NumPy : Beginner's Guide - Third Edition

Time for action – comparing with assert_array_almost_equal_nulp

Let's see the assert_array_almost_equal_nulp() function in action:

1. Determine the machine epsilon with the finfo() function:

   eps = np.finfo(float).eps
   print("EPS", eps)

   The epsilon would be as follows:

   EPS 2.22044604925e-16
   

2. Compare 1.0 with 1 + epsilon using the assert_almost_equal_nulp() function. Do the same for 1 + 2 * epsilon:

   print("1", np.testing.assert_array_almost_equal_nulp(1.0, 1.0 + eps))
   print("2", np.testing.assert_array_almost_equal_nulp(1.0, 1.0 + 2 * eps))

   The result is as follows:

   1 None
   2
   Traceback (most recent call last):
     …
    assert_array_almost_equal_nulp
       raise AssertionError(msg)
   AssertionError: X and Y are not equal to 1 ULP (max is 2)
   

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