numpy.testing.assert_array_almost_equal_nulp(x, y, nulp=1)
[source]
Compare two arrays relatively to their spacing.
This is a relatively robust method to compare two arrays whose amplitude is variable.
Parameters: |
x, y : array_like Input arrays. nulp : int, optional The maximum number of unit in the last place for tolerance (see Notes). Default is 1. |
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Returns: |
None |
Raises: |
AssertionError If the spacing between |
See also
assert_array_max_ulp
spacing
An assertion is raised if the following condition is not met:
abs(x - y) <= nulps * spacing(maximum(abs(x), abs(y)))
>>> x = np.array([1., 1e-10, 1e-20]) >>> eps = np.finfo(x.dtype).eps >>> np.testing.assert_array_almost_equal_nulp(x, x*eps/2 + x)
>>> np.testing.assert_array_almost_equal_nulp(x, x*eps + x) Traceback (most recent call last): ... AssertionError: X and Y are not equal to 1 ULP (max is 2)
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https://docs.scipy.org/doc/numpy-1.14.2/reference/generated/numpy.testing.assert_array_almost_equal_nulp.html