python中实现Mann-Kendall趋势检验代码

以下是Python中实现Mann-Kendall趋势检验的代码示例：

import numpy as np
from scipy.stats import norm

def mann_kendall(x):
    n = len(x)
    s = np.zeros((n, n))
    for i in range(n):
        for j in range(i+1, n):
            sgn = np.sign(x[j] - x[i])
            s[i, j] = sgn
            for k in range(i+1, j):
                s[k, j] += sgn
    sn = s.sum()
    var_sn = n*(n-1)*(2*n+5)/18
    if sn > 0:
        z = (sn-1)/np.sqrt(var_sn)
    elif sn == 0:
        z = 0
    else:
        z = (sn+1)/np.sqrt(var_sn)
    p = 2*(1-norm.cdf(abs(z)))
    return z, p

该函数接受一维数组x作为输入，并返回Mann-Kendall趋势系数z和显著性水平p值。