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Mixin classes for custom array types that don't inherit from ndarray.
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ÚNDArrayOperatorsMixinc ó> | j du S # t $ r Y yw xY w)z)True when __array_ufunc__ is set to None.NF)Ú__array_ufunc__ÚAttributeError)Úobjs úCH:\Change_password\venv_build\Lib\site-packages\numpy/lib/mixins.pyÚ_disables_array_ufuncr s* ðØ×"Ñ" dÐ*Ð*øÜ ò Ùðús c ó( fd}d| d|_ |S )z>Implement a forward binary method with a ufunc, e.g., __add__.c ó8 t |« rt S | |« S ©N©r ÚNotImplemented©ÚselfÚotherÚufuncs r Úfuncz _binary_method.<locals>.func s ø Ü Ô 'Ü!Ð !ÙT5Ó!Ð!ó Ú__©Ú__name__©r Únamer s ` r Ú_binary_methodr s ø ô"ð bMDMØ Kr c ó( fd}d| d|_ |S )zAImplement a reflected binary method with a ufunc, e.g., __radd__.c ó8 t |« rt S || « S r r r s r r z&_reflected_binary_method.<locals>.func s ø Ü Ô 'Ü!Ð !ÙUDÓ!Ð!r Ú__rr r r s ` r Ú_reflected_binary_methodr s ø ô"ð $rNDMØ Kr c ó( fd}d| d|_ |S )zAImplement an in-place binary method with a ufunc, e.g., __iadd__.c ó | || f¬« S )N)Úout© r s r r z$_inplace_binary_method.<locals>.func& s ø ÙT5 t gÔ.Ð.r Ú__ir r r s ` r Ú_inplace_binary_methodr# $ s ø ô/à$rNDMØ Kr c óH t | |« t | |« t | |« fS )zEImplement forward, reflected and inplace binary methods with a ufunc.)r r r# )r r s r Ú_numeric_methodsr% , s* ä 5 $Ó 'Ü $ U¨DÓ 1Ü " 5¨$Ó /ð 1ð 1r c ó( fd}d| d|_ |S )z.Implement a unary special method with a ufunc.c ó | « S r r! )r r s r r z_unary_method.<locals>.func5 s ø ÙT{Ðr r r r s ` r Ú _unary_methodr( 3 s ø ôàbMDMØ Kr c ó> e Zd ZdZddlmZ dZ eej d« Z
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eej d« Z eej d« Z eej d« Z eej" d « Z eej& d
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« Z eej, d « \ ZZZ eej4 d « \ ZZ Z eej< d « \ Z Z Z! eejD d« \ Z#Z$Z% eejL d« \ Z'Z(Z) eejT d« \ Z+Z,Z- eej\ d« \ Z/Z0Z1 eejd d« Z3 e4ejd d« Z5 eejl d« \ Z7Z8Z9 eejt d« \ Z;Z<Z= eej| d« \ Z?Z@ZA eej d« \ ZCZDZE eej d« \ ZGZHZI eej d« \ ZKZLZM eNej d« ZP eNej¢ d« ZR eNej¦ d« ZT eNejª d « ZVy ) r aî Mixin defining all operator special methods using __array_ufunc__.
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This class implements the special methods for almost all of Python's
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builtin operators defined in the `operator` module, including comparisons
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(``==``, ``>``, etc.) and arithmetic (``+``, ``*``, ``-``, etc.), by
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deferring to the ``__array_ufunc__`` method, which subclasses must
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implement.
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It is useful for writing classes that do not inherit from `numpy.ndarray`,
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but that should support arithmetic and numpy universal functions like
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arrays as described in :external+neps:doc:`nep-0013-ufunc-overrides`.
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As an trivial example, consider this implementation of an ``ArrayLike``
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class that simply wraps a NumPy array and ensures that the result of any
|
arithmetic operation is also an ``ArrayLike`` object:
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>>> import numbers
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>>> class ArrayLike(np.lib.mixins.NDArrayOperatorsMixin):
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... def __init__(self, value):
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... self.value = np.asarray(value)
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...
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... # One might also consider adding the built-in list type to this
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... # list, to support operations like np.add(array_like, list)
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... _HANDLED_TYPES = (np.ndarray, numbers.Number)
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...
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... def __array_ufunc__(self, ufunc, method, *inputs, **kwargs):
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... out = kwargs.get('out', ())
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... for x in inputs + out:
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... # Only support operations with instances of
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... # _HANDLED_TYPES. Use ArrayLike instead of type(self)
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... # for isinstance to allow subclasses that don't
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... # override __array_ufunc__ to handle ArrayLike objects.
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... if not isinstance(
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... x, self._HANDLED_TYPES + (ArrayLike,)
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... ):
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... return NotImplemented
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...
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... # Defer to the implementation of the ufunc
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... # on unwrapped values.
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... inputs = tuple(x.value if isinstance(x, ArrayLike) else x
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... for x in inputs)
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... if out:
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... kwargs['out'] = tuple(
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... x.value if isinstance(x, ArrayLike) else x
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... for x in out)
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... result = getattr(ufunc, method)(*inputs, **kwargs)
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...
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... if type(result) is tuple:
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... # multiple return values
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... return tuple(type(self)(x) for x in result)
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... elif method == 'at':
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... # no return value
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... return None
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... else:
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... # one return value
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... return type(self)(result)
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...
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... def __repr__(self):
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... return '%s(%r)' % (type(self).__name__, self.value)
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In interactions between ``ArrayLike`` objects and numbers or numpy arrays,
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the result is always another ``ArrayLike``:
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>>> x = ArrayLike([1, 2, 3])
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>>> x - 1
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ArrayLike(array([0, 1, 2]))
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>>> 1 - x
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ArrayLike(array([ 0, -1, -2]))
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>>> np.arange(3) - x
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ArrayLike(array([-1, -1, -1]))
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>>> x - np.arange(3)
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ArrayLike(array([1, 1, 1]))
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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.
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