scipy stats.hypsecant() | Python
Last Updated :
07 Jun, 2019
scipy.stats.hypsecant() is an hyperbolic secant continuous random variable. to complete its specificaitons it is defined with a standard format and some shape parameters. The probability density is defined in the “standardized” form.
Parameters :
-> α : scale
-> β : shape
-> μ : location
Code #1 : Creating Hyperbolic secant continuous random variable
from scipy.stats import hypsecant
numargs = hypsecant.numargs
[] = [ 0.7 , 0.4 ] * numargs
rv = hypsecant ()
print ( "RV : \n" , rv)
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Output:
RV :
scipy.stats._distn_infrastructure.rv_frozen object at 0x0000021FB588A160
Code #2 : Hyperbolic secant continuous variates and probability distribution
import numpy as np
quantile = np.arange ( 0.01 , 1 , 0.1 )
R = hypsecant .rvs(scale = 2 , size = 10 )
print ( "Random Variates : \n" , R)
R = hypsecant .pdf(quantile, loc = 0 , scale = 1 )
print ( "\nProbability Distribution : \n" , R)
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Output:
Random Variates :
[ 0.50120826 0.60225476 -0.38307417 7.15799321 -1.1929279 -2.03152053
-0.07410646 1.79859597 -3.14724818 2.03731139]
Probability Distribution :
[0.31829397 0.31639377 0.31141785 0.30360449 0.2933099 0.28097073
0.26706289 0.25206321 0.23641852 0.22052427]
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))
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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 )
y1 = hypsecant .pdf(x, 1 , 3 )
y2 = hypsecant .pdf(x, 1 , 4 )
plt.plot(x, y1, "*" , x, y2, "r--" )
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Output:
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