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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) `

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``)``   ` `# Random Variates``R ``=` `hypsecant .rvs(scale ``=` `2``,  size ``=` `10``)``print` `(``"Random Variates : \n"``, R)``  ` `# PDF``R ``=` `hypsecant .pdf(quantile, loc ``=` `0``, scale ``=` `1``)``print` `(``"\nProbability Distribution : \n"``, R)`

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))`

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

Output:

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