bundles / numpy 2.5.0.dev0+git20251130.2de293a / numpy / testing / _private / utils / assert_array_almost_equal
function
numpy.testing._private.utils:assert_array_almost_equal
source: build-install/usr/lib/python3.14/site-packages/numpy/testing/_private/utils.py :1126
Signature
def assert_array_almost_equal ( actual , desired , decimal = 6 , err_msg = '' , verbose = True ) Summary
Raises an AssertionError if two objects are not equal up to desired precision.
Extended Summary
The test verifies identical shapes and that the elements of actual and desired satisfy
abs(desired-actual) < 1.5 * 10**(-decimal)That is a looser test than originally documented, but agrees with what the actual implementation did up to rounding vagaries. An exception is raised at shape mismatch or conflicting values. In contrast to the standard usage in numpy, NaNs are compared like numbers, no assertion is raised if both objects have NaNs in the same positions.
Parameters
actual: array_likeThe actual object to check.
desired: array_likeThe desired, expected object.
decimal: int, optionalDesired precision, default is 6.
err_msg: str, optionalThe error message to be printed in case of failure.
verbose: bool, optionalIf True, the conflicting values are appended to the error message.
Raises
: AssertionErrorIf actual and desired are not equal up to specified precision.
Examples
the first assert does not raise an exceptionnp.testing.assert_array_almost_equal([1.0,2.333,np.nan], [1.0,2.333,np.nan])
np.testing.assert_array_almost_equal([1.0,2.33333,np.nan], [1.0,2.33339,np.nan], decimal=5)
np.testing.assert_array_almost_equal([1.0,2.33333,np.nan], [1.0,2.33333, 5], decimal=5)
See also
- assert_allclose
Compare two array_like objects for equality with desired relative and/or absolute precision.
- assert_array_almost_equal_nulp
- assert_array_max_ulp
- assert_equal
Aliases
-
numpy.testing.assert_array_almost_equal