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
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: