我试图用beta分布拟合一些数据，然后绘制beta分布与数据的拟合程度。但是输出看起来很奇怪，而且不正确。

import scipy.stats as stats 
import matplotlib.pyplot as plt

x = np.array([0.9999999 , 0.9602287 , 0.8823198 , 0.83825594, 0.92847216,
       0.9632976 , 0.90275735, 0.8383094 , 0.9826664 , 0.9141795 ,
       0.88799196, 0.9272752 , 0.94456017, 0.90466917, 0.8905505 ,
       0.95424247, 0.781545  , 0.9489085 , 0.9578988 , 0.8644015 ])
beta_params = stats.beta.fit(x)
print(beta_params)

# (3.243900357315478, 1.5909897101396109, 0.7270083219563888, 0.27811444901271615

beta_pdf = stats.beta.pdf(x, beta_params[0], beta_params[1], beta_params[2], beta_params[3])

print(beta_pdf)

# [2.70181543 6.8442073  4.98204632 2.82445508 6.76055614 6.75910611

 #5.90419012 2.82696622 5.58521916 6.34096675 5.2508072  6.73212694
 #6.98854653 5.98225724 5.36937625 6.9519977  0.67812362 6.99116729
 #6.89484982 4.10113147]

plt.plot(x, beta_pdf)