# NumPy sqrt() - Square Root of Matrix Elements

Published on August 3, 2022 By Pankaj
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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.]]
``````

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        ])
>>>
``````

## 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 Pankaj

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Developer and author at DigitalOcean.