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scipy stats.halfgennorm() | Python
  • Last Updated : 07 Jun, 2019

scipy.stats.halfgennorm() is an upper half of a generalized normal continuous random variable. To complete its specificaitons, it is defined with a standard format and some shape parameters. The object object inherits from it a collection of generic methods and completes them with details specific.

Parameters :

-> α : scale
-> β : shape
-> μ : location
Code #1 : Creating Half-generalized normal continuous random variable




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

Output:

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

Code #2 : Half-generalized random variates and probability distribution






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)

Output:

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]

Code #3 : Graphical Representation.




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))

Output:

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.        ]

Code #4 : Varying Positional Arguments




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--")

Output:

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