cmpstr/dist/esm/metric/DamerauLevenshtein.mjs

CmpStr is a lightweight, fast and well performing package for calculating string similarity

// CmpStr v3.2.2 build-bb61120-260311 by Paul Köhler @komed3 / MIT License
import { Pool } from '../utils/Pool.mjs';
import { MetricRegistry, Metric } from './Metric.mjs';

class DamerauLevenshteinDistance extends Metric {
  constructor(a, b, opt = {}) {
    super('damerau', a, b, opt, true);
  }
  compute(a, b, m, n, maxLen) {
    const len = m + 1;
    const [test, prev, curr] = Pool.acquireMany('int32', [len, len, len]);
    try {
      for (let i = 0; i <= m; i++) prev[i] = i;
      for (let j = 1; j <= n; j++) {
        curr[0] = j;
        const cb = b.charCodeAt(j - 1);
        for (let i = 1; i <= m; i++) {
          const ca = a.charCodeAt(i - 1);
          const cost = ca === cb ? 0 : 1;
          let val = Math.min(curr[i - 1] + 1, prev[i] + 1, prev[i - 1] + cost);
          if (
            i > 1 &&
            j > 1 &&
            ca === b.charCodeAt(j - 2) &&
            cb === a.charCodeAt(i - 2)
          )
            val = Math.min(val, test[i - 2] + cost);
          curr[i] = val;
        }
        test.set(prev);
        prev.set(curr);
      }
      const dist = prev[m];
      return {
        res: maxLen === 0 ? 1 : Metric.clamp(1 - dist / maxLen),
        raw: { dist, maxLen }
      };
    } finally {
      Pool.release('int32', test, len);
      Pool.release('int32', prev, len);
      Pool.release('int32', curr, len);
    }
  }
}
MetricRegistry.add('damerau', DamerauLevenshteinDistance);

export { DamerauLevenshteinDistance };