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a e�h� � @ sX d Z ddlmZ dgZdd� Zdd� Zdd � Zd d � Zd d � Z dd� Z G dd� d�Z dS )zEMixin classes for custom array types that don't inherit from ndarray.� )�umath�NDArrayOperatorsMixinc C s& z | j du W S ty Y dS 0 dS )z)True when __array_ufunc__ is set to None.NF)Z__array_ufunc__�AttributeError)�obj� r ��/root/rpmbuild/BUILDROOT/imh-python39-modules-3.9.7-92.el8.x86_64/opt/imh-python/lib/python3.9/site-packages/numpy/lib/mixins.py�_disables_array_ufunc s r c s � fdd�}d� |�|_|S )z>Implement a forward binary method with a ufunc, e.g., __add__.c s t |�r tS � | |�S �N�r �NotImplemented��self�other��ufuncr r �func s z _binary_method.<locals>.func�__{}__��format�__name__�r �namer r r r �_binary_method s r c s � fdd�}d� |�|_|S )zAImplement a reflected binary method with a ufunc, e.g., __radd__.c s t |�r tS � || �S r r r r r r r s z&_reflected_binary_method.<locals>.funcz__r{}__r r r r r �_reflected_binary_method s r c s � fdd�}d� |�|_|S )zAImplement an in-place binary method with a ufunc, e.g., __iadd__.c s � | || fd�S )N)�outr r r r r r & s z$_inplace_binary_method.<locals>.funcz__i{}__r r r r r �_inplace_binary_method$ s r c C s t | |�t| |�t| |�fS )zEImplement forward, reflected and inplace binary methods with a ufunc.)r r r )r r r r r �_numeric_methods, s �r c s � fdd�}d� |�|_|S )z.Implement a unary special method with a ufunc.c s � | �S r r )r r r r r 5 s z_unary_method.<locals>.funcr r r r r r � _unary_method3 s r c @ s� e Zd ZdZdZeejd�Zeej d�Z eej d�Z eej d�Zeejd�Zeejd�Zeejd �\ZZZeejd �\ZZZeej d �\Z Z Z eej 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 ) r a 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__Z less_equal�__le__�equal�__eq__� not_equal�__ne__Zgreater�__gt__Z greater_equal�__ge__r r$ �__add__�__radd__�__iadd__�subtract�__sub__�__rsub__�__isub__�multiply�__mul__�__rmul__�__imul__r' � __matmul__� __rmatmul__� __imatmul__Z true_divide� __truediv__� __rtruediv__� __itruediv__Z floor_divide� __floordiv__� __rfloordiv__� __ifloordiv__� remainder�__mod__�__rmod__�__imod__r+ � __divmod__r � __rdivmod__�power�__pow__�__rpow__�__ipow__Z left_shift� __lshift__� __rlshift__� __ilshift__Z right_shift� __rshift__� __rrshift__� __irshift__Z bitwise_and�__and__�__rand__�__iand__Z bitwise_xor�__xor__�__rxor__�__ixor__Z bitwise_or�__or__�__ror__�__ior__r �negative�__neg__Zpositive�__pos__�absolute�__abs__r5 � __invert__r r r r r ; sJ L � � � � � N) r8 Z numpy.corer r: �__all__r r r r r r r r r r r �<module> s
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