assert_array_almost_equal(x, y, decimal=6, err_msg='', verbose=True)

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

x : array_like

The actual object to check.

y : array_like

The desired, expected object.

decimal : int, optional

Desired precision, default is 6.

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.

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

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

Examples

the first assert does not raise an exception

This example is valid syntax, but we were not able to check execution

>>> np.testing.assert_array_almost_equal([1.0,2.333,np.nan],
...                                      [1.0,2.333,np.nan])

This example is valid syntax, but we were not able to check execution

>>> np.testing.assert_array_almost_equal([1.0,2.33333,np.nan],
...                                      [1.0,2.33339,np.nan], decimal=5)
Traceback (most recent call last):
    ...
AssertionError:
Arrays are not almost equal to 5 decimals
<BLANKLINE>
Mismatched elements: 1 / 3 (33.3%)
Max absolute difference: 6.e-05
Max relative difference: 2.57136612e-05
 x: array([1.     , 2.33333,     nan])
 y: array([1.     , 2.33339,     nan])

This example is valid syntax, but we were not able to check execution

>>> np.testing.assert_array_almost_equal([1.0,2.33333,np.nan],
...                                      [1.0,2.33333, 5], decimal=5)
Traceback (most recent call last):
    ...
AssertionError:
Arrays are not almost equal to 5 decimals
<BLANKLINE>
x and y nan location mismatch:
 x: array([1.     , 2.33333,     nan])
 y: array([1.     , 2.33333, 5.     ])

See :

Back References

The following pages refer to to this document either explicitly or contain code examples using this.

numpy.testing._private.utils.assert_array_less numpy.testing._private.utils.assert_almost_equal

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GitHub : /numpy/testing/_private/utils.py#938
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