scipy stats.halfgennorm() | Python

scipy.stats.halfgennorm()是广义正态连续随机变量的上半部分。为了完成其规范，它使用标准格式和一些形状参数进行定义。对象对象从它继承了一组通用方法，并用特定的细节来完成它们。

参数 ：

-> α : scale
-> β : shape
-> μ : location

代码 #1：创建半广义正态连续随机变量

from scipy.stats import halfgennorm  
   
numargs = halfgennorm.numargs
[a] = [0.7, ] * numargs
rv = halfgennorm (a)
   
print ("RV : \n", rv) 

输出：

RV : 
 scipy.stats._distn_infrastructure.rv_frozen object at 0x0000021FB55D8DD8

代码#2：半广义随机变量和概率分布

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

输出：

Random Variates : 
 [1.41299459e+03 3.51301175e+04 1.79981484e+05 2.90925518e+02
 2.70178121e+05 1.31706797e+05 3.25898913e+01 1.62607410e+04
 2.02263946e+04 1.97078668e+04]

Probability Distribution : 
 [0.00559658 0.0043805  0.00400834 0.0037776  0.00360957 0.00347731
 0.00336825 0.00327549 0.00319482 0.00312348]

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.         0.06122449 0.12244898 0.18367347 0.24489796 0.30612245
 0.36734694 0.42857143 0.48979592 0.55102041 0.6122449  0.67346939
 0.73469388 0.79591837 0.85714286 0.91836735 0.97959184 1.04081633
 1.10204082 1.16326531 1.2244898  1.28571429 1.34693878 1.40816327
 1.46938776 1.53061224 1.59183673 1.65306122 1.71428571 1.7755102
 1.83673469 1.89795918 1.95918367 2.02040816 2.08163265 2.14285714
 2.20408163 2.26530612 2.32653061 2.3877551  2.44897959 2.51020408
 2.57142857 2.63265306 2.69387755 2.75510204 2.81632653 2.87755102
 2.93877551 3.        ]

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

输出：