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numpy.hypot() in Python
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.
Syntax :
numpy.exp2(arr1, arr2[, out]) = ufunc 'hypot') :
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]]
References :
https://docs.scipy.org/doc/numpy-dev/reference/generated/numpy.hypot.html#numpy.hypot
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