  # scipy stats.fatiguelife () | python

NumPy | Python Methods and Functions

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: & lt; scipy.stats._distn_infrastructure.rv_frozen object at 0x0000018D567B8400 & gt; `

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: