Related Articles

# Python | numpy.assert_allclose() method

• Last Updated : 17 Sep, 2019

With the help of `numpy.assert_allclose()` method, we can get the assertion errors when two array objects are not equal upto the mark by using `numpy.assert_allclose()`.

Syntax : `numpy.assert_allclose(actual_array, desired_array)`

Return : Return the Assertion error if two array objects are not equal.

Example #1 :
In this example we can see that using `numpy.assert_allclose()` method, we are able to get the assertion error if two arrays are not equal.

 `# import numpy``import` `numpy as np`` ` `# using numpy.assert_allclose() method``gfg1 ``=` `[``1``, ``2``, ``3``]``gfg2 ``=` `np.array(gfg1)`` ` `if` `np.testing.assert_allclose(gfg1, gfg2):``     ``print``(``"Matched"``)`

Output :

Matched

Example #2 :

 `# import numpy``import` `numpy as np`` ` `# using numpy.assert_allclose() method``gfg1 ``=` `[``1``, ``2``, ``3``]``gfg2 ``=` `np.array([``4``, ``5``, ``6``])`` ` `print``(np.testing.assert_allclose(gfg1, gfg2))`

Output :

Mismatch: 100%
Max absolute difference: 3
Max relative difference: 0.75
gfg1: array([1, 2, 3])
gfg2: array([4, 5, 6])

Attention geek! Strengthen your foundations with the Python Programming Foundation Course and learn the basics.

To begin with, your interview preparations Enhance your Data Structures concepts with the Python DS Course. And to begin with your Machine Learning Journey, join the Machine Learning – Basic Level Course

My Personal Notes arrow_drop_up