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scipy stats.halfnorm() | Python

  • Last Updated : 27 Mar, 2019

scipy.stats.halfnorm() is an Half-normal continuous random variable that is defined with a standard format and some shape parameters to complete its specification.

Parameters :
-> q : lower and upper tail probability
-> x : quantiles
-> loc : [optional]location parameter. Default = 0
-> scale : [optional]scale parameter. Default = 1
-> size : [tuple of ints, optional] shape or random variates.
-> moments : [optional] composed of letters [‘mvsk’]; ‘m’ = mean, ‘v’ = variance, ‘s’ = Fisher’s skew and ‘k’ = Fisher’s kurtosis. (default = ‘mv’).

Results : Half-normal continuous random variable

Code #1 : Creating Half-normal continuous random variable






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

Output :

RV : 
 <scipy.stats._distn_infrastructure.rv_frozen object at 0x000001E39B53B630>

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




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

Output :

Random Variates : 
 [3.95023511 1.97013912 2.00977927 1.88217027 2.24680027 0.7298033
 0.56769996 0.62071753 1.74743798 0.35512999]

Probability Distribution : 
 [0.79784467 0.79307193 0.78048376 0.76045271 0.73356332 0.70058376
 0.66242936 0.62012057 0.57473779 0.52737608]

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

Output :

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