class AnnoyIndex<T> where T : AnnoyOperable
```
```

--------------------------------

### addItem(index:vector:)

Source: https://github.com/jbadger3/swiftannoy/blob/master/docs/Classes/AnnoyIndex.html

Adds a new item to the index with a specified index and vector.

```APIDOC
## addItem(index:vector:)

### Description
Adds a new item to the index.

### Throws
`AnnoyIndexError.addItemFailed`

### Parameters
- **index** (Int) - The index (integer) to assign to the item.
- **vector** ([T]) - Array representing the feature vector for the item.
```

--------------------------------

### DistanceMetric Enumeration

Source: https://github.com/jbadger3/swiftannoy/blob/master/docs/Classes/AnnoyIndex/DistanceMetric.html

The DistanceMetric enumeration defines the supported distance metrics for AnnoyIndex. These include angular, dotProduct, euclidean, and manhattan distances.

```APIDOC
## DistanceMetric

### Description

Supported distance metrics / similarity measures.

### Cases

- **angular**
  The angular distance used is the Euclidean distance of normalized vectors, which is sqrt(2(1-cos(u,v)))

- **dotProduct**
  The dot product also called the inner product.

- **euclidean**
  The L2 or straight line distance as calculated using the Pythagorean formula

- **manhattan**
  The L1 or city block distance
```

--------------------------------

### Euclidean Distance Metric

Source: https://github.com/jbadger3/swiftannoy/blob/master/docs/Classes/AnnoyIndex/DistanceMetric.html

Represents the Euclidean (L2) distance metric, calculated using the Pythagorean formula.

```swift
case euclidean
```

--------------------------------

### setSeed(seedVal:)

Source: https://github.com/jbadger3/swiftannoy/blob/master/docs/Classes/AnnoyIndex.html

Sets the random seed for index generation to ensure reproducible results.

```APIDOC
## setSeed(seedVal:)

### Description
Sets the random seed used for generating the index. Setting this value is useful when running performance testing to ensure consistent results.

### Declaration
Swift
```swift
public func setSeed(seedVal: Int)
```
```

--------------------------------

### getItem(index:)

Source: https://github.com/jbadger3/swiftannoy/blob/master/docs/Classes/AnnoyIndex.html

Retrieves the vector associated with a specific item index.

```APIDOC
## getItem(index:)

### Description
Retrieves the vector for an item in the index.

### Declaration
Swift
```swift
public func getItem(index: Int) -> [T]?
```

### Parameters
#### Path Parameters
- **index** (Int) - The index of the item to retrieve

### Return Value
The vector associated with the item or nil if not found.
```

--------------------------------

### Extend Double with AnnoyOperable

Source: https://github.com/jbadger3/swiftannoy/blob/master/docs/Extensions.html

This extension enables Double types to conform to the AnnoyOperable protocol. Ensure the SwiftAnnoy library is imported for this functionality.

```swift
extension Double: AnnoyOperable
```

--------------------------------

### Query Annoy Index by Vector

Source: https://github.com/jbadger3/swiftannoy/blob/master/docs/index.html

Retrieve nearest neighbors for a given vector. This method returns optional indices and distances.

```swift
var vector = [3.0, 4.0]
let results2 = index.getNNsForVector(vector: &vector, neighbors: 3)
print(results2)
"Optional((indices: [2, 0, 1], distances: [0.0, 3.605551275463989, 3.605551275463989]))"
```

--------------------------------

### getDistance(item1:item2:)

Source: https://github.com/jbadger3/swiftannoy/blob/master/docs/Classes/AnnoyIndex.html

Calculates the distance between two items in the index.

```APIDOC
## getDistance(item1:item2:)

### Description
Calculates the distance between two items in the index.

### Declaration
Swift
```swift
public func getDistance(item1: Int, item2: Int) -> T?
```

### Parameters
#### Path Parameters
- **item1** (Int) - The index of first item of inerest.
- **item2** (Int) - The index of the second item of interest.

### Return Value
The distance between the two items or nil if one of the items is not in the index.
```

--------------------------------

### AnnoyIndexError Cases

Source: https://github.com/jbadger3/swiftannoy/blob/master/docs/Enums/AnnoyIndexError.html

Defines the possible errors that can occur when using AnnoyIndex.

```swift
case invalidVectorLength(message: String)
```

```swift
case addItemFailed
```

```swift
case buildFailed
```

```swift
case unbuildFailed
```

```swift
case saveFailed
```

```swift
case loadFailed
```

--------------------------------

### Query Annoy Index by Item

Source: https://github.com/jbadger3/swiftannoy/blob/master/docs/index.html

Retrieve nearest neighbors for a given item index. This method returns optional indices and distances.

```swift
let results =  index.getNNsForItem(item: 3, neighbors: 3)
print(results)
"Optional((indices: [3, 2, 0], distances: [0.0, 5.0, 8.602325267042627]))"
```

--------------------------------

### getNNsForVector(vector:neighbors:search_k:)

Source: https://github.com/jbadger3/swiftannoy/blob/master/docs/Classes/AnnoyIndex.html

Gathers the approximate nearest neighbors for a given vector.

```APIDOC
## getNNsForVector(vector:neighbors:search_k:)

### Description
Gathers the approximate nearest neighbors for a vector.

### Declaration
Swift
```swift
public func getNNsForVector(vector: inout [T], neighbors: Int, search_k: Int = -1) -> (indices: [Int], distances: [T])?
```

### Parameters
#### Path Parameters
- **vector** (inout [T]) - The vector of interest.
- **neighbors** (Int) - The number of neighbors to return.
- **search_k** (Int) - The number of nodes to inspect during search. search_k defaults to n * n_trees * D where n is the number of approximate nearest neighbors and D is a constant determined by Annoy based on the distance metric. In general, increasing search_k increases search time, but will give more accurate results.

### Return Value
A tuple of arrays containing the item indicies and distances.
```

--------------------------------

### Dot Product Distance Metric

Source: https://github.com/jbadger3/swiftannoy/blob/master/docs/Classes/AnnoyIndex/DistanceMetric.html

Represents the dot product (inner product) distance metric.

```swift
case dotProduct
```

--------------------------------

### unload()

Source: https://github.com/jbadger3/swiftannoy/blob/master/docs/Classes/AnnoyIndex.html

Unloads the underlying index and all associated items from memory.

```APIDOC
## unload()

### Description
Unloads the underlying index and all associated items.

### Declaration
Swift
```swift
public func unload()
```
```

--------------------------------

### AnnoyIndexError

Source: https://github.com/jbadger3/swiftannoy/blob/master/docs/Enums.html

Errors thrown by AnnoyIndex operations.

```APIDOC
## AnnoyIndexError

### Description
Errors thrown by AnnoyIndex.

### Values
- `invalidVectorLenght`
- `addItemFailed`
- `buildFailed`
- `unbuildFailed`
- `saveFailed`
- `loadFailed`

### Declaration
Swift
```swift
public enum AnnoyIndexError : Error, LocalizedError
```
```

--------------------------------

### AnnoyIndex Class Declaration

Source: https://github.com/jbadger3/swiftannoy/blob/master/docs/Classes.html

This is the declaration for the primary generic AnnoyIndex class. It is used to create an index and requires its generic type T to conform to the AnnoyOperable protocol.

```swift
public class AnnoyIndex<T> where T : AnnoyOperable
```

--------------------------------

### Manhattan Distance Metric

Source: https://github.com/jbadger3/swiftannoy/blob/master/docs/Classes/AnnoyIndex/DistanceMetric.html

Represents the Manhattan (L1) distance metric, also known as the city block distance.

```swift
case manhattan
```

--------------------------------

### AnnoyIndexError Enumeration

Source: https://github.com/jbadger3/swiftannoy/blob/master/docs/Enums/AnnoyIndexError.html

The AnnoyIndexError enumeration defines the specific errors that can occur during operations with the AnnoyIndex. These errors include issues with vector lengths, adding items, building or unbuilding the index, and saving or loading the index.

```APIDOC
## AnnoyIndexError Enumeration

### Description
This enumeration lists the errors that can be thrown by the AnnoyIndex class. It conforms to the `Error` and `LocalizedError` protocols.

### Cases

- **`invalidVectorLength(message: String)`**
  - Description: Undocumented. This case indicates an issue with the provided vector length.
  - Declaration:
    ```swift
    case invalidVectorLength(message: String)
    ```

- **`addItemFailed`**
  - Description: Undocumented. This case indicates that adding an item to the index failed.
  - Declaration:
    ```swift
    case addItemFailed
    ```

- **`buildFailed`**
  - Description: Undocumented. This case indicates that the index build process failed.
  - Declaration:
    ```swift
    case buildFailed
    ```

- **`unbuildFailed`**
  - Description: Undocumented. This case indicates that the unbuild process for the index failed.
  - Declaration:
    ```swift
    case unbuildFailed
    ```

- **`saveFailed`**
  - Description: Undocumented. This case indicates that saving the index failed.
  - Declaration:
    ```swift
    case saveFailed
    ```

- **`loadFailed`**
  - Description: Undocumented. This case indicates that loading the index failed.
  - Declaration:
    ```swift
    case loadFailed
    ```

### LocalizedError Conformance

- **`errorDescription`**
  - Description: Returns a localized description of the error.
  - Declaration:
    ```swift
    public var errorDescription: String? { get }
    ```
```

--------------------------------

### AnnoyIndexError Declaration

Source: https://github.com/jbadger3/swiftannoy/blob/master/docs/Enums.html

Shows the declaration of the AnnoyIndexError enumeration, which conforms to the Error and LocalizedError protocols. This error type is used for exceptions thrown by AnnoyIndex operations.

```swift
public enum AnnoyIndexError : Error, LocalizedError
```

--------------------------------

### Angular Distance Metric

Source: https://github.com/jbadger3/swiftannoy/blob/master/docs/Classes/AnnoyIndex/DistanceMetric.html

Represents the angular distance metric. This is calculated as the Euclidean distance of normalized vectors.

```swift
case angular
```

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