numpy.sqrt() in Python

numpy.sqrt() in Python is a function from the NumPy library used to compute the square root of each element in an array or a single number. It returns a new array of the same shape with the square roots of the input values. The function handles both positive and negative numbers, returning NaN for negative inputs when working with real numbers.

Example:

import numpy as np a = np.array([1, 4, 9, 16, 25]) b = np.sqrt(a) print(b) 

[1. 2. 3. 4. 5.] 

Syntax

numpy.sqrt()

Parameters:

• array : [array_like] Input values whose square roots have to be determined.
• out : [ndarray, optional] Alternate array object in which to put the result; if provided, it must have the same shape as arr.

Return Type: [ndarray] Returns the square root of the number in an array.

Examples of numpy.sqrt()

Example 1: Square Root of Positive Integers

This example demonstrates how to compute the square root of an array of positive integers using numpy.sqrt().

import numpy as geek a = geek.sqrt([1, 4, 9, 16]) b = geek.sqrt([6, 10, 18]) print(a) print(b) 

[1. 2. 3. 4.] [2.44948974 3.16227766 4.24264069] 

Example 2: Square Root of Complex Numbers

This example shows how to compute the square root of complex numbers using numpy.sqrt().

import numpy as geek a = geek.sqrt([4, -1, -5 + 9J]) print(a) 

[2. +0.j 0. +1.j 1.62721083+2.76546833j] 

Example 3: Square Root of Negative Real Numbers

This example illustrates how numpy.sqrt() handles negative real numbers, which results in NaN for real number inputs.

import numpy as geek a = geek.sqrt([-4, 5, -6]) print(a) 

Output

[ nan 2.23606798 nan]

Explanation: The code applies numpy.sqrt() to an array with negative real numbers. Since square roots of negative real numbers are undefined in the real number system, it returns NaN for those values.