scipy stats.halfnorm () | python

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: Create a half-normal continuous random variable

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

Output:

 RV: "scipy.stats._distn_infrastructure.rv_frozen object at 0x000001E39B53B630" 

Code # 2: Seminormal Random Variables and Probability Distribution

import numpy as np quantile = np.arange ( 0.01 , 1 , 0.1 )   # Random Variants R = halfnorm.rvs (scale = 2 , size = 10 ) pr int ( "Random Variates:" , R)   # PDF R = halfnorm.pdf (quantile, loc = 0 , scale = 1 ) print ( "Probability Distribution:" , 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: Graphic representation.

import numpy as np import matplotlib.pyplot as plt   distribution = np.linspace ( 0 , np.minimum (rv.dist.b, 3 )) print ( "Distribution:" , distribution)   plot = plt.plot (distribution, rv.pdf (distributi on))

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: Various Positional Arguments

import matplotlib. pyplot as plt import numpy as np   x = np.linspace ( 0 , 5 , 100 )   # Various positional arguments y1 = halfnorm.pdf (x, 1 , 3 ) y2 = halfnorm.pdf (x, 1 , 4 ) plt.plot (x, y1, "* " , x, y2, " r-- " )

Output: