scipy stats.fatiguelife () | python

scipy.stats.fatiguelife () — continuous random variable for fatigue (Birnbaum-Sanders), which is defined by a standard format and some form 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: fatigue-life (Birnbaum-Sanders) continuous random variable

Code # 1: Generating a continuous random fatigue life

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

Output:

 RV: "scipy.stats._distn_infrastructure.rv_frozen object at 0x0000018D567B8400" 

Code # 2: Random Variations in Fatigue and Probability Distribution.

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

Output:

 Random Variates: [1.5759368 1.73788302 2.31297609 1.0005871 1.49635022 11.98492239 2.51785146 4.0096255 0.5654246 0.97502712 ] Probability Distribution: [3.74431292e-278 2.59381847e-002 6.41771315e-001 9.56754833e-001 9.63413710e-001 8 .86691481e-001 7.98585419e-001 7.17860186e-001 6.48103032e-001 5.88743459e-001] 

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 (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: Various Positional Arguments

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

Output: