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.
The actual object to check.
The desired, expected object.
Desired precision, default is 6.
The error message to be printed in case of failure.
If True, the conflicting values are appended to the error message.
If actual and desired are not equal up to specified precision.
Raises an AssertionError if two objects are not equal up to desired precision.
assert_allclose
np.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)
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