numpy.testing.assert_allclose

numpy.testing.assert_allclose(actual, desired, rtol=1e-07, atol=0, equal_nan=False, err_msg='', verbose=True) [source]

Raises an AssertionError if two objects are not equal up to desired tolerance.

The test is equivalent to allclose(actual, desired, rtol, atol). It compares the difference between actual and desired to atol + rtol * abs(desired).

New in version 1.5.0.

Parameters:	actual : array_like Array obtained. desired : array_like Array desired. rtol : float, optional Relative tolerance. atol : float, optional Absolute tolerance. equal_nan : bool, optional. If True, NaNs will compare equal. err_msg : str, optional The error message to be printed in case of failure. verbose : bool, optional If True, the conflicting values are appended to the error message.
Raises:	AssertionError If actual and desired are not equal up to specified precision.

See also

assert_array_almost_equal_nulp, assert_array_max_ulp

Examples

>>> x = [1e-5, 1e-3, 1e-1]
>>> y = np.arccos(np.cos(x))
>>> assert_allclose(x, y, rtol=1e-5, atol=0)