Python | Numpy np.assert_approx_equal() method

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.

Python3 1=1

# 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 :

Python3 1=1

# 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])

Python | Numpy np.assert_approx_equal() method

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