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bundles / numpy 2.5.0.dev0+git20251130.2de293a / numpy / testing / _private / utils / assert_almost_equal

function

numpy.testing._private.utils:assert_almost_equal

source: build-install/usr/lib/python3.14/site-packages/numpy/testing/_private/utils.py :507

Signature

def   assert_almost_equal ( actual ,  desired ,  decimal = 7 ,  err_msg = '' ,  verbose = True )

Summary

Raises an AssertionError if two items are not equal up to desired precision.

Extended Summary

The test verifies that the elements of actual and desired satisfy 

abs(desired-actual) < float64(1.5 * 10**(-decimal))

That is a looser test than originally documented, but agrees with what the actual implementation in assert_array_almost_equal did up to rounding vagaries. An exception is raised at conflicting values. For ndarrays this delegates to assert_array_almost_equal

Parameters

actual : array_like

The object to check.

desired : array_like

The expected object.

decimal : int, optional

Desired precision, default is 7.

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.

Examples

from numpy.testing import assert_almost_equal
assert_almost_equal(2.3333333333333, 2.33333334)
assert_almost_equal(2.3333333333333, 2.33333334, decimal=10)

assert_almost_equal(np.array([1.0,2.3333333333333]),
                    np.array([1.0,2.33333334]), decimal=9)

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_almost_equal