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•          numpy.testing.assert_array_almost_equal_nulp
•          numpy.testing.assert_array_max_ulp
•          numpy.testing.assert_array_equal
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numpy.testing.assert_allclose(actual, desired, rtol=1e-07, atol=0, equal_nan=True, 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) (note that allclose has different default values). It compares the difference between actual and desired to atol + rtol * abs(desired).

New in version 1.5.0.

Parameters

actualarray_like

Array obtained.

desiredarray_like

Array desired.

rtolfloat, optional

Relative tolerance.

atolfloat, optional

Absolute tolerance.

equal_nanbool, optional.

If True, NaNs will compare equal.

err_msgstr, optional

The error message to be printed in case of failure.

verbosebool, 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))
>>> np.testing.assert_allclose(x, y, rtol=1e-5, atol=0)