U ã€C^Aã@svdZddlmZmZmZddlZddlmZdgZ dd„Z dd „Z d d „Z d d „Z dd„Zdd„ZGdd„deƒZdS)zEMixin classes for custom array types that don't inherit from ndarray.é)ÚdivisionÚabsolute_importÚprint_functionN)ÚumathÚNDArrayOperatorsMixincCs(z |jdkWStk r"YdSXdS)z)True when __array_ufunc__ is set to None.NF)Z__array_ufunc__ÚAttributeError)Úobj©r ú3/tmp/pip-install-6_kvzl1k/numpy/numpy/lib/mixins.pyÚ_disables_array_ufunc s r cs‡fdd„}d |¡|_|S)z>Implement a forward binary method with a ufunc, e.g., __add__.cst|ƒr tSˆ||ƒS©N©r ÚNotImplemented©ÚselfÚother©Úufuncr r Úfuncsz_binary_method..funcú__{}__©ÚformatÚ__name__©rÚnamerr rr Ú_binary_methods  rcs‡fdd„}d |¡|_|S)zAImplement a reflected binary method with a ufunc, e.g., __radd__.cst|ƒr tSˆ||ƒSr r rrr r r sz&_reflected_binary_method..funcz__r{}__rrr rr Ú_reflected_binary_methods  rcs‡fdd„}d |¡|_|S)zAImplement an in-place binary method with a ufunc, e.g., __iadd__.csˆ|||fd�S)N)Úoutr rrr r r*sz$_inplace_binary_method..funcz__i{}__rrr rr Ú_inplace_binary_method(s  rcCst||ƒt||ƒt||ƒfS)zEImplement forward, reflected and inplace binary methods with a ufunc.)rrr)rrr r r Ú_numeric_methods0sþrcs‡fdd„}d |¡|_|S)z.Implement a unary special method with a ufunc.csˆ|ƒSr r )rrr r r9sz_unary_method..funcrrrr rr Ú _unary_method7s  r c@s¨eZdZdZeejdƒZeejdƒZ eej dƒZ eej dƒZ eejdƒZeejdƒZeejdƒ\ZZZeejd ƒ\ZZZeejd ƒ\ZZZeejd ƒ\Z Z!Z"e#j$j%d krºeej&d ƒ\Z'Z(Z)eej*dƒ\Z+Z,Z-eej.dƒ\Z/Z0Z1eej2dƒ\Z3Z4Z5eej6dƒZ7e8ej6dƒZ9eej:dƒ\Z;Zdƒ\Z?Z@ZAeejBdƒ\ZCZDZEeejFdƒ\ZGZHZIeejJdƒ\ZKZLZMeejNdƒ\ZOZPZQeRejSdƒZTeRejUdƒZVeRejWdƒZXeRejYdƒZZdS)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 <../../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. 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