numpy.testing.assert_array_almost_equal_nulp

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.
Returns:	None
Raises:	AssertionError If the spacing between x and y for one or more elements is larger than nulp.

See also

assert_array_max_ulp

Check that all items of arrays differ in at most N Units in the Last Place.

spacing

Return the distance between x and the nearest adjacent number.

Notes

An assertion is raised if the following condition is not met:

abs(x - y) <= nulps * spacing(maximum(abs(x), abs(y)))

Examples

>>> 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)