/**
 * Compute the edit distance score matrix between two sequences x (hyp) and y (ref)
 * using only pure Python lists.
 *
 * @param ref The reference sequence/transcript.
 * @param hyp The hypothesis sequence/transcript.
 * @param scoreFunc A function that takes two tokens (refToken, hypToken) and returns
 *                  a tuple of (deletionCost, insertionCost, diagonalCost)
 * @param backtrace Whether to compute the backtrace matrix.
 * @returns The score matrix and optionally the backtrace matrix
 */
declare function computeDistanceMatrix(ref: string | string[], hyp: string | string[], scoreFunc: (refToken: string, hypToken: string) => [number, number, number]): number[][];
declare function computeDistanceMatrix(ref: string | string[], hyp: string | string[], scoreFunc: (refToken: string, hypToken: string) => [number, number, number], backtrace: boolean): {
    scoreMatrix: number[][];
    backtraceMatrix: number[][];
};
/**
 * Compute the Levenshtein distance matrix between two sequences.
 *
 * @param ref The reference sequence/transcript.
 * @param hyp The hypothesis sequence/transcript.
 * @param backtrace Whether to compute the backtrace matrix.
 *
 * @returns The score matrix and optionally the backtrace matrix
 */
declare function computeLevenshteinDistanceMatrix(ref: string | string[], hyp: string | string[]): number[][];
declare function computeLevenshteinDistanceMatrix(ref: string | string[], hyp: string | string[], backtrace: true): {
    scoreMatrix: number[][];
    backtraceMatrix: number[][];
};
/**
 * Compute the error alignment distance matrix between two sequences.
 *
 * @param ref The reference sequence/transcript.
 * @param hyp The hypothesis sequence/transcript.
 * @param backtrace Whether to compute the backtrace matrix.
 *
 * @returns The score matrix and optionally the backtrace matrix.
 */
declare function computeErrorAlignDistanceMatrix(ref: string | string[], hyp: string | string[]): number[][];
declare function computeErrorAlignDistanceMatrix(ref: string | string[], hyp: string | string[], backtrace: true): {
    scoreMatrix: number[][];
    backtraceMatrix: number[][];
};

export { computeDistanceMatrix, computeErrorAlignDistanceMatrix, computeLevenshteinDistanceMatrix };