根据两个相似性矩阵的行标和列标，筛选两个相似性txt方矩阵共同存在的数据 并输出txt矩阵 python

以下是一个简单的实现：

def load_similarity_matrix(file_path):
    """从txt文件中加载相似性矩阵"""
    with open(file_path, "r") as f:
        lines = f.readlines()
    matrix = []
    for line in lines:
        row = [float(x) for x in line.strip().split()]
        matrix.append(row)
    return matrix

def filter_similarity_matrices(matrix1, matrix2):
    """根据两个相似性矩阵的行标和列标，筛选共同存在的数据"""
    filtered_matrix1 = []
    filtered_matrix2 = []
    for i in range(len(matrix1)):
        row1 = matrix1[i]
        row2 = matrix2[i]
        filtered_row1 = []
        filtered_row2 = []
        for j in range(len(row1)):
            if row1[j] != 0 and row2[j] != 0:
                filtered_row1.append(row1[j])
                filtered_row2.append(row2[j])
        filtered_matrix1.append(filtered_row1)
        filtered_matrix2.append(filtered_row2)
    return filtered_matrix1, filtered_matrix2

def save_similarity_matrix(matrix, file_path):
    """保存相似性矩阵到txt文件"""
    with open(file_path, "w") as f:
        for row in matrix:
            line = " ".join(str(x) for x in row)
            f.write(line + "\n")

# 加载相似性矩阵1
matrix1 = load_similarity_matrix("matrix1.txt")
# 加载相似性矩阵2
matrix2 = load_similarity_matrix("matrix2.txt")
# 筛选共同存在的数据
filtered_matrix1, filtered_matrix2 = filter_similarity_matrices(matrix1, matrix2)
# 保存筛选后的相似性矩阵1
save_similarity_matrix(filtered_matrix1, "filtered_matrix1.txt")
# 保存筛选后的相似性矩阵2
save_similarity_matrix(filtered_matrix2, "filtered_matrix2.txt")

这个实现假设两个相似性矩阵的行数和列数都相同。如果行数和列数不同，需要对实现进行修改。