📜  Python – 统计学中的三角分布

📅  最后修改于: 2022-05-13 01:55:05.616000             🧑  作者: Mango

Python – 统计学中的三角分布

scipy.stats.triang()是一个三角连续随机变量。它作为rv_continuous 类的实例继承自泛型方法。它使用特定于此特定发行版的详细信息来完成方法。

参数 :

代码#1:创建三角连续随机变量

# importing library
  
from scipy.stats import triang 
    
numargs = triang .numargs 
a = 0.158
rv = triang (a) 
    
print ("RV : \n", rv)  

输出 :

RV : 
 scipy.stats._distn_infrastructure.rv_frozen object at 0x000002A9D843A9C8

代码#2:三角连续变量和概率分布

import numpy as np 
quantile = np.arange (0.01, 1, 0.1) 
  
# Random Variates 
R = triang .rvs(0.158, size = 10) 
print ("Random Variates : \n", R) 
  
# PDF 
x = np.linspace(0, 5, 10) 
R = triang.pdf(x, 1)
print ("\nProbability Distribution : \n", R) 

输出 :

Random Variates : 
 [0.83667827 0.23988855 0.17637281 0.28973544 0.26458145 0.3554613
 0.09420123 0.20821321 0.3357951  0.1249713 ]

Probability Distribution : 
 [0.         1.11111111 0.         0.         0.         0.
 0.         0.         0.         0.        ]

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, 3)) 
print("Distribution : \n", distribution) 
     
plot = plt.plot(distribution, rv.pdf(distribution)) 

输出 :

Distribution : 
 [0.         0.02040816 0.04081633 0.06122449 0.08163265 0.10204082
 0.12244898 0.14285714 0.16326531 0.18367347 0.20408163 0.2244898
 0.24489796 0.26530612 0.28571429 0.30612245 0.32653061 0.34693878
 0.36734694 0.3877551  0.40816327 0.42857143 0.44897959 0.46938776
 0.48979592 0.51020408 0.53061224 0.55102041 0.57142857 0.59183673
 0.6122449  0.63265306 0.65306122 0.67346939 0.69387755 0.71428571
 0.73469388 0.75510204 0.7755102  0.79591837 0.81632653 0.83673469
 0.85714286 0.87755102 0.89795918 0.91836735 0.93877551 0.95918367
 0.97959184 1.        ]
  

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 = triang  .pdf(x, 1, 3, 5) 
y2 = triang  .pdf(x, 1, 4, 4) 
plt.plot(x, y1, "*", x, y2, "r--") 

输出 :