生成数据集

import scipy
import matplotlib.pyplot  as plt
# generate data with norm(mean = 0,std = 15)
data = scipy.stats.norm.rvs(loc = 0,scale = 15,size = 1000,random_state = 0)

执行KS测试

# perform KS test on your sample versus norm(10,5.5)
D, p = scipy.stats.kstest(data, 'norm', args= (10, 5.5))
test = 'Reject' if p < 0.05 else 'Not reject'
print(f'D-statistics: {D:.4f},\np-value: {p:.4f}, \ntest-result: {test}')

输出：
'D统计量：0.5091，p值：0.0000，检验结果：拒绝'

添加包含分布和数据的图

# draw a plot to see the distribution and your data hist
# draw a plot to see the distribution and your data hist
fig, ax = plt.subplots(1, 1)
x = np.linspace(data.min(),data.max(),100)
ax.plot(x, scipy.stats.norm.pdf(x,loc = 10, scale = 5.5), 'r-', color='green', lw=1, alpha=0.6, label='norm(10,5.5) pdf')
ax.hist(data, normed=True, histtype='stepfilled', bins=20, alpha=0.2, label='my data distribution')
ax.legend(loc='best', frameon=False)
plt.title('norm(10,5.5) vs. data')
plt.show()

如果发生错误，则'Polygon'对象没有属性'normed'
如果找到该属性，则normed=True，该属性已弃用，
更改为使用“密度=真”。
它将工作。