# BNNSNearestNeighborsLoad(_:_:_:) Adds new sample data to a k-nearest neighbors object. ``` func BNNSNearestNeighborsLoad(_ knn: BNNSNearestNeighbors?, _ n_new_samples: UInt32, _ data_ptr: UnsafeRawPointer) -> Int32 ``` ## Parameters `knn` The k-nearest neighbors object. `n_new_samples` The number of new samples. `data_ptr` A pointer to the sample data. This must point to `n_new_samples * n_features` elements. ## Return Value `0` when the load is successful; otherwise, a nonzero value. ## Discussion The following code generates eight 2D data points and loads them into a k-nearest neighbors object with a single call to the [`BNNSNearestNeighborsLoad(_:_:_:)`](/documentation/Accelerate/BNNSNearestNeighborsLoad(_:_:_:)) function. The code then computes the four nearest neighbors, based on Euclidean distance, to the sample data point at index 7 of the samples data. ```swift let samples: [Float] = [ 1, 2, // 0 7, 2, // 1 3, 4, // 2 8, 4, // 3 3, 7, // 4 7, 7, // 5 2, 8, // 6 2, 5 // 7 ] let maximumSampleCount: UInt32 = 8 let dimensionCount: UInt32 = 2 let nearestNeighborCount: UInt32 = 4 let knn = BNNSCreateNearestNeighbors( maximumSampleCount, dimensionCount, nearestNeighborCount, BNNSDataType.float, nil) defer { BNNSDestroyNearestNeighbors(knn) } BNNSNearestNeighborsLoad( knn, UInt32(samples.count) / dimensionCount, samples) var indices = [Int32](repeating: 0, count: Int(nearestNeighborCount)) var distances = [Float](repeating: 0, count: Int(nearestNeighborCount)) let sampleDataPointIndex = 7 BNNSNearestNeighborsGetInfo( knn, Int32(sampleDataPointIndex), &indices, &distances) ``` On return, the `indices` array contains the values `[7, 2, 4, 6]` and the distances array contains the values `[0.0, 1.4142135, 2.236068, 3.0]`.  --- Copyright © 2026 Apple Inc. All rights reserved. | [Terms of Use](https://www.apple.com/legal/internet-services/terms/site.html) | [Privacy Policy](https://www.apple.com/privacy/privacy-policy)