Tutorial

NumPy sqrt() - Square Root of Matrix Elements

Published on August 3, 2022
author

Pankaj

NumPy sqrt() - Square Root of Matrix Elements

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Python NumPy module is used to work with multidimensional arrays and matrix manipulations. We can use NumPy sqrt() function to get the square root of the matrix elements.

Python NumPy sqrt() Example

import numpy

array_2d = numpy.array([[1, 4], [9, 16]], dtype=numpy.float)

print(array_2d)

array_2d_sqrt = numpy.sqrt(array_2d)

print(array_2d_sqrt)

Output:

[[ 1.  4.]
 [ 9. 16.]]
[[1. 2.]
 [3. 4.]]
Python Numpy Sqrt Example
Python Numpy sqrt() Example

Let’s look at another example where the matrix elements are not square of integers. This time we will use the Python interpreter.

>>> import numpy
>>> 
>>> array = numpy.array([[1, 3], [5, 7]], dtype=numpy.float)
>>> 
>>> print(array)
[[1. 3.]
 [5. 7.]]
>>> 
>>> array_sqrt = numpy.sqrt(array)
>>> 
>>> print(array_sqrt)
[[1.         1.73205081]
 [2.23606798 2.64575131]]
>>> 

NumPy sqrt() Infinity Example

Let’s see what happens when we have infinity as the matrix element.

>>> array = numpy.array([1, numpy.inf])
>>> 
>>> numpy.sqrt(array)
array([ 1., inf])
>>> 

Complex Numbers

>>> array = numpy.array([1 + 2j, -3 + 4j], dtype=numpy.complex)
>>> 
>>> numpy.sqrt(array)
array([1.27201965+0.78615138j, 1.        +2.j        ])
>>> 
Numpy Sqrt Complex Numbers
Numpy Sqrt Complex Numbers

Negative Numbers

>>> array = numpy.array([4, -4])
>>> 
>>> numpy.sqrt(array)
__main__:1: RuntimeWarning: invalid value encountered in sqrt
array([ 2., nan])
>>> 

The square root of a matrix with negative numbers will throw RuntimeWarning and the square root of the element is returned as nan. Reference: NumPy Docs

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Pankaj

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