o

���g��@sXdZd
dl
mZ
dg
Zdd�Zdd�Zdd	�Zd
d�Zdd
�Z	dd�Z
Gdd�d�ZdS)zEMixin classes for custom array types that don't inherit from ndarray.�)
�umath�NDArrayOperatorsMixinc

Cs"z|jd
uWSt
y


YdSw)z)True when __array_ufunc__ is set to None.NF)�__array_ufunc__�AttributeError)
�obj�r�;/usr/local/lib/python3.10/dist-packages/numpy/lib/mixins.py�_disables_array_ufuncs



�r	c��f
d
d�}d�|
�
|_
|S)z>Implement a forward binary method with a ufunc, e.g., __add__.cst|
�
rt
S�||
�S�
N�r	�NotImplemented��self�other�
�ufuncrr�func�



z_binary_method.<locals>.func�__{}__��format�__name__�r�namerrrr�_binary_method�
rcr
)zAImplement a reflected binary method with a ufunc, e.g., __radd__.cst|
�
rt
S�|
|�Srrrrrrrrz&_reflected_binary_method.<locals>.funcz__r{}__rrrrr�_reflected_binary_methodrrcr
)zAImplement an in-place binary method with a ufunc, e.g., __iadd__.cs�||
|f
d
�S)N)
�outrrrrrr&s
z$_inplace_binary_method.<locals>.funcz__i{}__rrrrr�_inplace_binary_method$�
rcCst||
�t
||
�t||
�fS)
zEImplement forward, reflected and inplace binary methods with a ufunc.)rrr)rrrrr�_numeric_methods,s

�r!cr
)z.Implement a unary special method with a ufunc.c

s�|�
Srr)
rrrrr5s
z_unary_method.<locals>.funcrrrrrr�
_unary_method3r r"c@s�
eZ
dZd
ZdZeejd�Zeej	d�Z
eejd�Zeej
d�Zeejd�Zeejd�Zeejd	�\ZZZeejd
�\ZZZeejd�\ZZZeej d�\Z!Z"Z#eej$d
�\Z%Z&Z'eej(d�\Z)Z*Z+eej,d�\Z-Z.Z/eej0d�Z1e2ej0d�Z3eej4d�\Z5Z6Z7eej8d�\Z9Z:Z;eej<d�\Z=Z>Z?eej@d�\ZAZBZCeejDd�\ZEZFZGeejHd�\ZIZJZKeLejMd�ZNeLejOd�ZPeLejQd�ZReLejSd�ZTdS)ra
Mixin defining all operator special methods using __array_ufunc__.

    This class implements the special methods for almost all of Python's
    builtin operators defined in the `operator` module, including comparisons
    (``==``, ``>``, etc.) and arithmetic (``+``, ``*``, ``-``, etc.), by
    deferring to the ``__array_ufunc__`` method, which subclasses must
    implement.

    It is useful for writing classes that do not inherit from `numpy.ndarray`,
    but that should support arithmetic and numpy universal functions like
    arrays as described in `A Mechanism for Overriding Ufuncs
    <https://numpy.org/neps/nep-0013-ufunc-overrides.html>`_.

    As an trivial example, consider this implementation of an ``ArrayLike``
    class that simply wraps a NumPy array and ensures that the result of any
    arithmetic operation is also an ``ArrayLike`` object::

        class ArrayLike(np.lib.mixins.NDArrayOperatorsMixin):
            def __init__(self, value):
                self.value = np.asarray(value)

            # One might also consider adding the built-in list type to this
            # list, to support operations like np.add(array_like, list)
            _HANDLED_TYPES = (np.ndarray, numbers.Number)

            def __array_ufunc__(self, ufunc, method, *inputs, **kwargs):
                out = kwargs.get('out', ())
                for x in inputs + out:
                    # Only support operations with instances of _HANDLED_TYPES.
                    # Use ArrayLike instead of type(self) for isinstance to
                    # allow subclasses that don't override __array_ufunc__ to
                    # handle ArrayLike objects.
                    if not isinstance(x, self._HANDLED_TYPES + (ArrayLike,)):
                        return NotImplemented

                # Defer to the implementation of the ufunc on unwrapped values.
                inputs = tuple(x.value if isinstance(x, ArrayLike) else x
                               for x in inputs)
                if out:
                    kwargs['out'] = tuple(
                        x.value if isinstance(x, ArrayLike) else x
                        for x in out)
                result = getattr(ufunc, method)(*inputs, **kwargs)

                if type(result) is tuple:
                    # multiple return values
                    return tuple(type(self)(x) for x in result)
                elif method == 'at':
                    # no return value
                    return None
                else:
                    # one return value
                    return type(self)(result)

            def __repr__(self):
                return '%s(%r)' % (type(self).__name__, self.value)

    In interactions between ``ArrayLike`` objects and numbers or numpy arrays,
    the result is always another ``ArrayLike``:

        >>> x = ArrayLike([1, 2, 3])
        >>> x - 1
        ArrayLike(array([0, 1, 2]))
        >>> 1 - x
        ArrayLike(array([ 0, -1, -2]))
        >>> np.arange(3) - x
        ArrayLike(array([-1, -1, -1]))
        >>> x - np.arange(3)
        ArrayLike(array([1, 1, 1]))

    Note that unlike ``numpy.ndarray``, ``ArrayLike`` does not allow operations
    with arbitrary, unrecognized types. This ensures that interactions with
    ArrayLike preserve a well-defined casting hierarchy.

    .. versionadded:: 1.13
    r�lt�le�eq�ne�gt�ge�add�sub�mul�matmul�truediv�floordiv�mod�divmod�pow�lshift�rshift�and�xor�or�neg�pos�abs�invertN)Ur�
__module__�__qualname__�__doc__�	__slots__r�um�less�__lt__�
less_equal�__le__�equal�__eq__�	not_equal�__ne__�greater�__gt__�
greater_equal�__ge__r!r)�__add__�__radd__�__iadd__�subtract�__sub__�__rsub__�__isub__�multiply�__mul__�__rmul__�__imul__r,�
__matmul__�__rmatmul__�__imatmul__�true_divide�__truediv__�__rtruediv__�__itruediv__�floor_divide�__floordiv__�
__rfloordiv__�
__ifloordiv__�	remainder�__mod__�__rmod__�__imod__r0�
__divmod__r�__rdivmod__�power�__pow__�__rpow__�__ipow__�
left_shift�
__lshift__�__rlshift__�__ilshift__�right_shift�
__rshift__�__rrshift__�__irshift__�bitwise_and�__and__�__rand__�__iand__�bitwise_xor�__xor__�__rxor__�__ixor__�
bitwise_or�__or__�__ror__�__ior__r"�negative�__neg__�positive�__pos__�absolute�__abs__r:�
__invert__rrrrr;sL
L









�

�

�




�

�




N)r=�
numpy.corerr?�__all__r	rrrr!r"rrrrr�<module>
s