/** * Levenshtein 距离算法 * 用于计算两个字符串之间的编辑距离 */ /** * 内部最小值计算函数 */ function _min(d0: number, d1: number, d2: number, bx: number, ay: number): number { return d0 < d1 || d2 < d1 ? d0 > d2 ? d2 + 1 : d0 + 1 : bx === ay ? d1 : d1 + 1; } /** * 计算两个字符串之间的 Levenshtein 距离 * @param a 第一个字符串 * @param b 第二个字符串 * @returns 编辑距离 */ export function levenshteinDistance(a: string, b: string): number { if (a === b) { return 0; } if (a.length > b.length) { const tmp = a; a = b; b = tmp; } let la = a.length; let lb = b.length; while (la > 0 && (a.charCodeAt(la - 1) === b.charCodeAt(lb - 1))) { la--; lb--; } let offset = 0; while (offset < la && (a.charCodeAt(offset) === b.charCodeAt(offset))) { offset++; } la -= offset; lb -= offset; if (la === 0 || lb < 3) { return lb; } let x = 0; let y: number; let d0: number; let d1: number; let d2: number; let d3: number; let dd = 0; let dy: number; let ay: number; let bx0: number; let bx1: number; let bx2: number; let bx3: number; const vector: number[] = []; for (y = 0; y < la; y++) { vector.push(y + 1); vector.push(a.charCodeAt(offset + y)); } const len = vector.length - 1; for (; x < lb - 3;) { bx0 = b.charCodeAt(offset + (d0 = x)); bx1 = b.charCodeAt(offset + (d1 = x + 1)); bx2 = b.charCodeAt(offset + (d2 = x + 2)); bx3 = b.charCodeAt(offset + (d3 = x + 3)); x += 4; dd = x; for (y = 0; y < len; y += 2) { dy = vector[y]; ay = vector[y + 1]; d0 = _min(dy, d0, d1, bx0, ay); d1 = _min(d0, d1, d2, bx1, ay); d2 = _min(d1, d2, d3, bx2, ay); dd = _min(d2, d3, dd, bx3, ay); vector[y] = dd; d3 = d2; d2 = d1; d1 = d0; d0 = dy; } } for (; x < lb;) { bx0 = b.charCodeAt(offset + (d0 = x)); dd = ++x; for (y = 0; y < len; y += 2) { dy = vector[y]; vector[y] = dd = _min(dy, d0, dd, bx0, vector[y + 1]); d0 = dy; } } return dd; }