Calculate the Levenshtein distance between two strings using a two-row optimization
(source: string, target: string)
| 1 | /** |
| 2 | * Optimal string alignment distance (restricted Damerau–Levenshtein: handles |
| 3 | * substitution, insertion, deletion, and adjacent transposition). Bails out |
| 4 | * early, returning `max + 1`, once the distance is known to exceed `max`. |
| 5 | */ |
| 6 | export function osaDistance(a: string, b: string, max: number): number { |
| 7 | const la = a.length; |
| 8 | const lb = b.length; |
| 9 | if (Math.abs(la - lb) > max) return max + 1; |
| 10 | if (la === 0) return lb; |
| 11 | if (lb === 0) return la; |
| 12 | |
| 13 | let prevPrev = new Array<number>(lb + 1); |
| 14 | let prev = new Array<number>(lb + 1); |
| 15 | let curr = new Array<number>(lb + 1); |
| 16 | for (let j = 0; j <= lb; j++) prev[j] = j; |
| 17 | |
| 18 | for (let i = 1; i <= la; i++) { |
| 19 | curr[0] = i; |
| 20 | let rowMin = curr[0]; |
| 21 | for (let j = 1; j <= lb; j++) { |
| 22 | const cost = a[i - 1] === b[j - 1] ? 0 : 1; |
| 23 | let v = Math.min( |
| 24 | prev[j] + 1, // deletion |
| 25 | curr[j - 1] + 1, // insertion |
| 26 | prev[j - 1] + cost // substitution |
| 27 | ); |
| 28 | if (i > 1 && j > 1 && a[i - 1] === b[j - 2] && a[i - 2] === b[j - 1]) |
| 29 | v = Math.min(v, prevPrev[j - 2] + 1); // transposition |
| 30 | curr[j] = v; |
no test coverage detected