题解 | 计算协方差矩阵

import numpy as np

def jia(vectors, a):
    return [i + a for i in vectors]

def dianji(a,b):
    if len(a) != len(b):
        return -1
    s = 0
    for j in range(len(a)):
        s += a[j] * b[j]
    return s

def cov(x,y):
    return dianji(jia(x, -sum(x)/len(x)),jia(y, -sum(y)/len(y))) / (len(x)-1)

def calculate_covariance_matrix(vectors):
    # 补全代码
    return [[cov(x,y) for x in vectors] for y in vectors]

# 主程序
if __name__ == "__main__":
    # 输入
    ndarrayA = input()

    # 处理输入
    import ast
    A = ast.literal_eval(ndarrayA)

    # 调用函数计算
    output = calculate_covariance_matrix(A)
    
    # 输出结果
    print(output)