题解 | 计算相关矩阵

import numpy as np

def calculate_correlation_matrix(X, Y=None):
	# Your code here
    if Y is None:
        Y=X
    #X 是形如 [[1, 2], [3, 4], [5, 6]]，即 每行是一个样本，每列是一个特征
    # 转置：每行是一个变量，每列是一个样本
    X=X.T
    Y=Y.T
    d=X.shape[0]
    big=np.cov(X,Y,bias=True)
    cov_xy=big[:d,d:]
    # print(cov_xy)
    var_x=np.var(X,axis=1,ddof=0)
    var_y=np.var(Y,axis=1,ddof=0)
    # print(var_x)
    sqrtx=np.sqrt(var_x)
    sqrty=np.sqrt(var_y)
    return np.divide(cov_xy,np.outer(sqrtx,sqrty))


if __name__ == "__main__":
    X = np.array(eval(input()))
    print(calculate_correlation_matrix(X))