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Python | Numpy np.assert_approx_equal() method

Python | numpy.assert_allclose() method

Last Updated : 17 Sep, 2019

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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])

Python | Numpy np.assert_approx_equal() method

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Article Tags :

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Python-numpy

Practice Tags :

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