u!hNdZdgZdZdZdZdZdZdZGddZd S) zG Mixin classes for custom array types that don't inherit from ndarray. NDArrayOperatorsMixinc8 |jduS#t$rYdSwxYw)z)True when __array_ufunc__ is set to None.NF)__array_ufunc__AttributeError)objs Jc:\xampp_lite_8_4\www\timesheet\venv\Lib\site-packages\numpy/lib/mixins.py_disables_array_ufuncrs7"d** uus  c(fd}d|d|_|S)z>Implement a forward binary method with a ufunc, e.g., __add__.cHt|rtS||SNrNotImplementedselfotherufuncs rfuncz_binary_method..funcs+  ' ' "! !uT5!!!____name__rnamers` r_binary_methodrs2""""""MMMDM Krc(fd}d|d|_|S)zAImplement a reflected binary method with a ufunc, e.g., __radd__.cHt|rtS||Sr r rs rrz&_reflected_binary_method..funcs+  ' ' "! !uUD!!!r__rrrrs` r_reflected_binary_methodrs2"""""#$NNNDM Krc(fd}d|d|_|S)zAImplement an in-place binary method with a ufunc, e.g., __iadd__.c"|||fS)N)outrs rrz$_inplace_binary_method..func&suT5tg....r__irrrs` r_inplace_binary_methodr#$s0/////"$NNNDM Krc`t||t||t||fS)zEImplement forward, reflected and inplace binary methods with a ufunc.)rrr#)rrs r_numeric_methodsr%,s3 5$ ' ' $UD 1 1 "5$ / / 11rc(fd}d|d|_|S)z.Implement a unary special method with a ufunc.c|Sr r!)rrs rrz_unary_method..func5suT{{rrrrs` r _unary_methodr(3s0!MMMDM KrceZdZdZddlmZdZeej dZ eej dZ eej dZeejdZeejd Zeejd Zeejd \ZZZeejd \ZZZeejd \ZZ Z!eej"d\Z#Z$Z%eej&d\Z'Z(Z)eej*d\Z+Z,Z-eej.d\Z/Z0Z1eej2dZ3e4ej2dZ5eej6d\Z7Z8Z9eej:d\Z;Zd\Z?Z@ZAeejBd\ZCZDZEeejFd\ZGZHZIeejJd\ZKZLZMeNejOdZPeNejQdZReNejSdZTeNejUdZVdS)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 :external+neps:doc:`nep-0013-ufunc-overrides`. 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: >>> import numbers >>> 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. )umathr!ltleeqnegtgeaddsubmulmatmultruedivfloordivmoddivmodpowlshiftrshiftandxorornegposabsinvertN)Wr __module__ __qualname____doc__ numpy._corer+um __slots__rless__lt__ less_equal__le__equal__eq__ not_equal__ne__greater__gt__ greater_equal__ge__r%r2__add____radd____iadd__subtract__sub____rsub____isub__multiply__mul____rmul____imul__r5 __matmul__ __rmatmul__ __imatmul__ true_divide __truediv__ __rtruediv__ __itruediv__ floor_divide __floordiv__ __rfloordiv__ __ifloordiv__ remainder__mod____rmod____imod__r9 __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__rC __invert__r!rrrr;sMM\('''''I ^BGT * *F ^BM4 0 0F ^BHd + +F ^BL$ / /F ^BJ - -F ^B,d 3 3F#3"2265"A"AGXx"2"22;"F"FGXx"2"22;"F"FGXx+;+; 8,,(J [.>.>  /#/#+K|1A1A 2%2%.L-"2"22<"G"GGXx 844J**29h??K#3"228U"C"CGXx+;+; x,!,!(J [+;+; ,","(J ["2"22>5"I"IGXx"2"22>5"I"IGXx// tDDFGWmBK//GmBK//GmBK//Gry(33JJJrN) rF__all__rrrr#r%r(rr!rrrs # #111y4y4y4y4y4y4y4y4y4y4r