numpy.testing.assert_approx_equal(actual, desired, significant=7, err_msg='', verbose=True)
[source]
Raises an AssertionError if two items are not equal up to significant digits.
Note
It is recommended to use one of assert_allclose
, assert_array_almost_equal_nulp
or assert_array_max_ulp
instead of this function for more consistent floating point comparisons.
Given two numbers, check that they are approximately equal. Approximately equal is defined as the number of significant digits that agree.
Parameters: |
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Raises: |
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See also
assert_allclose
assert_array_almost_equal_nulp
, assert_array_max_ulp
, assert_equal
>>> np.testing.assert_approx_equal(0.12345677777777e-20, 0.1234567e-20) >>> np.testing.assert_approx_equal(0.12345670e-20, 0.12345671e-20, ... significant=8) >>> np.testing.assert_approx_equal(0.12345670e-20, 0.12345672e-20, ... significant=8) Traceback (most recent call last): ... AssertionError: Items are not equal to 8 significant digits: ACTUAL: 1.234567e-21 DESIRED: 1.2345672e-21
the evaluated condition that raises the exception is
>>> abs(0.12345670e-20/1e-21 - 0.12345672e-20/1e-21) >= 10**-(8-1) True
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https://docs.scipy.org/doc/numpy-1.17.0/reference/generated/numpy.testing.assert_approx_equal.html