U O8c@sXdZddlmZdgZddZddZdd Zd d Zd d Z ddZ GdddZ dS)zEMixin classes for custom array types that don't inherit from ndarray.)umathNDArrayOperatorsMixincCs(z |jdkWStk r"YdSXdS)z)True when __array_ufunc__ is set to None.NF)Z__array_ufunc__AttributeError)objr4/tmp/pip-unpacked-wheel-fd_gsd75/numpy/lib/mixins.py_disables_array_ufuncs rcsfdd}d||_|S)z>Implement a forward binary method with a ufunc, e.g., __add__.cst|r tS||SNrNotImplementedselfotherufuncrrfuncsz_binary_method..func__{}__format__name__rnamerrrr_binary_methods  rcsfdd}d||_|S)zAImplement a reflected binary method with a ufunc, e.g., __radd__.cst|r tS||Sr r r rrrrsz&_reflected_binary_method..funcz__r{}__rrrrr_reflected_binary_methods  rcsfdd}d||_|S)zAImplement an in-place binary method with a ufunc, e.g., __iadd__.cs|||fdS)N)outrr rrrr&sz$_inplace_binary_method..funcz__i{}__rrrrr_inplace_binary_method$s  rcCst||t||t||fS)zEImplement forward, reflected and inplace binary methods with a ufunc.)rrr)rrrrr_numeric_methods,srcsfdd}d||_|S)z.Implement a unary special method with a ufunc.cs|Sr r)r rrrr5sz_unary_method..funcrrrrrr _unary_method3s  rc@seZdZdZeejdZeejdZ eej dZ eej dZ eejdZeejdZeejd\ZZZeejd \ZZZeejd \ZZZeejd \Z Z!Z"eej#d \Z$Z%Z&eej'd \Z(Z)Z*eej+d\Z,Z-Z.eej/dZ0e1ej/dZ2eej3d\Z4Z5Z6eej7d\Z8Z9Z:eej;d\Zeej?d\Z@ZAZBeejCd\ZDZEZFeejGd\ZHZIZJeKejLdZMeKejNdZOeKejPdZQeKejRdZSdS)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 `_. 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 ltleeqnegtgeaddsubmulmatmultruedivfloordivmoddivmodpowlshiftrshiftandxorornegposabsinvertN)Tr __module__ __qualname____doc__rumZless__lt__Z less_equal__le__equal__eq__ not_equal__ne__Zgreater__gt__Z greater_equal__ge__rr$__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__rnegative__neg__Zpositive__pos__absolute__abs__r5 __invert__rrrrr;sRP                N) r8Z numpy.corerr9__all__rrrrrrrrrrrs