如何降低正态分布曲线的高度

import numpy as np
import matplotlib.pyplot as plt

# 设置均值和标准差
mu = 0
sigma1 = 1
sigma2 = 2

# 生成数据点
x = np.linspace(mu - 4*sigma2, mu + 4*sigma2, 100)

# 计算概率密度函数值
y1 = (1/(sigma1 * np.sqrt(2 * np.pi))) * np.exp(-0.5 * ((x - mu)/sigma1)**2)
y2 = (1/(sigma2 * np.sqrt(2 * np.pi))) * np.exp(-0.5 * ((x - mu)/sigma2)**2)

# 绘制曲线
plt.plot(x, y1, label=f'sigma = {sigma1}')
plt.plot(x, y2, label=f'sigma = {sigma2}')
plt.legend()
plt.title('Normal Distribution with Different Standard Deviations')
plt.xlabel('Value')
plt.ylabel('Probability Density')
plt.show()