如何检查两个不等长的子列表的相似性，并在列表1中有匹配时添加到列表2的分数？

import numpy as np
import Levenshtein

def calculate_similarity(list1, list2):
    similarity_matrix = np.zeros((len(list1), len(list2)))  # 创建相似度矩阵

    for i, sublist1 in enumerate(list1):
        for j, sublist2 in enumerate(list2):
            similarity_matrix[i, j] = Levenshtein.distance(sublist1, sublist2)

    max_similarity_indices = np.argmin(similarity_matrix, axis=1)  # 找到每个子列表的最佳匹配索引

    for i, sublist1 in enumerate(list1):
        sublist2 = list2[max_similarity_indices[i]]
        similarity_score = 1 - similarity_matrix[i, max_similarity_indices[i]] / max(len(sublist1), len(sublist2))
        if similarity_score > threshold:  # 根据阈值判断是否添加分数
            # 将分数添加到列表2中的相应位置
            list2[max_similarity_indices[i]] += similarity_score

    return list2