scipy stats.halfgennorm() | Python
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)
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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 )
R = halfgennorm .rvs(. 2 , scale = 2 , size = 10 )
print ( "Random Variates : \n" , R)
R = halfgennorm .pdf(quantile, . 2 , loc = 0 , scale = 1 )
print ( "\nProbability Distribution : \n" , R)
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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))
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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 )
y1 = halfgennorm .pdf(x, 1 , 3 )
y2 = halfgennorm .pdf(x, 1 , 4 )
plt.plot(x, y1, "*" , x, y2, "r--" )
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Output:
Last Updated :
07 Jun, 2019
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