dotProduct function exported ✓ 100.0%

Last updated: 2026-02-24T19:46:21.789Z

Location

src/lib/shared/ngram.ts:36-41

Metrics

LOC: 6 Complexity: 2 Params: 2 Coverage: 100.0% (4/4 lines, 3x executed)

Signature

dotProduct(a: Float32Array, b: Float32Array): : number

Summary

Computes the dot product between two L2-normalised vectors. Since vectors are expected to be L2-normalised beforehand, the dot product is equivalent to cosine similarity. Returns a similarity score in range [-1, 1]. For frequency-based n-gram vectors, the range will typically be [0, 1].

Source Code

export function dotProduct(a: Float32Array, b: Float32Array): number {
  let sum = 0;
  const len = Math.min(a.length, b.length);
  for (let i = 0; i < len; i++) sum += a[i] * b[i];
  return sum;
}

No outgoing dependencies.

Impact (Incoming)

graph LR dotProduct["dotProduct"] PretrainedState["PretrainedState"] resetModelMock["resetModelMock"] PretrainedState -->|uses| dotProduct resetModelMock -->|uses| dotProduct style dotProduct fill:#dbeafe,stroke:#2563eb,stroke-width:2px click dotProduct "964849590f3f9d32.html" click PretrainedState "5cefc72e50bf5399.html" click resetModelMock "4ef72c19f1c89871.html"
SourceType
PretrainedState uses
resetModelMock uses