Python Scipy stats.chi()用法及代碼示例

scipy.stats.chi()是chi連續隨機變量，已使用標準格式和一些形狀參數定義以完成其規格。

特別案例：

• chi(1，loc，scale)=半正態
• chi(2，0，scale)=瑞利
• chi(3，0，scale)：麥克斯韋

代碼1：創建chi連續隨機變量

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

輸出：

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

代碼2：chi隨機變量和概率分布。

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)

輸出：

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]
 

代碼3：圖形表示。

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))

輸出：

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.        ]

代碼4：改變位置參數

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--")

輸出：