hypot() - ( NumPy Functions )

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Syntax

numpy.hypot(x, y, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj])

Example

import numpy as np

x = np.array([3, 4])
y = np.array([4, 3])

result = np.hypot(x, y)

print(result)

Output

[5.         5.        ]

Explanation

The numpy.hypot() function is used to compute the hypotenuse of a right-angled triangle given the lengths of its legs. It takes two arrays x and y of the same shape, and returns an array containing the hypotenuse of each corresponding triangle. Specifically, it computes the square root of the sum of the squares of the two input arrays.

Use

The numpy.hypot() function is useful in a variety of applications, such as:

• Computing the distance between two points in Euclidean space
• Computing the magnitude of a complex number

Important Points

• The numpy.hypot() function takes two arrays x and y of the same shape, and returns an array containing the hypotenuse of each corresponding right-angled triangle
• It computes the square root of the sum of the squares of the two input arrays
• The function is useful for computing the distance between two points in Euclidean space, or the magnitude of a complex number

Summary

In conclusion, the numpy.hypot() function is a useful tool for computing the hypotenuse of a right-angled triangle given the lengths of its legs. It takes two arrays x and y of the same shape, and returns an array containing the hypotenuse of each corresponding triangle. It is useful in a variety of applications, such as computing distances in Euclidean space or magnitudes of complex numbers.