# numpy.hypot() in Python

numpy.exp2(arr1, arr2[, out]) = ufunc ‘hypot’) : This mathematical function helps user to calculate hypotenuse for the right angled triangle, given its side and perpendicular. Result is equivalent to Equivalent to sqrt(x1**2 + x2**2), element-wise.

Parameters :

```arr1, arr2  : [array_like] Legs(side and perpendicular) of triangle
out         : [ndarray, optional] Output array with result.
```

Return :

```An array having hypotenuse of the right triangle.
```

Code #1 : Working

 `# Python3 program explaining ` `# hypot() function ` ` `  `import` `numpy as np ` ` `  `leg1 ``=` `[``12``, ``3``, ``4``, ``6``] ` `print` `(``"leg1 array : "``, leg1) ` ` `  ` `  `leg2 ``=` `[``5``, ``4``, ``3``, ``8``] ` `print` `(``"leg2 array : "``, leg2) ` ` `  `result ``=` `np.hypot(leg1, leg2) ` `print``(``"\nHypotenuse is as follows :"``) ` `print``(result) `

Output :

```leg1 array :  [12, 3, 4, 6]
leg2 array :  [5, 4, 3, 8]

Hypotenuse is as follows :
[ 13.   5.   5.  10.]
```

Code #2 : Working with 2D array

 `# Python3 program explaining ` `# hypot() function ` ` `  `import` `numpy as np ` ` `  `leg1 ``=` `np.random.rand(``3``, ``4``) ` `print` `(``"leg1 array : \n"``, leg1) ` ` `  `leg2 ``=` `np.ones((``3``, ``4``)) ` `print` `(``"leg2 array : \n"``, leg2) ` ` `  `result ``=` `np.hypot(leg1, leg2) ` `print``(``"\nHypotenuse is as follows :"``) ` `print``(result) `

Output :

```leg1 array :
[[ 0.57520509  0.12043366  0.50011671  0.13800957]
[ 0.0528084   0.17827692  0.44236813  0.87758732]
[ 0.94926413  0.47816742  0.46111934  0.63728903]]
leg2 array :
[[ 1.  1.  1.  1.]
[ 1.  1.  1.  1.]
[ 1.  1.  1.  1.]]

Hypotenuse is as follows :
[[ 1.15362944  1.00722603  1.11808619  1.0094784 ]
[ 1.00139339  1.01576703  1.09347591  1.33047342]
[ 1.37880469  1.10844219  1.10119528  1.18580661]]```

Code 3 : Equivalent to sqrt(x1**2 + x2**2), element-wise.

 `# Python3 program explaining ` `# hypot() function ` ` `  `import` `numpy as np ` ` `  `leg1 ``=` `np.random.rand(``3``, ``4``) ` `print` `(``"leg1 array : \n"``, leg1) ` ` `  `leg2 ``=` `np.ones((``3``, ``4``)) ` `print` `(``"leg2 array : \n"``, leg2) ` ` `  `result ``=` `np.sqrt((leg1 ``*` `leg1) ``+` `(leg2 ``*` `leg2)) ` `print``(``"\nHypotenuse is as follows :"``) ` `print``(result) `

Output :

```leg1 array :
[[ 0.7015073   0.89047987  0.1595603   0.27557254]
[ 0.67249153  0.16430312  0.70137114  0.48763522]
[ 0.68067777  0.52154819  0.04339669  0.2239366 ]]
leg2 array :
[[ 1.  1.  1.  1.]
[ 1.  1.  1.  1.]
[ 1.  1.  1.  1.]]

Hypotenuse is as follows :
[[ 1.15362944  1.00722603  1.11808619  1.0094784 ]
[ 1.00139339  1.01576703  1.09347591  1.33047342]
[ 1.37880469  1.10844219  1.10119528  1.18580661]]```

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