/**
 * Smith-Waterman Algorithm
 * src/metric/SmithWaterman.ts
 *
 * @see https://en.wikipedia.org/wiki/Smith%E2%80%93Waterman_algorithm
 *
 * The Smith-Waterman algorithm performs local alignment, finding the best matching
 * subsequence between two strings. It is commonly used in bioinformatics for local
 * sequence alignment. Instead of looking at the entire sequence, the Smith–Waterman
 * algorithm compares segments of all possible lengths and optimizes the similarity
 * measure.
 *
 * @module Metric
 * @name SmithWatermanDistance
 * @author Paul Köhler (komed3)
 * @license MIT
 */
import type { MetricCompute, MetricInput, MetricOptions } from '../utils/Types';
import { Metric } from './Metric';
export interface SmithWatermanRaw {
    score: number;
    denum: number;
}
/**
 * SmithWatermanDistance class extends the Metric class to implement the Smith-Waterman algorithm.
 */
export declare class SmithWatermanDistance extends Metric<SmithWatermanRaw> {
    /**
     * Constructor for the SmithWaterman class.
     *
     * Initializes the Smith-Waterman metric with two input strings or
     * arrays of strings and optional options.
     *
     * Metric is symmetrical.
     *
     * @param {MetricInput} a - First input string or array of strings
     * @param {MetricInput} b - Second input string or array of strings
     * @param {MetricOptions} [opt] - Options for the metric computation
     */
    constructor(a: MetricInput, b: MetricInput, opt?: MetricOptions);
    /**
     * Calculates the Smith-Waterman local alignment score between two strings.
     *
     * @param {string} a - First string
     * @param {string} b - Second string
     * @param {number} m - Length of the first string
     * @param {number} n - Length of the second string
     * @return {MetricCompute< SmithWatermanRaw >} - Object containing the similarity result and raw score
     */
    protected compute(a: string, b: string, m: number, n: number): MetricCompute<SmithWatermanRaw>;
}