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File: //proc/thread-self/root/usr/local/lib/python3.7/test/__pycache__/test_statistics.cpython-37.pyc
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�N)�Decimal)�FractioncCst�d|�S)z:Return -1.0 for negatives, including -0.0, otherwise +1.0.�)�math�copysign)�x�r�0/usr/local/lib/python3.7/test/test_statistics.py�signsr
cCsZt|�t|�k	rdSt|t�r2t�|�o0t�|�S|��d}|��d}||koX|dkS)a�Return True if a and b are both the same kind of NAN.

    >>> _nan_equal(Decimal('NAN'), Decimal('NAN'))
    True
    >>> _nan_equal(Decimal('sNAN'), Decimal('sNAN'))
    True
    >>> _nan_equal(Decimal('NAN'), Decimal('sNAN'))
    False
    >>> _nan_equal(Decimal(42), Decimal('NAN'))
    False

    >>> _nan_equal(float('NAN'), float('NAN'))
    True
    >>> _nan_equal(float('NAN'), 0.5)
    False

    >>> _nan_equal(float('NAN'), Decimal('NAN'))
    False

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rcCs:tt|�t|��}t||�}|r*||ntd�}||fS)z�Return the absolute and relative errors between two numbers.

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    �inf)�max�absr)�actual�expected�base�abs_err�rel_errrrr	�_calc_errors<s
r��-���q=�H�����z>cCs�|dks|dkrtd��t�|�s,t�|�r0dS||kr<dSt�|�sPt�|�rTdSt||�}t||tt|�t|���}||kS)a�approx_equal(x, y [, tol [, rel]]) => True|False

    Return True if numbers x and y are approximately equal, to within some
    margin of error, otherwise return False. Numbers which compare equal
    will also compare approximately equal.

    x is approximately equal to y if the difference between them is less than
    an absolute error tol or a relative error rel, whichever is bigger.

    If given, both tol and rel must be finite, non-negative numbers. If not
    given, default values are tol=1e-12 and rel=1e-7.

    >>> approx_equal(1.2589, 1.2587, tol=0.0003, rel=0)
    True
    >>> approx_equal(1.2589, 1.2587, tol=0.0001, rel=0)
    False

    Absolute error is defined as abs(x-y); if that is less than or equal to
    tol, x and y are considered approximately equal.

    Relative error is defined as abs((x-y)/x) or abs((x-y)/y), whichever is
    smaller, provided x or y are not zero. If that figure is less than or
    equal to rel, x and y are considered approximately equal.

    Complex numbers are not directly supported. If you wish to compare to
    complex numbers, extract their real and imaginary parts and compare them
    individually.

    NANs always compare unequal, even with themselves. Infinities compare
    approximately equal if they have the same sign (both positive or both
    negative). Infinities with different signs compare unequal; so do
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    to compare floats with equality. Instead the usual procedure is to test
    them with some (hopefully small!) allowance for error.

    The ``approx_equal`` function allows you to specify either an absolute
    error tolerance, or a relative error, or both.

    Absolute error tolerances are simple, but you need to know the magnitude
    of the quantities being compared:

    >>> approx_equal(12.345, 12.346, tol=1e-3)
    True
    >>> approx_equal(12.345e6, 12.346e6, tol=1e-3)  # tol is too small.
    False

    Relative errors are more suitable when the values you are comparing can
    vary in magnitude:

    >>> approx_equal(12.345, 12.346, rel=1e-4)
    True
    >>> approx_equal(12.345e6, 12.346e6, rel=1e-4)
    True

    but a naive implementation of relative error testing can run into trouble
    around zero.

    If you supply both an absolute tolerance and a relative error, the
    comparison succeeds if either individual test succeeds:

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        test attributes of the same name (by default, 0).

        The objects may be either numbers, or sequences of numbers. Sequences
        are tested element-by-element.

        >>> class MyTest(NumericTestCase):
        ...     def test_number(self):
        ...         x = 1.0/6
        ...         y = sum([x]*6)
        ...         self.assertApproxEqual(y, 1.0, tol=1e-15)
        ...     def test_sequence(self):
        ...         a = [1.001, 1.001e-10, 1.001e10]
        ...         b = [1.0, 1e-10, 1e10]
        ...         self.assertApproxEqual(a, b, rel=1e-3)
        ...
        >>> import unittest
        >>> from io import StringIO  # Suppress test runner output.
        >>> suite = unittest.TestLoader().loadTestsFromTestCase(MyTest)
        >>> unittest.TextTestRunner(stream=StringIO()).run(suite)
        <unittest.runner.TextTestResult run=2 errors=0 failures=0>

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