ai-zero-shot-classifier/dist/utils/similarityFunctions/euclideanDistance.js

🧠 powerful JavaScript library that leverages advanced AI embeddings to perform zero-shot text classification. Whether you're dealing with unlabelled data or seeking to classify text against dynamic and user-defined labels, this library provides a seamles

"use strict";

Object.defineProperty(exports, "__esModule", {
  value: true
});
exports.default = euclideanDistance;
/**
 * Computes the Euclidean distance between two numerical vectors.
 *
 * @param {number[]} a - The first input vector.
 * @param {number[]} b - The second input vector.
 * @returns {number} - The Euclidean distance between vectors `a` and `b`.
 *                      Returns 0 if both vectors are zero or identical.
 *
 * @complexity
 * Time Complexity: O(n)
 *   - The function processes each element of the vectors `a` and `b` exactly once in a single loop.
 *
 * Space Complexity: O(1)
 *   - The function uses a constant amount of extra space regardless of the input size.
 */
function euclideanDistance(a, b) {
  // Ensure vectors are of the same length
  if (a.length !== b.length) {
    throw new Error('Vectors must be of the same length');
  }
  var sumSquaredDifferences = 0;

  // Compute the sum of squared differences
  for (var i = 0; i < a.length; i += 1) {
    var difference = a[i] - b[i];
    sumSquaredDifferences += difference * difference;
  }

  // Return the square root of the sum of squared differences
  return Math.sqrt(sumSquaredDifferences);
}
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