题解 | 计算相关矩阵

import numpy as np

def calculate_correlation_matrix(X, Y=None):
	# Your code here
    m,p=X.shape
    x_mean=np.mean(X,axis=0)
    x_centered=X-x_mean
    std_x=np.std(x_centered,axis=0,ddof=1)
    if Y is None:
        y_centered=x_centered
        std_y=np.std(y_centered,axis=0,ddof=1)
    else:
        y_mean=np.mean(Y,axis=0)
        y_centered=Y-y_mean
        std_y=np.std(y_centered,axis=0,ddof=1)
    std_outer=np.outer(std_x,std_y)
    cov_matrix=x_centered.T@y_centered/(m-1)
    corr_matrix=cov_matrix/std_outer
    return corr_matrix
if __name__ == "__main__":
    X = np.array(eval(input()))
    print(calculate_correlation_matrix(X))