如何为scipy.stats生成的直方图显示最佳拟合方程并计算r^2？

import numpy as np
import matplotlib.pyplot as plt
from scipy import stats

data = np.random.normal(0, 1, 1000)  # 生成1000个符合正态分布的随机数

plt.hist(data, bins='auto', density=True, alpha=0.7, rwidth=0.85)

mu, sigma = stats.norm.fit(data)  # 拟合数据到正态分布
x = np.linspace(min(data), max(data), 100)
y = stats.norm.pdf(x, mu, sigma)
plt.plot(x, y, 'r-', label='Normal Fit')

r_squared = stats.pearsonr(data, y)[0] ** 2

import numpy as np
import matplotlib.pyplot as plt
from scipy import stats

data = np.random.normal(0, 1, 1000)

plt.hist(data, bins='auto', density=True, alpha=0.7, rwidth=0.85)

mu, sigma = stats.norm.fit(data)
x = np.linspace(min(data), max(data), 100)
y = stats.norm.pdf(x, mu, sigma)
plt.plot(x, y, 'r-', label='Normal Fit')

r_squared = stats.pearsonr(data, y)[0] ** 2

plt.legend()
plt.show()

print("R-squared value:", r_squared)