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Module « numpy.testing »

Fonction assert_approx_equal - module numpy.testing

Signature de la fonction assert_approx_equal

def assert_approx_equal(actual, desired, significant=7, err_msg='', verbose=True) 

Description

help(numpy.testing.assert_approx_equal)

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
----------
actual : scalar
    The object to check.
desired : scalar
    The expected object.
significant : 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.

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
--------
>>> 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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