+ ei csHRtR.tRtRtRtRtRtRt!RR4tR #) zG Mixin classes for custom array types that don't inherit from ndarray. NDArrayOperatorsMixincsDVPRJ# \dR#i;i)z)True when __array_ufunc__ is set to None.NF)Z__array_ufunc__ZAttributeError)Zobjs&7/usr/lib64/python3.14/site-packages/numpy/lib/mixins.py_disables_array_ufuncrs*""d** s  c*aV3RlpRV R2VnV#)z>Implement a forward binary method with a ufunc, e.g., __add__.csB<\V4'd\#S!W4#NrZNotImplementedselfZotherufunc&&rfuncZ_binary_method..funcs  ' '! !T!!____name__rnamer f& r_binary_methodrs"bMDM Kr c*aV3RlpRV R2VnV#)zAImplement a reflected binary method with a ufunc, e.g., __radd__.csB<\V4'd\#S!W4#rrrr rr Z&_reflected_binary_method..funcs  ' '! !U!!r Z__rr r rrr_reflected_binary_methodrs"$rNDM Kr cr)zAImplement an in-place binary method with a ufunc, e.g., __iadd__.cs<S!WV3R7#))Zoutrr rr Z$_inplace_binary_method..func&sTtg..r Z__ir r rrr_inplace_binary_methodr$s/$rNDM Kr csB\W4\W4\W43#)zEImplement forward, reflected and inplace binary methods with a ufunc.)rrr)rrs&&r_numeric_methodsr,s$ 5 ' $U 1 "5 / 11r cr)z.Implement a unary special method with a ufunc.cs<S!V4#rr)rrs&rr Z_unary_method..func5s T{r r r rrr _unary_methodr3sbMDM Kr csH]tRt^;tRt^RIHtRt] !]PR4t ] !]PR4t ] !]PR4t] !]P R4t] !]P$R4t] !]P(R4t]!]P.R 4wttt]!]P6R 4wttt]!]P>R 4wt t!t"]!]PFR 4wt$t%t&]!]PNR 4wt(t)t*]!]PVR4wt,t-t.]!]P^R4wt0t1t2] !]PfR4t4]5!]PfR4t6]!]PnR4wt8t9t:]!]PvR4wt]!]P~R4wt@tAtB]!]PR4wtDtEtF]!]PR4wtHtItJ]!]PR4wtLtMtN]O!]PR4tQ]O!]PR4tS]O!]PR4tU]O!]PR4tWRtXR#)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. 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