Python Scipy stats.chi()用法及代码示例

scipy.stats.chi()是chi连续随机变量，已使用标准格式和一些形状参数定义以完成其规格。

特别案例：

• chi(1，loc，scale)=半正态
• chi(2，0，scale)=瑞利
• chi(3，0，scale)：麦克斯韦

代码1：创建chi连续随机变量

# importing scipy 
from scipy.stats import chi  
  
numargs = chi.numargs 
[a] = [0.6, ] * numargs 
rv = chi(a) 
  
print ("RV : \n", rv) 

输出：

RV : 
 <scipy.stats._distn_infrastructure.rv_frozen object at 0x000002948537C6D8>

代码2：chi随机变量和概率分布。

import numpy as np 
quantile = np.arange (0.01, 1, 0.1) 
   
# Random Variates 
R = chi.rvs(a, scale = 2,  size = 10) 
print ("Random Variates : \n", R) 
  
# PDF 
R = chi.pdf(a, quantile, loc = 0, scale = 1) 
print ("\nProbability Distribution : \n", R)

输出：

Random Variates : 
 [2.40483665 1.68478304 0.01664071 2.48977805 3.66286843 1.68463842
 0.14434643 0.67812242 0.46190886 1.99973997]

Probability Distribution : 
 [0.01384193 0.14349716 0.25719966 0.35519439 0.43801475 0.50641521
 0.56131243 0.60373433 0.63477687 0.65556791]
 

代码3：图形表示。

import numpy as np 
import matplotlib.pyplot as plt 
  
distribution = np.linspace(0, np.minimum(rv.dist.b, 5)) 
print("Distribution : \n", distribution) 
  
plot = plt.plot(distribution, rv.pdf(distribution))

输出：

Distribution : 
Distribution : 
 [0.         0.10204082 0.20408163 0.30612245 0.40816327 0.51020408
 0.6122449  0.71428571 0.81632653 0.91836735 1.02040816 1.12244898
 1.2244898  1.32653061 1.42857143 1.53061224 1.63265306 1.73469388
 1.83673469 1.93877551 2.04081633 2.14285714 2.24489796 2.34693878
 2.44897959 2.55102041 2.65306122 2.75510204 2.85714286 2.95918367
 3.06122449 3.16326531 3.26530612 3.36734694 3.46938776 3.57142857
 3.67346939 3.7755102  3.87755102 3.97959184 4.08163265 4.18367347
 4.28571429 4.3877551  4.48979592 4.59183673 4.69387755 4.79591837
 4.89795918 5.        ]

代码4：改变位置参数

import matplotlib.pyplot as plt 
import numpy as np 
  
x = np.linspace(0, 5, 100) 
  
# Varying positional arguments 
y1 = chi.pdf(x, 1, 6) 
y2 = chi.pdf(x, 1, 4) 
plt.plot(x, y1, "*", x, y2, "r--")

输出：