[人工智能]Python | scipy实现连续型概率分布-正态分布

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

'''1、定义随机变量'''
# 平均值
mu=0 
# 标准差
sigma=1
x=np.arange(-5,5,0.1)
x

array([-5.00000000e+00, -4.90000000e+00, -4.80000000e+00, -4.70000000e+00,
       -4.60000000e+00, -4.50000000e+00, -4.40000000e+00, -4.30000000e+00,
       -4.20000000e+00, -4.10000000e+00, -4.00000000e+00, -3.90000000e+00,
       -3.80000000e+00, -3.70000000e+00, -3.60000000e+00, -3.50000000e+00,
       -3.40000000e+00, -3.30000000e+00, -3.20000000e+00, -3.10000000e+00,
       -3.00000000e+00, -2.90000000e+00, -2.80000000e+00, -2.70000000e+00,
       -2.60000000e+00, -2.50000000e+00, -2.40000000e+00, -2.30000000e+00,
       -2.20000000e+00, -2.10000000e+00, -2.00000000e+00, -1.90000000e+00,
       -1.80000000e+00, -1.70000000e+00, -1.60000000e+00, -1.50000000e+00,
       -1.40000000e+00, -1.30000000e+00, -1.20000000e+00, -1.10000000e+00,
       -1.00000000e+00, -9.00000000e-01, -8.00000000e-01, -7.00000000e-01,
       -6.00000000e-01, -5.00000000e-01, -4.00000000e-01, -3.00000000e-01,
       -2.00000000e-01, -1.00000000e-01, -1.77635684e-14,  1.00000000e-01,
        2.00000000e-01,  3.00000000e-01,  4.00000000e-01,  5.00000000e-01,
        6.00000000e-01,  7.00000000e-01,  8.00000000e-01,  9.00000000e-01,
        1.00000000e+00,  1.10000000e+00,  1.20000000e+00,  1.30000000e+00,
        1.40000000e+00,  1.50000000e+00,  1.60000000e+00,  1.70000000e+00,
        1.80000000e+00,  1.90000000e+00,  2.00000000e+00,  2.10000000e+00,
        2.20000000e+00,  2.30000000e+00,  2.40000000e+00,  2.50000000e+00,
        2.60000000e+00,  2.70000000e+00,  2.80000000e+00,  2.90000000e+00,
        3.00000000e+00,  3.10000000e+00,  3.20000000e+00,  3.30000000e+00,
        3.40000000e+00,  3.50000000e+00,  3.60000000e+00,  3.70000000e+00,
        3.80000000e+00,  3.90000000e+00,  4.00000000e+00,  4.10000000e+00,
        4.20000000e+00,  4.30000000e+00,  4.40000000e+00,  4.50000000e+00,
        4.60000000e+00,  4.70000000e+00,  4.80000000e+00,  4.90000000e+00])

'''2、概率密度函数PDF'''
y=stats.norm.pdf(x,mu,sigma)

'''3、绘图'''
fig=plt.figure()
plt.plot(x,y)
plt.xlabel('随机变量：x')
plt.ylabel('概率：y')
plt.title('正态分布：$\mu$=%.1f,$\sigma^2$=%.1f' % (mu,sigma))
plt.show()